JP7126434B2 - Rain attenuation prediction device and program - Google Patents

Description

Article 30, Paragraph 2 of the Patent Law applies [Meeting name] Kansai Broadcasting and Technology Forum 2018 [Date] May 17, 2018 [Venue] NHK Osaka Broadcasting Station 17th floor conference room

The present invention relates to a technique for measuring attenuation of radio waves due to rainfall, and more particularly to a rain attenuation prediction device and program for predicting attenuation of radio waves due to rainfall (hereinafter referred to as "rainfall attenuation").

FIG. 13 is a schematic diagram illustrating a broadcast network. This broadcasting network 100 is composed of a broadcasting station (performance hall) 101, a broadcasting station (master station) 102, relay stations 103-1 and 103-2, and the like. The broadcasting network 100 uses STL (Studio to Transmitter Link) lines and TTL (Transmitter to Transmitter Link) lines, and is installed in each home from a broadcasting station (master station) 102 or relay stations 103-1, 103-2, etc. broadcast wave to the specified receiver. This allows viewers at home to view the video.

The STL line is a radio line using microwaves for transmitting broadcast contents from the broadcasting station (musical hall) 101 to the broadcasting station (master station) 102, and the TTL line relays from the broadcasting station (master station) 102. It is a radio link using microwaves for transmitting broadcast contents to stations 103-1, 103-2, and the like.

By the way, in recent years, the frequency of occurrence of heavy rains has increased, and there is an increasing tendency for the reception level of radio waves to decrease due to heavy rains in the STL line, TTL line, or the like shown in FIG.

As a technique for measuring the reception level of such radio waves, a technique for calculating attenuation of radio waves has been disclosed (see Patent Document 1, for example).

This method approximates the probability distribution of the rainfall intensity every 10 minutes with a logarithmic normal distribution based on the rainfall intensity of the point actually observed every 10 minutes, generates the rainfall intensity distribution data, and generates the rainfall intensity distribution data and generates attenuation distribution data representing this probability distribution. Then, the rainfall margin is calculated based on the generated attenuation distribution data, the predicted hourly rainfall input from the outside, and the requested broadcast time data indicating the time during which the broadcast is not interrupted per hour.

JP 2006-246375 A

In the broadcasting network 100 shown in FIG. 13, when rain attenuation occurs in the STL line or the TTL line, the broadcasting station (playground) 101, the broadcasting station (master station) 102, or relay stations 103-1, 103-2, etc. The reception level of the transmitted radio waves may drop and the broadcast may be interrupted. In other words, when rain attenuation occurs in the STL line or TTL line, images such as programs produced by the broadcasting station (musical hall) 101 may not reach viewers.

Therefore, it has been desired to predict the rain attenuation in the STL or TTL line in advance. By predicting rainfall attenuation, the line in use can be switched from a normal STL line or TTL line to a separate spare line if one is available, thereby avoiding interruptions in broadcasting. is.

In order to predict such rainfall attenuation, it is assumed that the technique of Patent Document 1 is used. However, with this method, when generating attenuation distribution data, it is necessary to approximate the probability distribution of rainfall intensity at predetermined time intervals with a logarithmic normal distribution. is high.

SUMMARY OF THE INVENTION Accordingly, the present invention has been made to solve the above problems, and an object of the present invention is to provide a rainfall attenuation prediction device and a program that can easily and reliably predict rainfall attenuation.

In order to solve the above-mentioned problems, the rain attenuation prediction device of claim 1 is a rain attenuation prediction device that predicts the attenuation of radio waves due to rainfall at a predetermined location. and a receiving unit that stores the rainfall intensity in a memory, and based on the latest rainfall intensity and the predetermined moving speed and moving direction of rain clouds stored in the memory, from the current time to a predetermined predicted time and a prediction unit that predicts the attenuation of radio waves at the predetermined location as a rainfall attenuation amount, and the prediction unit predicts the predetermined location from the current time to the prediction time based on the moving speed and the moving direction a sorting range setting unit for setting, as a sorting range, an area for sorting the rainfall intensities caused by the rain clouds predicted to pass through; a precipitation intensity sorting unit for sorting the precipitation intensities within the sorted range and specifying the maximum precipitation intensity for the predetermined location; and a rain attenuation amount prediction unit for predicting the rain attenuation amount.

Moreover, the rain attenuation prediction apparatus of claim 2 is characterized in that, in the rain attenuation prediction apparatus of claim 1, the moving speed and the moving direction are set in advance by the user.

Further, the rain attenuation prediction device according to claim 3 is the rain attenuation prediction device according to claim 2, wherein the moving speed preset by the user is the maximum moving speed observed in the past at the predetermined location, The movement direction preset by the user is a plurality of directions observed in the past at the predetermined location.

Further, the rain attenuation prediction device according to claim 4 is the rain attenuation prediction device according to claim 1, further reading the latest rain intensity and the past rain intensity from the memory, Matching is performed between the distribution of a first region including a predetermined location and the distribution of a second region having the same size as the first region in the past rainfall intensity, and the second region is sequentially shifted by a predetermined distance. By specifying the second region where the difference between the distribution of the first region and the distribution of the second region is the smallest, and based on the first region and the second region where the difference is the smallest and a movement pattern setting unit for setting the movement speed and the movement direction.

In addition, the rain attenuation prediction device of claim 5 is the rain attenuation prediction device of any one of claims 1 to 4, further comprising a determination unit, and the prediction unit further includes a reception level prediction unit. , the reception level prediction unit uses the reception level of the radio wave when there is no rainfall at the predetermined location as a reference reception level, and based on the reference reception level and the rain attenuation predicted by the rain attenuation prediction unit , predicting the reception level at the predetermined location, and determining the possibility that the broadcast at the predetermined location will be interrupted based on the reception level predicted by the reception level prediction unit and a predetermined threshold, It is characterized by

Furthermore, a program according to claim 6 causes a computer to function as the rain attenuation prediction device according to any one of claims 1 to 5.

As described above, according to the present invention, it is possible to easily and reliably predict rainfall attenuation. By predicting the occurrence of rainfall attenuation, for example, the line in use can be switched from a normal STL line or TTL line to a separately prepared backup line, if any, to avoid interruptions in broadcasting. It becomes possible to

1 is a schematic diagram of an entire system including rain attenuation prediction devices of Examples 1 and 2; FIG. 1 is a block diagram showing a configuration example of a rain attenuation prediction device of Example 1. FIG. 5 is a flow chart showing a processing example of the rain attenuation prediction device of the embodiment 1; It is a block diagram which shows the structural example of a prediction part. (1) is a diagram for explaining a sorting range C. FIG. (2) is a diagram for explaining the maximum rainfall intensity obtained by sorting. It is a figure explaining an example when nine kinds of movement directions A are set. FIG. 10 is a diagram for explaining the possibility of overlooking the occurrence of rain attenuation when using only weather data every 5 minutes; FIG. 4 is a diagram showing an example of a display screen; FIG. 11 is a block diagram showing a configuration example of a rain attenuation prediction device of Example 2; 10 is a flow chart showing a processing example of the rain attenuation prediction device of Example 2. FIG. It is a figure explaining an example of movement pattern setting processing. FIG. 2 is a diagram showing experimental results of Example 1; 1 is a schematic diagram illustrating a broadcast network; FIG.

EMBODIMENT OF THE INVENTION Hereinafter, the form for implementing this invention is demonstrated in detail using drawing. FIG. 1 is a schematic diagram of the entire system including rain attenuation prediction devices of Examples 1 and 2. FIG. This rain attenuation prediction system comprises a server 104 and rain attenuation prediction devices 1 and 2 . Server 104 and rain attenuation prediction devices 1 and 2 are connected via Internet 105 .

The server 104 is a device installed in the General Incorporated Foundation Meteorological Business Support Center, and receives weather data (1 km mesh nationwide synthetic radar GPV (Grid Point Value) every 5 minutes) via FTP communication via the Internet 105. to the rain attenuation prediction devices 1 and 2.

The Japan Meteorological Agency uses 20 weather radars nationwide to observe the converted precipitation intensity [mm/h] for each area of about 1 km mesh (1 km ² ). The server 104 converts this 1km mesh unit converted rainfall intensity into weather data every 5 minutes (hereinafter referred to as "weather data of 1km mesh rainfall intensity every 5 minutes"), and converts it into the user's device (for example, the rain attenuation prediction device 1 , 2). The converted rainfall intensity is a value obtained by converting instantaneous rain or snow intensity per hour.

The rain attenuation prediction devices 1 and 2 receive weather data of 1 km mesh rain intensity every 5 minutes from the server 104 . Then, the rain attenuation prediction devices 1 and 2 will pass through a predetermined place between the current time and the prediction time based on the current (latest) rainfall intensity every 5 minutes and the movement pattern of rain clouds. Predict the maximum rainfall intensity due to rain clouds). Rain attenuation prediction devices 1 and 2 calculate the amount of rain attenuation from the maximum rain intensity, and predict the line reception level at a predetermined target location.

The predetermined location is, for example, an STL line or a TTL line (hereinafter referred to as "target line”).

A rainfall attenuation prediction device 1 according to a first embodiment, which will be described below, predicts rainfall attenuation using a rain cloud movement pattern (movement speed and movement direction) set in advance by a user's operation. Specifically, the rain attenuation prediction device 1 acquires the rain intensity actually observed every predetermined time (every 5 minutes in this example). Then, the rain attenuation prediction device 1 predicts the maximum rainfall intensity due to rain clouds that will pass through the target line between the current time and the prediction time based on the rainfall intensity every 5 minutes and a preset movement pattern. , the rain attenuation amount is calculated from the maximum rainfall intensity, and the line reception level is predicted. The rain attenuation prediction device 1 determines the possibility of interruption of broadcasting based on the line reception level and a preset threshold value.

This eliminates the need for the conventional process of approximating with a logarithmic normal distribution (the process of Patent Document 1), so it is possible to predict rainfall attenuation with a simple process. In addition, since the focus is on the rain clouds passing through the target line between the current time and the prediction time, unlike the process of directly predicting rainfall attenuation from the rainfall intensity for each predetermined time, rainfall attenuation is not overlooked. can be predicted with certainty. When it is determined that there is a possibility of a broadcast interruption, it is possible to avoid the interruption of the broadcast by switching the target line being used to the backup line if there is one prepared separately. becomes.

Also, the rain attenuation prediction device 2 of the second embodiment obtains the rain intensity actually observed every predetermined time, and sets the movement pattern of rain clouds based on the rain intensity every 5 minutes. The rain attenuation prediction device 2 predicts the line reception level by the same processing as in the first embodiment based on the rainfall intensity every 5 minutes and the set movement pattern, and determines the possibility of interruption of broadcasting.

As a result, the movement pattern of the rain clouds is not set in advance by the user's operation, but is set using the actually observed rainfall intensity. can be reliably avoided.

[Example 1]
First, Example 1 will be described. As described above, the first embodiment uses a preset movement pattern of rain clouds to predict the maximum rainfall intensity due to rain clouds that will pass through the target line based on the rainfall intensity actually observed every 5 minutes. Then, the rain attenuation amount is calculated from the maximum rainfall intensity to predict the line reception level. Then, the possibility of interruption of broadcasting is determined.

FIG. 2 is a block diagram showing a configuration example of the rain attenuation prediction device 1 of the first embodiment, and FIG. 3 is a flowchart showing a processing example of the rain attenuation prediction device 1 of the first embodiment. This rain attenuation prediction device 1 includes a receiver 10 , a memory 11 , a prediction section 12 , a determination section 13 and a display section 14 .

The receiving unit 10 receives weather data of 1 km mesh rainfall intensity every 5 minutes from the server 104 installed in the Japan Meteorological Business Support Center, and stores the weather data in the memory 11 (step S301). The memory 11 stores the latest weather data and past weather data. The meteorological data consists of the time every 5 minutes, the point of 1 km mesh, and the precipitation intensity. The process of step S301 is always executed.

The prediction unit 12 inputs a movement pattern preset by the user (step S302). Also, the prediction unit 12 inputs prediction time preset by the user, line point information, frequency information, etc., and reads weather data from the memory 11 .

Here, the movement pattern consists of the movement speed and movement direction of rain clouds, and is set in advance by the user in the first embodiment, and is calculated as current data based on received weather data in the second embodiment, which will be described later. The line point information is information for specifying the target line. Details of the movement pattern will be described later. Details of the line point information, frequency information, etc. will also be described later.

The movement pattern, predicted time, line point information, frequency information, etc. can be changed according to the user's operation. When the movement pattern or the like is changed by the user's operation, the prediction unit 12 immediately inputs the changed movement pattern or the like, and uses the changed movement pattern or the like for the processing described later. Moreover, since the weather data stored in the memory 11 is updated every five minutes, the prediction unit 12 reads the latest weather data at the timing when the weather data is updated.

Based on the movement pattern, the prediction unit 12 selects an area (current rain cloud area) for sorting the rainfall intensity due to rain clouds that will pass through the target line from the current time to the prediction time as a sorting range. (step S303). As a result, a sorting range is set with reference to the target line.

The prediction unit 12 identifies the maximum rainfall intensity within the sorting range using the latest weather data (step S304). As a result, the maximum rainfall intensity due to rain clouds that will pass through the target line between the current time and the predicted time is specified.

The prediction unit 12 calculates rainfall attenuation from the maximum rainfall intensity (step S305). As a result, the rainfall attenuation amount corresponding to the maximum rainfall intensity in the target line from the current time to the prediction time is obtained.

The prediction unit 12 predicts the line reception level from the reference reception level and rain attenuation (step S306). As a result, the line reception level corresponding to the maximum rainfall intensity on the target line from the current time to the prediction time is predicted.

The prediction unit 12 outputs the predicted value of the line reception level to the determination unit 13, and also outputs the current precipitation intensity, line point information, line reception level (line reception level prediction value), etc. to the display unit 14 as display data. do. Details of the processing of the prediction unit 12 will be described later.

The determination unit 13 receives the predicted value of the line reception level from the prediction unit 12, compares the predicted value of the line reception level with a threshold preset by the user, and determines whether or not there is a possibility of interruption of the broadcast. . If the predicted value of the line reception level is equal to or less than the threshold, the determination unit 13 determines that there is a possibility that the broadcast will be interrupted, generates an alarm indicating that the broadcast may be interrupted, and outputs the alarm to the display unit 14 and the outside. (step S307).

Since the threshold is a value indicating that there is a possibility that the broadcast may be interrupted at the broadcasting station (musical hall) 101, broadcasting station (master station) 102, or relay stations 103-1, 103-2, etc. of the target line, the determination unit 13, it is determined whether or not the predicted value of the line reception level has decreased to a value (warning level) at which there is a possibility that the broadcast will be interrupted. As a result, by outputting the warning to the outside, it is possible to notify the user, for example, by voice that there is a possibility that the broadcast will be interrupted.

If the predicted value of the line reception level is greater than the threshold, the determination unit 13 determines that there is no possibility of interruption of the broadcast. The determination unit 13 outputs to the outside a determination result indicating whether or not there is a possibility of interruption of broadcasting.

When the line point information indicates a plurality of target lines, the line reception level prediction processing by the prediction unit 12 and the broadcast interruption possibility determination processing by the determination unit 13 are performed for each of the plurality of target lines. and The threshold is set for each target line, and the same applies to frequency information and the like.

The display unit 14 receives display data from the prediction unit 12 and an alarm from the determination unit 13, and displays the display data and the alarm on the screen. Display data and alarm screen displays shall be constantly updated. As a result, the user can recognize the current rainfall intensity, the target line, the predicted value of the line reception level, and the like, and can recognize the possibility of interruption of the broadcast. A screen example displayed by the display unit 14 will be described later.

The prediction unit 12 may read past weather data from the memory 11 according to the user's operation, obtain the maximum rainfall intensity at that time, calculate the rainfall attenuation amount, and predict the line reception level. In this case, the determination unit 13 determines whether or not there is a possibility that the broadcast will be interrupted at that time, and the display unit 14 displays the display data and the warning at that time on the screen.

In addition, the rain attenuation prediction device 1, according to the user's operation, outputs the prediction value of the rain attenuation amount and the line reception level for the period specified by the user, the display data, etc., in a format such as an Excel (registered trademark) file. You can also output with

(Prediction unit 12)
Next, the prediction unit 12 shown in FIG. 2 will be described in detail. As described above, the prediction unit 12 inputs a preset movement pattern, sets a sorting range, specifies the maximum rainfall intensity within the sorting range, calculates rainfall attenuation, and predicts the line reception level. (processing of steps S302 to S306 shown in FIG. 3) is performed.

FIG. 4 is a block diagram showing a configuration example of the prediction unit 12. As shown in FIG. The prediction unit 12 includes a sorting range setting unit 20 , a rain intensity sorting unit 21 , a rain attenuation amount prediction unit 22 and a reception level prediction unit 23 .

The sorting range setting unit 20 inputs a preset movement pattern, preset predicted time and line point information, and specifies a target line from the line point information.

The predicted time indicates the time when the line reception level is predicted. That is, with the current time as a reference, the line reception level (lowest line reception level) up to the prediction time is predicted. The line point information includes information on the broadcasting station (playground) 101 and the broadcasting station (master station) 102 indicating the radio wave transmitting point, and the broadcasting station (master station) 102 and the relay station 103-1 indicating the radio wave receiving point. etc.

The sorting range setting unit 20 sets a sorting range for sorting the current rainfall intensities caused by rain clouds that are likely to pass through the target line between the current time and the predicted time based on the movement pattern. Then, sort range setting section 20 outputs the sort range to rain intensity sort section 21 .

FIG. 5(1) is a diagram for explaining the sorting range C, and shows an example in which a rain cloud moves due east. The radio wave transmitting point (transmitting station) is the line point α1, the radio wave receiving point (receiving station) is the line point α2, and the propagation path between the transmitting station line point α1 and the receiving station line point α2 is the target line β. do. Let A be the moving direction of the rain cloud, B be the sorting direction, C be the sorting range, L be the moving distance of the rain cloud, and M1 to M31 be the areas of the 1-km mesh. In the 1-km mesh area, black areas indicate high precipitation intensity, black-dotted areas indicate medium precipitation intensity, and blank areas indicate low precipitation intensity.

The sorting range setting unit 20 multiplies the moving speed included in the moving pattern by the predicted time to obtain the moving distance L. FIG. Then, the sort range setting unit 20 sets the opposite direction of the moving direction (moving direction A of the rain cloud) included in the moving pattern as the sorting direction B, and moves by the moving distance L in the sorting direction B with the target line β as a reference. Find the range of movement when As a result, a rectangular movement range surrounded by a straight line indicated by the target line β and a straight line indicated by the movement distance L in the sorting direction B is obtained. The sorting range setting unit 20 sets a sorting range C, which is a 1-km mesh range that overlaps with the movement range. In FIG. 5(1), 1-km meshes M1 to M31 are set as the sorting range C. In FIG.

In addition, the movement speed included in the movement pattern must be a speed that does not overlook rainfall attenuation in order to predict rainfall attenuation with high accuracy. set. For example, the maximum speed (for example, 60 [km/h]) of a typhoon that has passed near the target line β in the past is set. If the movement speed is set to a value higher than the actual speed of the rain cloud, the chance of missing rainfall attenuation will be reduced, but if the movement speed is set too fast, the prediction error will increase, so the movement speed is not appropriate. must be set to a valid value. Also, the direction of movement included in the movement pattern is set in consideration of the direction of rain clouds observed in the past, in order to predict rainfall attenuation with high accuracy.

Returning to FIG. 4, the precipitation intensity sorting unit 21 inputs the sorting range from the sorting range setting unit 20, reads out the latest weather data from the memory 11, and uses the weather data to generate a maximum of 1 km mesh within the sorting range. Determine precipitation intensity. The rain intensity sorting unit 21 then outputs the maximum rain intensity (maximum rain intensity of the target line) to the rain attenuation amount prediction unit 22 .

FIG. 5(2) is a diagram for explaining the maximum rainfall intensity obtained by sorting the sort range C shown in FIG. 5(1).

The precipitation intensity sorting unit 21 sets the opposite direction to the moving direction A of the rain clouds as the sorting direction B, and sorts the weather Sort the precipitation intensities indicated by the data and identify the maximum precipitation intensity of the 1 km mesh. This maximum rainfall intensity is the maximum rainfall intensity due to rain clouds that will pass through the target line β between the current time and the prediction time.

Specifically, the rain intensity sorting unit 21 identifies 1-km meshes M10, M20, M21, and M31, among the 1-km meshes M1 to M31 within the sorting range C, that overlap the target line β. Then, the precipitation intensity sorting unit 21 sorts the precipitation intensity of each of the 1-km meshes M1 to M10 in the sorting direction B within the sorting range C for the 1-km mesh M10 overlapping the target circuit β. Identify maximum precipitation intensity. Then, the precipitation intensity sorting unit 21 replaces the precipitation intensity of the 1-km mesh M10 with the specified maximum precipitation intensity.

Similarly, the rain intensity sorting unit 21 sorts the rain intensity in the sort direction B within the sort range C for each of the 1-km meshes M20, M21, and M31 overlapping the target circuit β, and identifies the maximum rain intensity. . Then, the rain intensity sorting unit 21 replaces the rain intensities of the 1-km meshes M20, M21, and M31 with the specified maximum rain intensities. The rain intensity sorting unit 21 identifies the highest rain intensity among the rain intensities (maximum rain intensity) of the 1-km meshes M10, M20, M21, and M31 after replacement as the maximum rain intensity of the target line β.

As a result, the maximum rainfall intensity due to rain clouds that will pass through the target line β between the current time and the predicted time is obtained.

Here, the movement direction A included in the movement pattern needs to be a direction that does not overlook rainfall attenuation in order to predict rainfall attenuation with high accuracy, and it is desirable that a plurality of directions be set.

FIG. 6 is a diagram for explaining an example when nine movement directions A are set, and shows a case where the sort range setting unit 20 inputs nine movement patterns. In order not to overlook the occurrence of rainfall attenuation, it is desirable to appropriately set not only the moving speed of the rain cloud but also the moving direction A.

Therefore, the present inventors diligently studied the movement tendency of rain clouds observed in the past with respect to the movement direction A of rain clouds, and repeated prediction experiments of rainfall attenuation. As a result, it was found that setting nine movement directions A shown in FIG. 6 with the top, bottom, left, and right in FIG.

As shown in FIG. 6, the movement direction A consists of a total of nine directions from the northeast to the southeast, in addition to the case where the rain cloud moves due east shown in FIG.

The precipitation intensity sorting unit 21 sets sorting ranges C for nine moving directions A, respectively, as shown in FIG. Then, the rainfall intensity sorting unit 21 performs the same processing as described above for each of the nine sorting ranges C, and specifies the maximum rainfall intensity of the target line β. The rain intensity sorting unit 21 outputs the maximum rain intensity of the target line β to the rain attenuation amount prediction unit 22 for each of the nine moving directions A. FIG.

Returning to FIG. 4, the rain attenuation amount prediction unit 22 receives the maximum rain intensity of the target line from the rain intensity sorting unit 21, and also inputs preset frequency information and polarization plane information. Then, the rain attenuation amount prediction unit 22 predicts the rain attenuation amount based on the maximum rainfall intensity, frequency information, polarization plane information, and propagation distance (1 km in this example). As a result, a predicted value of rain attenuation in the target line is obtained. The frequency information is information about the frequency of radio waves, and the polarization plane information is information about the plane of polarization of radio waves. The rain attenuation amount prediction unit 22 outputs the rain attenuation amount (predicted value of rain attenuation amount) to the reception level prediction unit 23 .

Specifically, the rain attenuation amount γ _R [dB/km] is calculated by the following formula using the maximum rainfall intensity R [mm/h], frequency information, polarization plane information, and propagation distance.
[Number 1]
γ _R =k·R ^α (1)
k and α are parameters determined by frequency information and polarization plane information.

The propagation distance is the distance of the propagation path passing through each mesh. Further, the above formula (1) is a formula defined by ITU-R, and for details, please refer to the following literature.
International Telecommunication Union, “Specific attenuation model for rain for use in prediction methods”, Recommendation ITU-R P.838-3, Mar. 2005

Here, it is assumed that nine movement directions A are set as shown in FIG. 6, that is, nine movement patterns are input to the sort range setting unit 20 . The rain attenuation amount prediction unit 22 inputs the maximum rain intensity of the target line β in each of the nine moving directions A from the rain intensity sorting unit 21 .

The rain attenuation amount prediction unit 22 calculates the rain attenuation amounts γ _R-1 , γ _{R -2} , . . The rain attenuation amount prediction unit 22 specifies the maximum rain attenuation amount among the rain attenuation amounts γ _R-1 , γ _{R -2} , . . Thereby, the predicted value of the rain attenuation amount in the target line β is obtained. The rain attenuation amount prediction unit 22 outputs the specified rain attenuation amount (predicted value of rain attenuation amount) to the reception level prediction unit 23 .

Note that the rain intensity sorting unit 21 outputs the largest maximum rain intensity among the maximum rain intensity in each of the nine movement directions A to the rain attenuation amount prediction unit 22 as the maximum rain intensity of the target line β. good too. In this case, the rain attenuation amount prediction unit 22 uses the maximum rain intensity of the target line β input from the rain intensity sort unit 21 to predict the rain attenuation amount γ _R using the above equation (1).

Here, as described above, the sorting range setting unit 20 provided in the prediction unit 12 sets the sorting range using the movement pattern, the precipitation intensity sorting unit 21 sorts the precipitation intensity to obtain the maximum precipitation intensity, The rain attenuation amount prediction unit 22 predicts rain attenuation. On the other hand, the prediction unit 12 can also predict rainfall attenuation using only meteorological data for every 5 minutes. However, if only the meteorological data every 5 minutes is used, the occurrence of rainfall attenuation may be overlooked, which is not appropriate.

FIG. 7 is a diagram for explaining the possibility of overlooking the occurrence of rainfall attenuation when using only five-minute weather data. (1) shows the rainfall intensity distribution (delivered weather data) at time t1, and (3) shows the rainfall intensity distribution (delivered weather data) at time t2. The interval between times t1 and t2 is 5 minutes, which is the weather data delivery interval time. (2) is the distribution of the rainfall intensity assumed at a predetermined time t' between the times t1 and t2. Time t' is the time when the maximum rainfall intensity passes through the target line β, that is It shows the maximum time.

As shown in FIG. 7, if only weather data for every 5 minutes at times t1 and t2 is used, the distribution of rainfall intensity at time t' is not assumed, so there is a possibility that the occurrence of rainfall attenuation will be overlooked. For this reason, processing using only weather data every 5 minutes is not preferable. Therefore, as in the processing by the sort range setting unit 20, the precipitation intensity sorting unit 21, and the rain attenuation amount prediction unit 22 of the prediction unit 12 shown in FIG. By doing so, the occurrence of rain attenuation was not overlooked.

Returning to FIG. 4, the reception level prediction section 23 inputs the rain attenuation amount from the rain attenuation amount prediction section 22 and also inputs a preset reference reception level. The reference reception level is the average value of reception level measurements when there is no rain on the target line. As a result, instead of using the theoretical value at the time of line design as the reference reception level, the average value of the reception level measured without rainfall is used, so that only the effect of rain attenuation is used in the predicted value of the line reception level. can be reflected. By using a value including an average value of actually measured values such as distance attenuation, antenna gain, fading, etc. as the reference reception level, the influence of these can be reflected in the predicted value of the line reception level.

The reception level prediction unit 23 uses the reference reception level as a reference value and subtracts the amount of rain attenuation from the reference reception level to obtain the line reception level. As a result, the predicted value of the line reception level at the current point of time in the target line is obtained. The reception level prediction section 23 outputs the line reception level to the determination section 13 .

Although details are not shown in FIG. 4, the prediction unit 12 outputs the current rainfall intensity, line point information, line reception level (line reception level prediction value), etc. as display data to the display unit 14 .

FIG. 8 is a diagram showing an example of a display screen displayed by the display unit 14. As shown in FIG. On this display screen, the target line β (arrow ←) and the line points α1 and α2 (circles) of the target line β are drawn on the map, and the current rainfall intensity for each 1-km mesh is displayed on the map. is drawn in the form (a) according to FIG. 8 shows the display data at the current time of 16:36.

Also, on the display screen, the name (b) of the transmitting station that is the line point α1 and the receiving station that is the line point α2 of the target line β, the reference level (reference reception level) (c), and the possibility that the target line β will be interrupted are displayed. A certain value (alert level) (d) of is displayed. Furthermore, the display screen displays the predicted value (e) of the line reception level from the current time to the predicted time of 10 minutes.

In FIG. 8, the predicted time is set to 10 minutes. The reason why the prediction time is set to 10 minutes is that the data delivery interval is 5 minutes. , the display error increases.

Although not shown in FIG. 8, when the display unit 14 receives an alarm from the determination unit 13, it displays an alarm such as "broadcast may be interrupted" and highlights the part of the target line β where the alarm is generated. .

As a result, the user can recognize the current rainfall intensity, the position of the target line β, the estimated value of the line reception level, etc. β can be recognized.

(Experimental result)
Next, experimental results by the rain attenuation prediction device 1 of Example 1 will be described. FIG. 12 is a diagram showing the experimental results of Example 1, and shows the experimental results for a predetermined target line β in a certain area with nine movement patterns (FIG. 6) and a prediction time of 10 minutes. ing. The horizontal axis indicates time, and the vertical axis indicates the line reception level [dBm] in a predetermined target line β. The solid line indicates the measured value of the line reception level (the value actually observed at the broadcasting station (music venue) 101, the broadcasting station (master station) 102, or the repeater station 103-1, etc.), and the dotted line indicates the rain attenuation prediction device 1. shows the predicted value of the line reception level calculated by the prediction unit 12 of the .

From the measured values and predicted values shown in FIG. 12, the predicted values follow changes in the actual line reception level. That is, the rain attenuation prediction device 1 correctly predicts the rain attenuation of the target line β.

In particular, from the measured values shown in FIG. 12, it can be seen that heavy rain occurred at time 16:32 and the line reception level of the predetermined target line β decreased. Further, from the predicted values shown in FIG. 12, when the weather data was received at time 16:30, that is, approximately two minutes before time 16:32 when the torrential rain occurred, the line reception level of the predetermined target line β at time 16:32 It can be seen that the decrease in

As described above, according to the rain attenuation prediction device 1 of the first embodiment, the receiving unit 10 receives weather data of 1 km mesh rain intensity every 5 minutes and stores the weather data in the memory 11 .

Based on a preset movement pattern, the prediction unit 12 sets, as a sorting range, the current rain cloud area that is likely to pass through the target line between the current time and the predicted time. Then, the prediction unit 12 identifies the maximum rainfall intensity within the sorting range using the latest weather data stored in the memory 11, calculates the rainfall attenuation from the maximum rainfall intensity, and calculates the rainfall attenuation from the reference reception level and the rainfall attenuation. Predict line reception levels.

The determination unit 13 compares the line reception level predicted by the prediction unit 12 with a threshold, and determines that there is a possibility of interruption of broadcasting when the line reception level is equal to or lower than the threshold.

This eliminates the need for complicated processing such as conventional approximation with a logarithmic normal distribution (the processing of Patent Document 1), so it is possible to predict rainfall attenuation with simple processing. In addition, since the focus is on the rain clouds passing through the target line between the current time and the prediction time, unlike the process of directly predicting rainfall attenuation from the rainfall intensity for each predetermined time, rainfall attenuation is not overlooked. can be predicted with certainty. When it is determined that there is a possibility of a broadcast interruption, it is possible to avoid the interruption of the broadcast by switching the target line being used to the backup line if there is one prepared separately. becomes.

[Example 2]
Next, Example 2 will be described. As described above, in the second embodiment, the actually observed rainfall intensity is acquired every 5 minutes, and the movement pattern of rain clouds is set based on this rainfall intensity. Then, based on the rainfall intensity and movement pattern every 5 minutes, predict the maximum rainfall intensity due to rain clouds that will pass through the target line, calculate the rainfall attenuation from the maximum rainfall intensity, and predict the line reception level, Determine the possibility of a break in broadcasting.

In the first embodiment, if the moving speed and moving direction of the rain cloud, which are the preset moving patterns, are different from the actual moving speed and moving direction of the rain cloud, the prediction error of rain attenuation increases, resulting in interruption of the broadcast. may erroneously predict the possibility of

Therefore, in the second embodiment, movement patterns are set based on actually observed weather data. As a result, rain attenuation can be predicted with higher accuracy than in the first embodiment, and the possibility of broadcast interruption can be predicted with higher accuracy.

FIG. 9 is a block diagram showing a configuration example of the rain attenuation prediction device 2 of the second embodiment, and FIG. 10 is a flow chart showing a processing example of the rain attenuation prediction device 2 of the second embodiment. This rain attenuation prediction device 2 includes a receiver 10 , a memory 11 , a prediction section 12 , a determination section 13 , a display section 14 and a movement pattern setting section 15 .

Comparing the rain attenuation prediction device 1 of the first embodiment and the rain attenuation prediction device 2 of the second embodiment shown in FIG. , determination unit 13 and display unit 14. On the other hand, the rain attenuation prediction device 2 is different from the rain attenuation prediction device 1 which does not include the movement pattern setting unit 15 in that it includes the movement pattern setting unit 15 .

Further, when comparing the processing example of the first embodiment shown in FIG. is the same as the processing of On the other hand, the processing of step S1002 by the rain attenuation prediction device 2 is different from the processing of step S302 by the rain attenuation prediction device 1 .

The processing of the receiving unit 10, the memory 11, the predicting unit 12, the determining unit 13, and the display unit 14 is the same as that of the first embodiment, and thus the description thereof is omitted here. Also, the processing of steps S1001 and S1003 to S1007 is the same as that of the first embodiment, so the description is omitted here.

The movement pattern setting unit 15 inputs line point information preset by the user and reads weather data from the memory 11 . Then, the movement pattern setting unit 15 sets the target line from the line point information, analyzes the latest weather data and past weather data in time series, and determines the current movement pattern of rain clouds near the target line. The speed and moving direction are set (step S1002). The movement pattern setting unit 15 then outputs the movement pattern to the prediction unit 12 .

FIG. 11 is a diagram illustrating an example of movement pattern setting processing by the movement pattern setting unit 15. As shown in FIG. The movement pattern setting unit 15 reads the latest weather data and past (for example, five minutes ago) weather data from the memory 11 .

The movement pattern setting unit 15 sets a reference frame W1 of a predetermined area including the target line for the distribution of the current weather data drawn on the map. In addition, the movement pattern setting unit 15 draws a frame W2 having the same size as the reference frame W1 within a predetermined search area centered on the same area as the reference frame W1 for the distribution of the past weather data drawn on the map. set.

The movement pattern setting unit 15 performs matching between the distribution of the weather data in the reference frame W1 and the distribution of the weather data in the frame W2. The movement pattern setting unit 15 obtains the difference between the distribution of the weather data in the reference frame W1 and the distribution of the weather data in the frame W2 while sequentially shifting the frame W2 by a predetermined distance within the predetermined search area. is the smallest (highest degree of matching).

That is, the movement pattern setting unit 15 performs matching between the rainfall intensity distribution of the reference frame W1 and the rainfall intensity distribution for each of the plurality of frames W2, and determines the difference between the rainfall intensity distributions among the plurality of frames W2. is the smallest (highest degree of matching).

The movement pattern setting unit 15 obtains the distance between the reference frame W1 and the frame W2′, obtains the time difference between the current weather data read from the memory 11 and the past weather data, and divides the distance by the time difference. to find the moving speed of rain clouds. The movement pattern setting unit 15 also obtains the direction of the reference frame W1 with respect to the frame W2', and sets this as the movement direction of the rain cloud. In this way, the movement pattern of rain clouds is set based on the weather data.

As described above, according to the rain attenuation prediction device 2 of the second embodiment, the movement pattern setting unit 15 analyzes the weather data in time series to determine the current movement pattern of rain clouds near the target line. and set the movement direction.

Based on the movement pattern set by the movement pattern setting section 15, the prediction section 12 sets the current rain cloud area that is likely to pass through the target line between the current time and the prediction time as a sorting range. Then, the prediction unit 12 identifies the maximum rainfall intensity within the sorting range using the latest weather data stored in the memory 11, calculates the rainfall attenuation from the maximum rainfall intensity, and calculates the rainfall attenuation from the reference reception level and the rainfall attenuation. Predict line reception levels.

The determination unit 13 compares the line reception level predicted by the prediction unit 12 with a threshold, and determines that there is a possibility of interruption of broadcasting when the line reception level is equal to or lower than the threshold.

As a result, rain attenuation can be easily and reliably predicted in the same manner as in the first embodiment. When it is determined that there is a possibility of a broadcast interruption, it is possible to avoid the interruption of the broadcast by switching the target line being used to the backup line if there is one prepared separately. becomes.

In addition, in the first embodiment, since rainfall attenuation is predicted using a movement pattern preset by the user, if this movement pattern differs from the actual movement pattern, the prediction error increases, and as a result, the broadcast It is possible to misestimate the possibility of discontinuity. In Example 2, a movement pattern is set based on the actually observed rainfall intensity, and rainfall attenuation is predicted based on this movement pattern. It is possible to predict the possibility of interruption of broadcasting with high accuracy.

Although the present invention has been described above with reference to Examples 1 and 2, the present invention is not limited to Examples 1 and 2, and can be variously modified without departing from the technical idea thereof. The rain attenuation prediction devices 1 and 2 of Examples 1 and 2 may be desktop devices or mobile terminals such as smartphones.

In addition, the rain attenuation prediction device 1 of the first embodiment uses, for example, nine movement patterns as shown in FIG. may be used. In short, the number of movement patterns to be used should be a number that can reduce the prediction error so that there is no rainfall attenuation prediction failure and rainfall attenuation is not over-predicted.

In addition, the rain attenuation prediction devices 1 and 2 of Examples 1 and 2 are configured to receive weather data of 1 km mesh rain intensity every 5 minutes from the server 104. is not limited to , and other time intervals may be used. Moreover, the present invention does not limit the area unit of the weather data to the 1-km mesh, and may be another area unit.

A normal computer can be used as the hardware configuration of the rain attenuation prediction devices 1 and 2 of the first and second embodiments. The rainfall attenuation prediction devices 1 and 2 are configured by a computer having a CPU, a volatile storage medium such as a RAM, a nonvolatile storage medium such as a ROM, an interface, and the like.

Each function of the receiver 10, memory 11, prediction unit 12, determination unit 13, and display unit 14 provided in the rain attenuation prediction device 1 is realized by causing the CPU to execute a program describing these functions. The functions of the receiving unit 10, the memory 11, the predicting unit 12, the determining unit 13, the display unit 14, and the movement pattern setting unit 15 provided in the rain attenuation prediction device 2 also execute programs describing these functions on the CPU. Each is realized by

These programs are stored in the storage medium and are read and executed by the CPU. In addition, these programs can be stored and distributed in storage media such as magnetic disks (floppy (registered trademark) disks, hard disks, etc.), optical disks (CD-ROM, DVD, etc.), semiconductor memories, etc., and distributed via networks. You can also send and receive Also, these programs may operate on a browser as web applications.

1, 2 rain attenuation prediction device 10 reception unit 11 memory 12 prediction unit 13 determination unit 14 display unit 15 movement pattern setting unit 20 sorting range setting unit 21 rain intensity sorting unit 22 rain attenuation amount prediction unit 23 reception level prediction unit 100 broadcasting network 101 broadcasting station
102 broadcasting station (master station)
103-1, 103-2 Relay station 104 Server 105 Internet α1 Line point (transmitting station)
α2 Line point (receiving station)
β Target line A Moving direction of rain cloud B Sorting direction C Sorting range L Moving distance of rain cloud M1 to M31 1 km mesh a value (alert level)
e Predicted value of line reception level W1 Reference frame W2 Frame

Claims (6)

In a rainfall attenuation prediction device that predicts the attenuation of radio waves due to rainfall at a predetermined location,
a receiving unit that receives the precipitation intensity actually observed for each prescribed period of time and for each prescribed area, and stores the precipitation intensity in a memory;
Predicting the attenuation of radio waves at the predetermined location from the current time to a predetermined prediction time as a rain attenuation amount based on the latest rain intensity and the predetermined moving speed and moving direction of rain clouds stored in the memory. and
The prediction unit
Sorting for setting an area for sorting the rainfall intensity due to the rain cloud predicted to pass through the predetermined location between the current time and the predicted time based on the moving speed and moving direction as a sorting range. a range setting unit;
a precipitation intensity sorting unit that reads out the latest rainfall intensity from the memory, sorts the rainfall intensities within the sort range set by the sort range setting unit, and identifies the maximum rainfall intensity at the predetermined location;
and a rain attenuation prediction unit that predicts the rain attenuation at the predetermined location based on the maximum rain intensity specified by the rain intensity sorting unit. In the rain attenuation prediction device according to claim 1,
A rain attenuation prediction device, wherein the moving speed and the moving direction are set in advance by a user. In the rain attenuation prediction device according to claim 2,
Let the moving speed preset by the user be the maximum moving speed observed in the past at the predetermined location,
A rainfall attenuation prediction device, wherein the moving directions preset by the user are a plurality of directions observed in the past at the predetermined location. In the rain attenuation prediction device according to claim 1,
Furthermore, the latest precipitation intensity and the past precipitation intensity are read from the memory, and the distribution of the first region including the predetermined location at the latest precipitation intensity and the same size as the first region at the past precipitation intensity The difference between the distribution of the first region and the distribution of the second region is minimized by performing matching between the distribution of the second region and sequentially shifting the second region by a predetermined distance A rainfall characterized by comprising a movement pattern setting unit that specifies the second area and sets the movement speed and the movement direction based on the first area and the second area where the difference is the smallest. Attenuation predictor. In the rain attenuation prediction device according to any one of claims 1 to 4,
Further comprising a determination unit, the prediction unit further comprising a reception level prediction unit,
The reception level prediction unit,
Using the reception level of the radio waves when there is no rainfall at the predetermined location as a reference reception level, the reception level at the predetermined location is calculated based on the reference reception level and the rain attenuation predicted by the rain attenuation prediction unit. to predict
The determination unit is
A rain attenuation prediction device, wherein a possibility of interruption of the broadcast at the predetermined location is determined based on the reception level predicted by the reception level prediction unit and a predetermined threshold value. A program for causing a computer to function as the rain attenuation prediction device according to any one of claims 1 to 5.

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