IL292732B2 - Method and system for maintaining line of sight between a follower and a followee - Google Patents

Description

LINE OF SIGHT MAINTENANCE DURING OBJECT TRACKING FIELD OF THE PRESENTLY DISCLOSED SUBJECT MATTER The presently disclosed subject matter relates to the field of sensor object tracking.

BACKGROUND Unmanned aerial vehicles (also known as UAVs, unmanned aerial systems or drones) are sometimes utilized as an airborne system for remote observation and tracking of objects. To this end, UAVs are equipped with some type of data surveillance system comprising a sensing device, such as a camera, radar, sonar, etc. The data surveillance system is used for surveying a scene and can be further operable to lock onto and track an object of interest located in the surveyed scene.

GENERAL DESCRIPTION One challenge related to autonomous tracking of moving objects by a sensing (e.g. imaging) device mounted onboard an aircraft is related to the difficulty of continuously maintaining the tracked object within the line of sight (LOS) of the sensing device. This task becomes more difficult if the tracked object is moving in an area with complex topography and/or landcover (which includes objects like trees or hills, as well as man-made objects such as buildings and other structures) that can hide the object of interest from the sensing device, potentially resulting in losing track of the object. LOS to a tracked object can also be obstructed by clouds residing in the sky below the observing surveillance system onboard the aircraft. Losing track of an object causes discontinuities in the gathered data and therefore degrades the tracking process. Furthermore, it is often difficult and sometimes impossible to regain track of the lost object, it is important to avoid losing track of an object of interest in the first place.

The term "complex topography" is used herein to include topography characterized by elements that may obstruct a line of sight between an aircraft and an object of interest. Likewise, the term "complex landcover" as used herein includes landcover characterized by elements that may obstruct a line of sight between an aircraft and an object of interest.

One example of a possible object tracking scenario in complex topography is a vehicle traveling along a winding road in a mountain area, where LOS to the vehicle may be blocked by the face of a mountain. An example of an object tracking scenario in an area with complex landcover, is a vehicle traveling along a road that passes through forested areas, where LOS to the vehicle may be blocked by trees. Another example of an object tracking scenario in an area with complex landcover, is a vehicle traveling in a city area with tall buildings, where LOS to the vehicle may be blocked by buildings.

The presently disclosed subject matter includes a system and method that provides autonomous flight monitoring and control over an aircraft that helps to maintain continuous object tracking by a sensing device (e.g. imaging payload such as a camera) mounted on the aircraft (e.g. UAV). The disclosed system and method provide real-time continuous LOS validation that helps to reduce the likelihood of line of sight obstruction or interception while tracking an object.

According to a first aspect of the presently disclosed subject matter, there is provided a surveillance system mountable on an aircraft, the surveillance system comprising at least one sensing device; the surveillance system being configured to observe a target object (e.g. moving object, stationary object, structure, area, etc.); the surveillance system comprises a processing circuitry configured, while observing the target object, while flying autonomously, to execute a process, comprising: estimating a future flight route of the aircraft at a future time-interval; predicting at least one predicted line of sight (LOS) between the surveillance system and the target object during the future time-interval; comparing the at least one predicted LOS relative to environmental elements located in an area of flight; determining whether the at least one predicted LOS is obstructed by the environmental elements; and in case the at least one predicted LOS is obstructed: generating an updated flight route that is adapted in a manner that avoids obstruction of the at least one predicted LOS.

In addition to the above features, the method according to this aspect of the presently disclosed subject matter can optionally comprise one or more of features (i) to (xvii) below, in any desired combination or permutation: (i) wherein the process further comprises estimating a future progression route of the target object at a future time interval. (ii) wherein environmental elements include any one of: topographical information and/or landcover information. (iii) wherein environmental elements include data on clouds along the future flight route of the aircraft. (iv) wherein the process further comprises repeatedly applying the predicting, comparing, and adapting on the updated flight route. (v) wherein the process further comprises: dividing the time-interval into a plurality of sub-intervals; determining a plurality of predicted lines of sight, each for a respective sub-interval; wherein each predicted LOS of a respective sub-interval, is based on a predicted position of the aircraft along the future flight route of the aircraft and a predicted position of the target object along the future progression route of the target object during the respective sub-interval; and performing the comparing, determining and adapting, for each one of at least some of the predicted lines of sight. (vi) wherein the processing circuitry is configured to repeatedly execute the process during a tracking mission, for maintaining a clear line of sight between the aircraft and the target object. (vii) wherein the aircraft is flying according to a first flight pattern, and is configured for adapting the flight route, to: select a different flight pattern and apply the process on the updated flight route. (viii) wherein the processing circuitry is configured for adapting the flight route, to adapt a specific maneuver along the flight route, to thereby generate an adapted flight route and repeat the process with the updated flight route. (ix) wherein the surveillance system is operatively connected to a flight control unit, the flight control unit being configured to generate instructions for controlling various aerial control devices in order to control the aircraft to fly according to the updated flight route. (x) wherein the processing circuitry is further configured to: for at least one estimated future position of the aircraft: determine a first uncertainty area surrounding the estimated future position of the aircraft; predict a plurality of lines of sight, each line of sight extending between the target object and a different point in the first uncertainty area; and perform the comparing, determining and adapting, for each one of the plurality of lines of sight. (xi) wherein the processing circuitry is further configured to: for at least one estimated future position of the aircraft: determine a second uncertainty area surrounding the estimated future position of the target object; predict a plurality of lines of sight, each line of sight extending between the aircraft and a different point in the second uncertainty area; and perform the comparing, determining and adapting, for each one of the plurality of lines of sight. (xii) wherein the second uncertainty area is limited to a first area located in front of the target object and a second area located behind the target object. (xiii) wherein the target object is a vehicle traveling on a road. (xiv) wherein the aircraft is an unmanned aircraft. (xv) wherein the at least one sensing device is configured to capture images of the sky below the aircraft; the processing circuitry is configured to: process the images captured by the at least one sensing device, detect one or more clouds in the images, and determine the position of the detected clouds; determine whether the at least one predicted LOS is bound to be obstructed by the detected clouds; and if so: generate an updated flight route that is adapted in a manner that avoids obstruction of the predicted LOS. (xvi) wherein the at least one sensing device includes a multispectral or a hyperspectral sensor configured to provide an optical response of the one or more clouds, the processing circuitry is configured to determine data indicative of transparency of the one or more clouds based on a spectral response, and exclude the one or more clouds from being obstructive in case transparency complies with one or more conditions. (xvii) wherein the at least one sensing device includes at least a first sensing device and a second sensing device; wherein the first sensing device is configured to capture images of an object in an observed area, and the second sensing is device is configured to capture images of the sky in the observed area below the aircraft, for detecting clouds.

According to a second aspect of the presently disclosed subject matter, there is provided an aircraft (e.g. an unmanned aircraft) comprising a surveillance systemaccording to the first aspect above; wherein in some examples the aircraft is capable of flying according to a first flight pattern that includes a circular maneuver, the surveillance system being configured for autonomously generating instructions for adapting the flight route that includes instructions to adapt (e.g. decrease) a radius of the circular maneuver; wherein in some examples the aircraft operates in camera driven mode, the aircraft further comprises a navigation and flight control unit, configured, following locking of the sensing device on the target object, to autonomously maneuver the aircraft while striving to continuously track the object and maintain a clear LOS between the at least one sensing device and the object.

According to a third aspect of the presently disclosed subject matter, there is provided a method of tracking a target object by a surveillance system mountable on an aircraft; the method comprising, during tracking of the target object, while the aircraft is operating in autonomous flight mode, operating a processing circuitry for executing a process comprising: estimating future progression route of the target object at a future time-interval; estimating future flight route of the aircraft at the future time-interval; predicting at least one line of sight (LOS) between the surveillance system and the target object during the future time-interval; comparing the at least one predicted LOS relative to data on environmental elements, and determining whether the at least one predicted LOS is obstructed by environmental elements; and in case the at least one predicted LOS is obstructed: adapting the future flight route of the aircraft in a manner that avoids obstruction of the predicted LOS by the environmental elements, thereby generating an updated future flight route.

According to a fourth aspect of the presently disclosed subject matter, there is provided a computer-readable memory device (e.g. non-transitory memory device) tangibly embodying a program of instructions executable by the computer for executing the method of object tracking as disclosed in the third aspect above.

According to a fifth aspect of the presently disclosed subject matter, there is provided a surveillance system mountable on an aircraft, the surveillance system comprising at least one sensing device operatively connected to a tracking module; the surveillance system is configured to track a target object traveling through an area; the tracking module comprises a processing circuitry configured, while the aircraft is operating in autonomous flight mode, during tracking of the target object, to execute a process, comprising: estimating future progression route of the target object at a future time-interval; estimating future flight route of the aircraft at the future time-interval; predicting at least one line of sight (LOS) between the surveillance system and the target object during the future time-interval; comparing the at least one predicted LOS relative to one or more of: topographical information of the area; landcover information of the area; and one or more clouds located between the aircraft and the target object; determining whether the at least one predicted LOS is obstructed by the geography or landcover; and in case the predicted LOS is obstructed: generate an updated flight route that is adapted in a manner that avoids obstruction of the predicted LOS.

According to a sixth aspect of the presently disclosed subject matter, there is provided a surveillance system mountable on an aircraft, the surveillance system comprising at least one sensing device operatively connected to a processing circuitry comprising one or more computer processors; the at least one sensing device is configured to: capture a stream of images of a target object or area in an observed area and capture images of the sky in the observed area below the aircraft; the processing circuitry is configured to: process the images of the target and track the target; process the images of the sky below the aircraft, detect clouds in the images,and determine estimated position of the detected clouds; estimate a future flight route of the aircraft at a future time-interval; and in case it is determined that the future flight route traverses the estimated position of the detected clouds, adapt the future flight route of the aircraft to avoid the estimated position of the detected clouds, thereby generating an updated future flight route.

According to a seventh aspect of the presently disclosed subject matter, there is provided a method of object tracking by a surveillance system mountable on an aircraft, the method comprising: capturing a stream of images of a surveyed area and tracking a target object or target area; capturing images of the sky in the surveyed area below the aircraft; detecting clouds in the images and determining an estimated position of the detected clouds; estimating a future flight route of the aircraft at a future time-interval; in case it is determined that the future flight route traverses the estimated position of the detected clouds, adapting the future flight route of the aircraft to avoid the estimated position of the detected clouds, thereby generating an updated future flight route.

According to an eighth aspect of the presently disclosed subject matter, there is provided an aircraft (e.g. an unmanned aircraft) comprising a surveillance system of the fifth aspect.

According to an ninth aspect of the presently disclosed subject matter, there is provided a computer-readable memory device (e.g. non-transitory memory device) tangibly embodying a program of instructions executable by the computer for executing the method of object tracking as disclosed in the seventh aspect.

The various aspects, including aircrafts, the methods, and the program storage devices disclosed in accordance with the presently disclosed subject matter, can optionally comprise one or more of features (i) to (xvii) listed above with respect to the first aspect, mutatis mutandis, in any desired combination or permutation.

BRIEF DESCRIPTION OF THE DRAWINGS In order to understand the presently disclosed subject matter and to see how it may be carried out in practice, the subject matter will now be described, by way of non-limiting examples only, with reference to the accompanying drawings, in which: Fig. 1 is a schematic block diagram of a UAV communicating with a control unit, according to an example of the presently disclosed subject matter; Fig. 2a is a schematic illustration in top view of a UAV tracking an object of interest while flying in a spiral flight pattern according to an example of the presently disclosed subject matter; Fig. 2b is a schematic illustration in top view of a UAV tracking an object of interest while flying in an offset-spiral flight pattern according to an example of the presently disclosed subject matter; Fig. 2c is a schematic illustration in top view of a UAV tracking an object of interest while flying in a sector-spiral flight pattern according to an example of the presently disclosed subject matter; Fig. 2d is a schematic illustration in top view of a UAV tracking an object of interest while flying in a serpentine flight pattern according to an example of the presently disclosed subject matter; Fig. 3 is a flowchart showing an example of a sequence of operations which are carried out during tracking of an object of interest, in accordance with the presently disclosed subject matter; Fig. 4 is a schematic illustration in top view of a vehicle traveling along a winding road, demonstrating some principles according examples of the presently disclosed subject matter; Fig. 5 is a flowchart showing another example of a sequence of operations which are carried out during tracking of an object of interest, in accordance with the presently disclosed subject matter; and Fig. 6 is flowchart showing yet another example of a sequence of operations which are carried out during tracking of an object of interest, in accordance with the presently disclosed subject matter.

DETAILED DESCRIPTION In the drawings and descriptions set forth, identical reference numerals indicate those components that are common to different embodiments or configurations. Elements in the drawings are not necessarily drawn to scale.

Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as "determining", "generating", "predicting", "estimating", "adapting", "comparing" or the like, include actions and/or processes of a computer that manipulate and/or transform data into other data, said data represented as physical quantities, e.g. such as electronic quantities, and/or said data representing the physical objects.

The terms include any kind of hardware-based electronic device with a data processing circuitry (e.g. digital signal processor (DSP), a GPU, a TPU, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), microcontroller, microprocessor etc.). The processing circuitry can comprise for example, one or more processors operatively connected to a computer memory, loaded with executable instructions for executing operations as further described below. Components of the system disclosed below with reference to Fig. 1, including navigation and flight control unit, tracking module and onboard surveillance system, are a computer, or include a computer, or are operatively connected to a computer.

As used herein, the phrase "for example," "such as", "for instance" and variants thereof, describe non-limiting embodiments of the presently disclosed subject matter. Reference in the specification to "one case", "some cases", "other cases" or variants thereof means that a particular feature, structure or characteristic described in connection with the embodiment(s) is included in at least one embodiment of the presently disclosed subject matter. Thus, the appearance of the phrase "one case", "some cases", "other cases" or variants thereof does not necessarily refer to the same embodiment(s).

It is appreciated that certain features of the presently disclosed subject matter, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of thepresently disclosed subject matter, which are, for brevity, described in the context of a single embodiment, may also be provided separately, or in any suitable sub-combination.

In embodiments of the presently disclosed subject matter, fewer, more and/or different stages than those shown in Figs. 3, 5 and 6 may be executed. In embodiments of the presently disclosed subject matter, one or more stages illustrated Figs. 3, 5 and may be executed in a different order and/or one or more groups of stages may be executed simultaneously. It should be understood that the presently disclosed subject matter contemplates any combination of operations which are described separately with reference to Figs. 3, 5 and 6, into a single process. For example, the operations described with reference to block 305 and block 307, which are described sequentially, can be executed simultaneously. In another example, capturing and processing images for the detection of clouds as described with reference to block 509 and 511 below,can be performed as an ongoing process, before and in parallel to other operations described with reference to blocks 501-507.

Fig. 1 illustrates a general schematic of the system architecture in accordance with an embodiment of the presently disclosed subject matter. Functional elements in Fig. 1 may be centralized in one location or dispersed over more than one location. In other embodiments of the presently disclosed subject matter, the system may comprise fewer, more, and/or different (e.g. distributed differently) functional elements than those shown in Fig. 1. For example, division in UAV 120 and control unit 110 into the specified functional elements is illustrated for the sake of example only and should not be construed as limiting in any way. For instance, functional elements,drawn as nested within other functional elements, may be otherwise designed as independent functional units.

It is noted that reference in the present description to a UAV is made by way of example only, and the same principles and similar functional elements described in relation to a UAV can be likewise applied to a piloted aircraft configured with an auto-pilot flight and object tracking functionality.

According to some examples, UAV system 100 as disclosed with reference to Fig. 1 can be designed to comply with the requirements of STANAG 4586 which is the NATO specification for implementing a core UAV control system (CUCS, comprising both ground and aerial UAV control components). According to STANAG 4586, control unit 110 comprises a client module (operator console) connected in sequence to the application-servers unit, vehicle specific module and primary B/LOS ground data terminal.

The application-servers unit comprises one or more computerized devices (e.g. computer servers) configured to enable the execution of various tasks. Each server is a computerized device with appropriate computer memory and one or more computer processors providing the required data processing capabilities.

The application servers unit can include by way of non-limiting example: flight contrservers operatively connected to a respective data acquisition device (e.g. camera, radar, communication intelligence device, etc.) installed on the UAV.

B/LOS GDT is configured to communicate with the UAV via a respective aerial data terminal (B/LOS ADT) which is part of the UAV onboard control systems. Communication between GDT and ADT can be line of sight communication (LOS) or satellite based, beyond line of sight communication (B-LOS).

Turning to Fig. 1, which schematically illustrates a block diagram of a UAV 120operatively connected to a control unit, according to an example of the presently disclosed subject matter. Fig. 1 shows UAV 120 comprising UAV navigation and flight control unit 26 operatively connected to UAV aerial control devices 28. The navigation and flight control unit comprises, or is otherwise operatively connected to, various navigation aids for enabling to determine flight parameters of the UAV, including its position, orientation, altitude, air speed, etc. Navigation aiding devices include for example: a GPS receiver, INS, an altimeter, pitot tubes, etc.

When operating in autonomous mode, navigation, and flight control unit 26 is configured, in general, to autonomously control the flight of the UAV. More specifically, navigation and flight control unit 26 can determine the position of the UAV (e.g. its geolocation) and a desired destination and generate flight instructions designated for leading the aircraft to the desired destination. The specific flight instructions are also dependent on a specific flight pattern that is executed by the UAV.

Flight instructions are provided to aerial control devices 28, which execute the specific instructions in order to perform a desired aerial maneuver and fly in a certain direction. UAV aerial control devices include for example throttle, flaps, stabilizers, ailerons, and rudders. The UAV may comprise various control units, each dedicated for controlling the operation of a respective aerial control device.

UAV communication unit 30 is configured to provide LOS (line of sight) communication link and possibly also BLOS (beyond line of sight communication), e.g. with communication unit 16 of control unit 110. Communication between UAV 120and control unit 110 can be realized by any suitable communication infrastructure and protocol known in the art. Communication unit 30 can comprise, or be otherwise operatively connected to, an aerial data terminal (B/LOS ADT), as mentioned above. Likewise, communication unit 16 can comprise or be otherwise operatively connected to a ground data terminal (B/LOS GDT), as mentioned above.

UAV 120 further comprises a surveillance system 20, comprising in turn one or more sensing devices. The sensing devices may include by way of non-limiting example, an electro-optic sensor which can provide for example, color optical images, black and white optical images, as well as an infra-red camera, or any other types of sensing device. In some examples the sensing device is fixed to a gimbal, allowing movement of the device in one or more degrees of freedom relative to the UAV body.

Turning to control unit 110 (for example a ground control station (GSC) as is well known in the art) it may comprise (in addition to communication unit 16) display unit 12, input device 10 and command processing unit 14. Display unit 12 comprises one or more display devices (e.g. one or more LED screens for displaying sensing-data received from UAV 120. Input device 10 is configured to enable an operator to interact with the control unit. Input device 10 includes for example, keyboard, joystick, computer mouse, touch pad, touch screen or any other device enabling operator-interaction with the control unit.

Command processing unit 14 is configured to generate control-data responsive to instructions inputted to the control unit. For example, an operator may interact with the control unit for generating locking and tracking instructions directed for tracking an object of interest located in the surveyed scene, e.g. by selecting an objected displayed on the display device. Command processing unit 14 is configured to generate a respective tracking command based on the received instructions. The command is then transmitted to the UAV for execution.

As mentioned above, UAVs are sometimes used for the purpose of observing and tracking objects located in a surveyed scene. In the event a lock and track command is received with respect to an object of interest (target object) located in the surveyed scene, an onboard command processing module (e.g. configured as part of the surveillance system) can be configured to process the command and provide instructions to the surveillance system for locking and tracking the object.

In some examples, when operating in tracking mode, while the aircraft autonomously maneuvers, control instructions are generated for directing the sensing device (e.g. camera) to point in the direction of the object and maintaining the object in the FOV, preferably at its center.

In some examples, instructions for controlling the sensing device are generated by an operator, who can manually track the target using a user interface device such as a joystick, by providing commands directing the sensing device to point in the desired direction.

In other examples (including in case the object is moving) various methods, which are known per se, can be used in order to provide autonomous control to the sensing device for maintaining the moving object within the FOV of the sensing device(e.g. implementing different contour-tracking algorithms by the surveillance system). In further examples, the UAV operates in sensing/imaging device (e.g. camera) driven mode, where, once the sensing device locks onto an object of interest, the navigation and flight control unit 26 autonomously maneuvers the UAV in a manner that strives to continuously track the object. In sensing device driven mode, the UAV is essentially lead by the sensing device for maintaining a clear LOS to the target object. In case the sensing device cannot be maneuvered for maintaining a clear line of sight to the tracked object, the navigation and flight control unit autonomously controls the aircraft so it changes position and maintains a clear LOS to the tracked object.

A UAV, operating in tracking mode or in sensing device driven mode, can fly in various types of flight patterns. Once a certain flight mode is selected, the UAV can fly autonomously according to the selected flight pattern. As explained herein below, the term "flight pattern" refers to specific maneuvers, which may be repetitive, and are performed by an aircraft while flying along a flight route. One example of a type of a flight pattern (referred to herein as "spiral flight pattern") is where the UAV advances in spiraling circles. In this type of flight pattern, an area of interest or target object is maintained below the spiraling flight pattern, e.g. substantially at the central area of the circles. This flight pattern is schematically illustrated in fig. 2a showing, in top view, a UAV tracking a moving vehicle along a road in spiral flight maneuvers, where the UAV is located substantially above the target object (a moving car) and the target object is maintained near the center of the spiraling circles. A spiral flight pattern can be likewise executed in observation mode while flying over an area of interest.

Another example of a type of a flight pattern is referred to herein as "offset-spiral flight pattern". In this flight pattern the navigation and flight control unit directs the UAV to advance in spiraling circles, where the circles are located in an offset relative to the location of the object or area of interest. In this flight pattern the object or area of interest is maintained in a substantially constant offset with respect to the UAV while the UAV advances in spiraling circular maneuvers alongside the object. This flight pattern is schematically illustrated in fig. 2b showing a UAV in top view tracking a moving vehicle along a road in spiral flight maneuvers where the UAV is located in an offset with respect to the moving object. Offset-spiral flight patterns can be likewise executed in observation mode while flying over an area of interest.

In another example of a flight pattern (referred to herein as "sector-spiral flight pattern") navigation and flight control unit directs the UAV to fly along a specific part of the circle. According to this flight pattern, the object or area of interest is maintained substantially at the central area of the circle sector. The advantage of this flight pattern is that the UAV is always in a specific position relative to the LOS, whereas the distance from the LOS, or the lowering angle, remains the same during the majority of time of the flight. This flight pattern is schematically illustrated in fig. 2c showing a UAV in top view, tracking a moving vehicle along a road in a sector-spiral flight pattern. A sector-spiral flight pattern can be likewise executed in observation mode while flying over an area of interest.

As demonstrated in fig. 2a, 2b and 2c, in all three examples of types of flight patterns mentioned above, the UAV advances along with the target object by A fourth example is a serpentine flight pattern, which is a term that refers to a flight pattern where the UAV positions itself at a certain distance behind the object of interest and tracks the object of interest from behind, while making serpentine shaped maneuvers and striving to maintain a substantially constant distance from the object. A serpentine flight pattern is schematically illustrated in fig. 2d.

Flight patterns which can be used while tracking a specific object of interest depend on the velocity of the object of interest and the performance limitation of the UAV. For example, the ability of a UAV to track the object while flying in a spiral flight pattern or serpentine flight pattern can be determined based on the velocity of the target object.

In a serpentine flight pattern, the UAV can fly at a velocity which is closer to the velocity of the target object, and in general reduce the flight distance the UAV is required to travel while tracking. The UAV is characterized by a certain minimal velocity (herein "minimal UAV flight velocity") which is the lowest velocity at which the UAV can fly safely without stalling. Thus, a UAV can track an object of interest while flying in a serpentine flight pattern, if the velocity of the object of interest prescribes a respective UAV velocity which is equal to or greater than the minimal UAV flight velocity.

Notably, in a spiral flight pattern and spiral-offset flight pattern, due to the spiral movement of the UAV, it travels a greater distance than the object of interest. The UAV is therefore required to fly at a speed (ground speed) which is greater than the speed of the object of interest in order to be able to track the object. Thus, the UAV can assume this flight pattern only if the required ground speed is not greater than a maximal UAV ground speed.

As mentioned above, when operating in tracking mode, in an area that is characterized by complex topography and/or complex landcover, LOS to the tracked object may be obstructed by the topography and/or landcover, causing the UAV to lose track of the object.

Accordingly, the presently disclosed subject matter includes an autonomous UAV object tracking method and system that helps to maintain the object of interest within a LOS, and avoids losing track of the object.

To this end, according to some examples, UAV 120 comprises a tracking module 24 configured with new tracking capabilities as further disclosed below. Tracking module 24 can be designed as part of an onboard surveillance system or can be otherwise operatively connected thereto. In some alternative designs, tracking module 24 can operate as part of the control unit 110 being operatively connected to the UAV systems over a communication link.

Fig. 3 is a flowchart illustrating operations carried out in accordance with an example of the presently disclosed subject matter. The operations described with reference to Fig. 3 can be executed, by way of example, by UAV onboard systems (e.g. surveillance system, tracking module, and navigation and flight control unit) disclosed above with reference to Fig. 1, however this should not be construed to limit the scope to a particular system design. The LOS validation process described below can be executed in real-time while the UAV is tracking a target object.

At block 301 surveillance system 20 onboard UAV 120 is used for identifying an object of interest or an area of interest. For simplicity, unless stated otherwise, the terms "object of interest" or "target" are used to include any type of tracked targets including moving objects, static objects, structures, and areas of interest. According to one example, tracking module 24 locks onto the identified object of interest and,once locked, it directs the sensing device for continuously tracking the object of interest. As mentioned above, locking can be executed responsive to a lock and track command received from a control unit. The lock and track command can be generated for example at a control unit, for example, by an operator of a GCS which is viewing images continuously being generated by the surveillance system 20 and transmittedfrom the surveillance system to the control unit. In other examples, locking onto an object can be executed autonomously by the surveillance system 20. For instance a surveillance system can include a video motion detection (VMD) module configured to apply a VMD algorithm on images captured by the sensing device (e.g. camera) and autonomously lock and track an object that complies with certain characteristics (e.g. size, color, speed, etc.).

After the surveillance system has locked onto the object of interest, motion parameters of the target object, including for example direction, speed, acceleration, are estimated (block 303). The velocity of a moving object can be determined using any one of various known methods, including, for example, by calculating the inertial LOS ground positions at any calculations cycle, and then integrating and filtering these positions into the estimated LOS ground speed. Alternatively, this can be accomplished using Video Motion Detection (VMD) algorithms.

According to other examples, an object of interest in a surveyed scene is identified without locking on to it (e.g. also by tracking module 24). For example, during manual tracking, where movement is applied on a control device (e.g. joystick or mouse) by an operator in order to direct the sensing device in a certain direction and manually track an object (e.g. a vehicle advancing along a road) system 20 can be configured to identify a tracked object and determine motion parameters in case it is moving. Autonomous identification of an object of interest can be carried out for example by a dedicated algorithm that can be configured to determine an object on which a joystick indicator (e.g. cross or arrow) is placed for a certain period of time and/or an object that is located nearest to the center of FOV of the sensing device, and/or an object that is maintained within the FOV for a certain period, and/or the direction of force applied on a joystick, etc. The above mentioned, as well as other parameters (some mentioned above with respect to VMD algorithms), can also be used for autonomously selecting an object of interest in case more than one object is identified within the FOV of the sensing device. For example, the object of interest can be selected based on its speed and/or shape, and/or size, and/or direction. In some examples, the surveillance system 20 can prompt the user, asking the user to identify the object of interest, e.g. by pointing to the object with a mouse or joystick pointer.

LOS obstruction is not limited to a moving object of interest and can also occur when observing a static target such as a specific area, structure, or static object. For example, a fixed wing aircraft that is observing a static target may assume a circular flight pattern surrounding the target. While the UAV is circling the target, the LOS between the sensing device and the static target may be obstructed by the topography or land cover near the target. Therefore, methods of avoiding LOS obstruction, as disclosed herein, can also be applied in these cases. Notably, the term "tracking" isused herein to refer to both tracking of a mobile object, as well as the observation ofa static target.

At block 305, it is determined whether the object is moving or not, and in case the target object is moving, the near future progression route of the target object is estimated. In case of a static target, there is no need to determine a future progression route. According to some examples, the term "near future" refers to a certain time interval of a few seconds. According to one example, near future refers to a time interval ranging between 3 seconds to one minute. Estimation of a near future route of the target object can be accomplished for example based on the speed (and/or acceleration) and direction of the target object, together with road maps of the area. Assuming for example, a vehicle is traveling on a road, the speed and direction of the vehicle together with the direction and shape of the road provide sufficient information for predicting the near future route of the vehicle. As demonstrated schematically in Fig. 4, based on the speed and direction of a vehicle traveling on the road, currently at position A, and the shape of the road, it can be predicted with a good level of certainty, that the vehicle will be at position B a few seconds later. In some examples, images captured by the surveillance system are registered to a map of the corresponding area (e.g. by tracking module 24), and the road shape and direction is analyzed. To this end, in some examples, tracking module 24 is operatively connected to a data storage comprising a map of the area, and may implement an image registration and processing algorithm to determine the shape of the road and the future position of the object along the road, according to the shape of the road and the speed and direction of the vehicle.

At block 307 near future flight route of the aircraft (including for example degree of freedom (DOF) positioning data) is estimated. The near future flight parameters can be estimated based on the future flight route of the aircraft (prescribed for example by a specific flight route and/or the flight pattern assumed by the aircraft). The aircraft may operate in camera driven mode, where, once the sensing device locks onto an object of interest, the UAV autonomously maneuvers (e.g. with the help of navigation and flight control unit), where the aircraft is essentially led by the tracked object while striving to continuously track the object. Thus, the near future flight parameters can be estimated also based on the position of the target object relative to the aircraft. Given the current position of the aircraft, the assumed flight pattern, and the current and estimated future position of the target object, corresponding future flight control commands (e.g. for controlling roll, speed, altitude, etc.) dedicated for maintaining the flight pattern while keeping track of the target object, are estimated, to thereby provide a simulation of the aircraft's maneuvers and corresponding position, and orientation in the near future.

In case of a static target, where the aircraft assumes a flight pattern selected for enabling the aircraft to continuously observe the object (e.g. a fight pattern that circles around the static target), a near future flight route can be likewise determined based on the near future maneuvers of the aircraft relative to the target, as prescribed by the flight pattern.

At block 309 it is determined whether a predicted line of sight between an estimated future position of the aircraft (e.g. extending from the sensing device), along the estimated flight route, and estimated future position of the target object, along the estimated progression route of the target object (e.g. vehicle), both corresponding to the same instance in the future, is clear, or obstructed. A future LOS extending between the target object and the surveillance system can be predicted(predicted LOS), based on the estimated future position of the aircraft, and estimated future position of the target.

This also depends on objective environmental elements and their location relative to the position of the aircraft and surveillance system (e.g. the sensing device onboard the aircraft) and the position of the target at a certain moment in the future, which prescribe a respective LOS between the aircraft and target. As mentioned above, environmental elements that have the potential to obstruct the LOS, include,for example, topography and landcover.

In some examples, tracking module 24 can be operatively connected to one or more data sources (e.g. data storage devices) comprising topographic and landcover data (including geographic information system (GIS) data). In some examples, the estimated future position of the aircraft, the estimated future position of the target object, and the topography and/or landcover information, are all transformed to a common coordinate system. 3D topography and/or landcover data can be stored in a database made accessible to system 20. In one example the database is implemented on a data storage device onboard the aircraft, e.g. as part of system 20, where, in another example, the database can be implemented on a data storage device located remotely from the aircraft, e.g. at the control unit 110. The 3D topography and/or landcover data can be retrieved from the database and compared with a predicted LOS to determine whether the LOS is obstructed or not.

In some examples, in addition to or instead of topography and landcover information, environmental elements include cloud data pertaining to the clouds condition in the sky between the surveillance system and the target. Thus, according to some examples, in addition to, or instead of topography and landcover information, cloud data is obtained and used for determining whether a future line of sight is bound to be obstructed by clouds. A more detailed description of the detection and analysis of clouds as LOS obstructing elements is described below with reference to Fig. 5.

The exact position and orientation of the sensing device (whether it is fixedly attached or gimbaled) relative to the aircraft, can be determined by methods which are well known in the art, allowing to calculate a more accurate LOS extending directly from the target object to the sensing device.

In some examples, the near future time interval is divided into sub-intervals. For each sub-interval, the predicted LOS extending between the predicted position of the aircraft and the predicted position of the target object during that sub-interval, is analyzed together with topographic data and landcover data, to determine whether the predicted LOS is obstructed. In one example, each sub-interval is 1-2 seconds long, thus LOS obstruction is estimated for about each second along the tracking mission.

Notably, due to possible inaccuracies and errors in the prediction process, around each point of an estimated position of the aircraft there is an area (e.g. a rectangle) of uncertainty, where the actual future position of the aircraft can be somewhere within the uncertainty area, rather than at the specific estimated position. Accordingly, in some examples, in order to improve the accuracy of prediction, rather than analyzing one LOS extending from one given predicted future position of the aircraft, a plurality of candidate lines of sight are analyzed, each one extending from a different point within the uncertainty area. For example, assuming the uncertainty area has a rectangular shape, four additional points can be added to the estimated future position of the aircraft, each of the four points located at a vertex of the rectangle. Five candidate lines of sight can be analyzed, four lines of sight extending each from a respective vertex to the target object, and a fifth line of sight extending from the estimated future position. In some examples, in case one of the predicted lines of sight is determined as being obstructed, the future flight route of the aircraft is updated, as explained above.

Likewise, an uncertainty area can be defined around each estimated future position of the target object. A plurality of points can be defined with the uncertainty area and a plurality of respective lines of sight can be analyzed, each line extending between an estimated future position of the aircraft (e.g. sensing device) and a respective point. For example, four lines of sight may be analyzed, each extending to a respective vertex of an uncertainty rectangle surrounding the estimated future position of the target object. Thus, in some examples, assuming there are five points, representing five possible future positions of the aircraft, and four points, representing four possible future points positions of the object, a total of twenty candidate lines of sight are analyzed. In some examples, this is done for each sub-interval.

In some examples, to reduce computational load, the area of uncertainty is restricted according to the specific environmental conditions. For example, in case the target object is advancing along a distinguishable pathway (e.g. a vehicle advancing on a road), the area of uncertainty can be restricted only to the parts on the road ahead and behind the object, thus reducing the number of uncertainty points and respective candidate lines of sight. To this end, for surveillance, in some examples, system 20 is configured (e.g. by tracking module 24) to process images captured by the sensing device to identify the environment surrounding the target and restrict the uncertainty area accordingly. For example, in case the processing output identifies the road on which a vehicle is traveling, the uncertainty area can be restricted according to the boundaries of the road, as the vehicle is expected to be located within these boundaries.

At block 311 in case LOS obstruction is predicted, the aircraft's future flight route is adapted in order to avoid the obstruction. In some examples, the process according to blocks 305-307 is repeated and applied on the adapted flight route todetermine whether the changed route overcomes the problem, i.e. provides a continuous clear LOS between the aircraft and the target object, and if it does not, the flight route may be further adapted. This cycle may be repeated until a flight route that avoids the LOS obstruction is obtained.

In some examples, when an LOS obstruction is predicted, a specific part of the aircraft maneuver is adapted in order to avoid the LOS obstruction. For example, a radius of a maneuver can be decreased or increased. In other examples, the UAV flight pattern is changed to another suitable flight pattern, e.g. from a serpentine flight pattern to a spiral flight pattern.

The process of updating the flight route can be completely autonomous, or may, in some cases, involve some human input. Assuming for example, during a tracking mission, the aircraft is autonomously maneuvering according to some predesignated or selected flight pattern, while the operator is manually directing a camera so it continuously points to a moving target object. In such a scenario, responsive to determination of a predicted obstruction of the LOS, tracking module may issue a warning to the operator (e.g. send a warning signal to the control unit, where a visible and/or audible warning is activated). The operator can actively change the flight pattern of the aircraft responsive to the warning. The surveillance system is ready to receive instructions from the operator and to change the flight route of the aircraft according to the received instructions. In other examples, for instance when the aircraft is operating in camera driven flight mode, the flight pattern can be changed autonomously, e.g. by tracking module 24.

If sub-intervals are applied, process 310 of LOS validation can be repeated for each given sub-interval to determine a clear LOS between the target object and UAV.

Process 310 of LOS validation, as described above with reference to Fig. 3, is repeated during UAV flight in real-time, in order to continuously monitor the future flight route of the aircraft and progression route of the target object, if moving, and enable to make changes to the flight route in case possible obstruction of the LOS is detected, thereby maintaining a clear LOS between the surveillance system and the tracked object.

As mentioned above, the presently disclosed subject matter includes a system and method that provides autonomous flight monitoring and control over an aircraft that helps to maintain continuous object tracking by a sensing device (e.g. imaging payload such as a camera) mounted on the aircraft (e.g. UAV). In some examples, the disclosed system and method further provide real-time continuous LOS validation that helps to reduce the likelihood of line of sight obstruction or interception caused by clouds while tracking an object.

As described above, system According to some examples, where the aircraft comprises a plurality of sensors, at least one sensor can be designated for observing the area and for tracking detected objects (hereinafter "observation and tracking sensor") and at least one other sensor is designated for observing the sky and detecting clouds (hereinafter "cloud detection sensor"). cloud detection sensor Fig. 5 is a flowchart illustrating operations carried out in accordance with an example of the presently disclosed subject matter. The operations described with reference to Fig. 5 can be executed, by way of example, by UAV onboard systems (e.g. tracking module, surveillance system and navigation and flight control unit) disclosed above with reference to Fig. 1 , however this should not be construed to limit the scope to a particular system design. The LOS validation process for avoiding LOS obstruction by clouds described below, is executed in real-time while the UAV is tracking a target object. While the process is described below using two different sensing devices, the same principles apply to the case where a single sensing device is used.

At block 501 a surveillance system onboard UAV 120 is operated for identifying an object of interest. Methods of identifying an object of interest are described above with reference to block 301.

After the surveillance system has identified the object of interest (and possibly also locked onto the object of interest), motion parameters of the target object, including its direction, speed and/or acceleration are estimated (block 503). The velocity of a moving object can be determined using any one of various known methods, including, for example, by calculating the inertial LOS ground positions at any calculations cycle, and then integrating and filtering these positions into the estimated LOS ground speed. In other examples, this can be accomplished using a Video Motion Detection algorithm.

At block 505, in case of a moving target object, the near future progression route of the target object is estimated, as explained above with respect to block 305in Fig. 3.

At block 507 near future flight route of the aircraft is estimated, as explained above with respect to block 305 in Fig. 3.

At block 509 a cloud detection sensor onboard UAV 120 is operated for capturing images of the sky below the aircraft between the tracked object and the UAV. The cloud detection sensor is used for capturing images of areas that include the future position of a tracked object. Therefore, as mentioned above, it is advantageous to use a sensor that is characterized by a wide angle (having a large FOV) in order to enable detection of LOS obstruction by clouds over greater areas, and thereby increase efficiency and effectiveness of the detection.

At block 511, the captured images are processed for the purpose of detecting clouds (also referred to herein as "clouds data"). Cloud detection in captured images can be carried out by various methods of image processing. For example, image processing algorithms (e.g. machine learning algorithms) dedicated to detecting cloud features and/or spectral signatures in images obtained by a multi-spectral or a hyper spectral sensor onboard the aircraft, can be applied for this purpose. Tracking module can comprise a processing circuitry configured for this purpose. In another example, the captured images are transmitted to control unit 110 or some other remote computer, and the processing of the images is carried out there. In the event clouds are identified, the cloud's estimated position is determined.

The presently disclosed subject matter further contemplates using a multispectral or a hyperspectral sensor onboard the UAV for calculating an estimated optical thickness of the clouds (clouds' optical thickness; COT) at the spectral-band of the observation and tracking sensor. Clouds may have various degrees of transparency for the spectrum detected by the observation and tracking sensor, such that in some cases the observation and tracking sensor may be able to detect targets covered by semi-transparent clouds. According to one example, cloud imaging, performed by the cloud detection sensor, is carried out using a multispectral or hyperspectral sensor. During the processing of the images captured by the cloud detection sensor, the output of the multispectral or hyperspectral image sensor output is processed in order to determine a spectral-response of clouds detected in the images. Then a COT threshold is applied on the detected spectral response, to determine whether the cloud's opacity would obstruct the target from being viewed in images generated by the observation and tracking sensor. This also depends on the specific features of the observation and tracking sensor. In case it is determined that the clouds are sufficiently transparent (e.g. if the values obtained from the multispectral or hyperspectral sensor are within a certain predefined range), they are not considered as obstructive, and can be excluded. Thus, it is suggested to use multispectral or hyperspectral output and a respective processing circuitry as a screening tool in order to identify those clouds which actually obstruct the targets from being captured by the observation and tracking sensor.

Notably, capturing images of the sky by a cloud detection sensor and processing the images for detecting clouds can be an ongoing process executed independently and in parallel to the other operations mentioned above, to thereby provide continuous output of the cloud situation.

In case of a positive identification of clouds, at block 513 it is determined whether a predicted LOS, extending between an estimated future position of the aircraft along the estimated flight route and estimated future position of the target object along the estimated progression route of the target object (e.g. vehicle), both corresponding to the same instance at a future time, is clear, or obstructed by clouds. A future LOS extending between the target object and the surveillance system can be predicted, based on the estimated future position of the aircraft, and estimated future position of the target vehicle. As mentioned above, the exact position and orientation of the sensing device (whether it is fixedly attached or gimbaled) relative to the aircraft, can be determined by methods which are well known in the art, allowing to calculate a more accurate LOS, extending directly from the target object to the sensing device. The position of the identified clouds is compared to the future LOS, and it is determined whether the clouds obstruct the future LOS.

As explained above with reference to Fig. 3, in some examples, the near future time interval is divided into sub-intervals, and a respective predicted LOS extending between the predicted position of the aircraft and the predicted position of the target object during that sub-interval, is analyzed together with detected clouds, to determine whether the predicted LOS is obstructed. In one example, each sub-interval is 1-2 seconds long, thus LOS obstruction is estimated for about each second along the tracking mission.

As further explained above, in some examples, in order to improve the accuracy of prediction, rather than analyzing one LOS extending from one given predicted future position of the aircraft, a plurality of candidate lines of sight are analyzed, each one extending from a different point within the uncertainty area. According to one non-limiting example, assuming the uncertainty area has a rectangular shape, four additional points can be added to the estimated future position of the aircraft, each of the four points located at a vertex of the rectangle. Five candidate lines of sight can be analyzed, four lines of sight extending each from a respective vertex to the target object, and a fifth line of sight extending from the estimated future position.

Likewise, an uncertainty area can be defined around each estimated future position of the target object. A plurality of points can be defined within the uncertainty area and a plurality of respective lines of sight can be analyzed, each line extending between an estimated future position of the aircraft (e.g. future position of aperture of the observation and tracking sensor) and a respective point. For example, four lines of sight may be analyzed, each extending to a respective vertex of an uncertainty rectangle surrounding the estimated future position of the target object. Thus, in some examples, assuming there are five points, representing five possible future positions of the aircraft, and four points, representing four possible future points positions of the object, a total of twenty candidate lines of sight are analyzed. In some examples, in case one of the predicted lines of sight is determined as being obstructed by clouds, the future flight route of the aircraft is updated, as explained above.

Notably, as the position of the identified clouds may be an estimated position rather than an accurate one (inter alia for lack of clouds' altitude data), in some examples, the future LOS between aircraft and target, as described above, may not be predicted as described with reference to block 513 above. As shown in Fig. 6, instead,after estimating the position of the identified clouds and the future position of the target, in case it is moving, the future flight route of the aircraft is adapted so it avoids clouded areas in the sky while directed to continuously track the target. In some examples, the cloudiness in different areas along the flight route is determined, and the flight route is adapted so it passes through an area with the least cloudiness is taking into consideration when determining the future flight route of the aircraft.

It is to be understood that the system according to the presently disclosed subject matter may be a suitably programmed computer. Likewise, the presently disclosed subject matter contemplates a non-transitory computer program being readable by a computer for executing the method of the presently disclosed subject matter. The presently disclosed subject matter further contemplates a machine-readable memory (transitory and non-transitory) tangibly embodying a program of instructions executable by the machine for executing the method of the presently disclosed subject matter.

It is also to be understood that the presently disclosed subject matter is not limited in its application to the details set forth in the description contained herein or illustrated in the drawings. The presently disclosed subject matter is capable of other embodiments and of being practiced and carried out in various ways. Hence, it is to be understood that the phraseology and terminology employed herein are for the purpose of description and should not be regarded as limiting. As such, those skilled in the art will appreciate that the conception upon which this disclosure is based may readily be utilized as a basis for designing other structures, methods, and systems for carrying out the several purposes of the present presently disclosed subject matter.

Claims (35)

1. 292732/9/10/20 -32- Claims:1. A surveillance system mountable on an aircraft, the surveillance system comprising at least one sensing device; the surveillance system being configured to observe a target object; the surveillance system comprises a processing circuitry configured, while flying autonomously and observing the target object, to execute a process, comprising: estimating future flight route of the aircraft at a future time-interval; estimating a future progression route of the target object at the future time interval; predicting at least one predicted line of sight (LOS) between the surveillance system and the target object during the future time-interval, wherein the at least one predicted LOS connects a future position of the aircraft along the future flight route and a future position of the target object along the future progression route; comparing the at least one predicted LOS relative to the environmental elements; determining whether the at least one predicted LOS is obstructed by the environmental elements; and in case the at least one predicted LOS is obstructed: generate an updated flight route that is adapted in a manner that avoids obstruction of the at least one predicted LOS; and repeating the process during aircraft flight to continuously maintain a clear LOS between the aircraft and the target. 292732/9/10/20 -33-

2. The surveillance system of any one of the preceding claims, wherein environmental elements include any one of: topographical information and/or landcover information.

3. The surveillance system of any one of the preceding claims, wherein environmental elements include data on clouds along the future flight route of the aircraft.

4. The surveillance system of any one of the preceding claims, wherein the process further comprises: repeatedly applying the estimating, predicting, comparing, and adapting on the updated flight route.

5. The surveillance system of any one of the preceding claims, wherein the process further comprises: dividing the time-interval into a plurality of sub-intervals; determining a plurality of predicted lines of sight, each for a respective sub-interval; wherein each predicted LOS of a respective sub-interval, is based on a predicted position of the aircraft along the future flight route of the aircraft and a predicted position of the target object along the future progression route of the target object during the respective sub-interval; and performing the comparing, determining and adapting, for each one of at least some of the predicted lines of sight.

6. The surveillance system of any one of the preceding claims, wherein the processing circuitry is configured to repeatedly execute the process during a tracking mission, for maintaining a clear line of sight between the aircraft and the target object.

7. The surveillance system of any one of the preceding claims, wherein the aircraft is flying according to a first flight pattern, and the processing circuitry is configured for adapting the flight route, to: 292732/9/10/20 -34- select a different flight pattern and apply the process on the updated flight route.

8. The surveillance system of any one of claims 1 to 7, wherein the processing circuitry is configured for adapting the flight route, to adapt a specific maneuver along the flight route, to thereby generate an adapted flight route and repeat the process with the updated flight route.

9. The surveillance system of any one of the preceding claims is operatively connected to a flight control unit, the flight control unit being configured to generate instructions for controlling various aerial control devices in order to control the aircraft to fly according to the updated flight route.

10. The surveillance system of any one of the preceding claims, wherein the processing circuitry is further configured to: for at least one estimated future position of the aircraft: determine a first uncertainty area surrounding the estimated future position of the aircraft; predict a plurality of lines of sight, each line of sight extending between the target object and a different point in the first uncertainty area; and perform the comparing, determining and adapting, for each one of the plurality of lines of sight.

11. The surveillance system of any one of the preceding claims, wherein the processing circuitry is further configured to: for at least one estimated future position of the aircraft: determine a second uncertainty area surrounding the estimated future position of the target object; predict a plurality of lines of sight, each line of sight extending between the aircraft and a different point in the second uncertainty area; and 292732/9/10/20 -35- perform the comparing, determining and adapting, for each one of the plurality of lines of sight.

12. The surveillance system of claim 11, wherein the second uncertainty area is limited to a first area located in front of the target object and a second area located behind the target object.

13. The surveillance system of any one of the preceding claims, wherein the target object is a vehicle traveling on a road.

14. The surveillance system of any one of the preceding claims, wherein the aircraft is an unmanned aircraft.

15. The surveillance system of any one of the preceding claims, wherein the at least one sensing device is configured to capture images of the sky below the aircraft; the processing circuitry is configured to: process the images captured by the at least one sensing device, detect one or more clouds in the images, and determine the position of the detected clouds; determine whether the at least one predicted LOS is bound to be obstructed by the detected clouds; and if so: generate an updated flight route that is adapted in a manner that avoids obstruction of the predicted LOS.

16. The surveillance system of any one of the preceding claims, wherein the at least one sensing device includes a multispectral or a hyperspectral sensor configured to provide an optical response of the one or more clouds, the processing circuitry is configured to determine data indicative of transparency of the one or more clouds based on a spectral response, and exclude the one or more clouds from being obstructive in case transparency complies with one or more conditions.

17. The surveillance system of any one of claims 15 to 16, wherein the at least one sensing device includes at least a first sensing device and a second sensing 292732/9/10/20 -36- device; wherein the first sensing device is configured to capture images of an object in an observed area, and the second sensing is device is configured to capture images of the sky in the observed area below the aircraft for detecting clouds.

18. An aircraft comprising a surveillance system according to any one of claims 1 to 17.

19. The aircraft of claim 18 is a UAV.

20. The aircraft of claim 18 is configured to operate in camera driven mode, where, following lock of the sensing device onto the target object, the aircraft autonomously maneuvers, while striving to continuously track the object.

21. The aircraft of any one of claims 18 to 20 operating in camera driven mode, the aircraft further comprising a navigation and flight control unit configured, following locking of the sensing device onto the target object, to autonomously maneuver the aircraft while striving to continuously track the object and maintain a clear LOS between the at least one sensing device and the object.

22. A method of tracking a target object by a surveillance system mountable on an aircraft; the method comprising, during tracking of the target object, while the aircraft is operating in autonomous flight mode, operating a processing circuitry for executing a process comprising: estimating future progression route of the target object at a future time-interval; estimating future flight route of the aircraft at the future time-interval; predicting at least one line of sight (LOS) between the surveillance system and the target object during the future time-interval, wherein the at least one predicted LOS connects a future position of the aircraft along the future flight route and a future position of the target object along the future progression route; 292732/9/10/20 -37- comparing the at least one predicted LOS relative to data on environmental elements and determining whether the at least one predicted LOS is obstructed by environmental elements; and in case the at least one predicted LOS is obstructed: generating an updated flight route that is adapted in a manner that avoids obstruction of the predicted LOS by the environmental elements; controlling the aircraft according to the updated flight route; and repeating the process during aircraft flight to continuously maintain a clear LOS between the aircraft and the target.

23. The method of claim 22, wherein the environmental elements include any one of: topographical information and landcover information.

24. The method of any one of claims 22 to 23, wherein environmental elements include data on clouds.

25. The method of any one of claims 22 to 24 further comprising: applying the predicting, comparing and adapting on the updated future flight route.

26. The method of any one of claims 22 to 25 further comprising: dividing the time-interval into a plurality of sub-intervals; determining a plurality of predicted lines of sight, each for a respective sub-interval; wherein each predicted LOS of a respective sub-interval is based on a predicted position of the aircraft along the future flight route of the aircraft and a predicted position of the target object along the future progression route of the target object during the respective sub-interval; and performing the comparing, determining and adapting, for each one of at least some of the predicted lines of sight. 292732/9/10/20 -38-

27. The method of any one of claims 22 to 26, wherein the aircraft is flying according to a first flight pattern, the adapting the future flight route comprising: selecting a different flight pattern and repeating the process with the different flight pattern.

28. The method of any one of claims 22 to 27, wherein adapting the future flight route comprises: adapting a specific maneuver along the flight route; and repeating the process with the updated future flight route.

29. The method of any one of claims 22 to 28, further comprising: operating the aircraft in camera driven mode, where following lock of the sensing device onto the target object, the aircraft autonomously maneuvers, while striving to continuously monitor and track the object.

30. The method of any one of claims 22 to 29, further comprising: for at least one estimated future position of the aircraft: determining a first uncertainty area surrounding the estimated future position of the aircraft; predicting a plurality of lines of sight, each line of sight extending between the target object and a different point in the first uncertainty area; and performing the comparing, determining and adapting, for each one of the plurality of lines of sight.

31. The method of any one of claims 22 to 30, further comprising: for at least one estimated future position of the aircraft: determining a second uncertainty area surrounding the estimated future position of the target object; predicting a plurality of lines of sight, each line of sight extending between the aircraft and a different point in the second uncertainty area; 292732/9/10/20 -39- and performing the comparing, determining and adapting, for each one of the plurality of lines of sight.

32. The method of claim 31, wherein the second uncertainty area is limited to a first area located in front of the target object and a second area located behind the target object.

33. The method of any one of claims 22 to 32, wherein in case it is determined that the predicted LOS is obstructed, generating a warning indicating to an operator of a control unit operatively connected to the surveillance system over a communication link, that the predicted LOS is obstructed, and enabling the operator to generate instructions for adapting the flight route by selecting a different flight pattern.

34. The method of any one of claims 22 to 33, further comprising: operating at least one second sensing device for capturing images of the sky below the aircraft; processing the images captured, detecting one or more clouds in the images, and determining the position of the detected clouds; determining whether the at least one LOS is bound to be obstructed by the detected clouds; and if so: generating an updated flight route that is adapted in a manner that avoids obstruction of the predicted LOS. 35. The method of any one of claims 22 to 34, further comprising: operating a multispectral or a hyperspectral sensor configured to provide an optical response of the one or more clouds; processing the multispectral or a hyperspectral sensor output, and determining data indicative of transparency of the one or more clouds based on a spectral response; and 292732/9/10/20 -40- excluding the one or more clouds from obstructing targets in case transparency complies with one or more conditions. 36. A computer-readable memory device tangibly embodying a program of instructions executable by the computer for executing the method of claims 22 to

35.