JP4712415B2 - Polyhedron model creation device and radar device - Google Patents

Description

  The present invention relates to a polyhedron model creating apparatus that approximately represents a three-dimensional shape of an object suitable for target recognition / identification based on a radar image by a polyhedron model, and a radar apparatus using the created polyhedron model for target recognition / identification. It is about.

In radar equipment known as inverse synthetic aperture radar, a high-frequency pulse signal generated by a transceiver is transmitted from an antenna to an unknown target, echoes reflected by the target are received by the antenna, and amplified and detected by the transceiver. The target high resolution image is reproduced based on the received signal. Further, in this type of radar apparatus, there is an apparatus that performs the following processing so that an operator can easily recognize and identify a radar image (see, for example, Patent Document 1).
In the radar apparatus disclosed in Patent Document 1, motion characteristics such as a target traveling direction, position, velocity, acceleration, and the like are estimated using the same received signal, and from the estimation result and the specifications of the radar apparatus, the radar apparatus A point image response function corresponding to the impulse response is calculated. At the same time, the aspect angle of the target is estimated from the position of the target and the radar device and the traveling direction of the target, and the three-dimensional target shape data stored in advance in the target shape data storage means are sequentially read out, Based on the aspect angle, a target RCS (Radar Cross Section; radar effective reflection area) distribution is calculated. Next, since the resolution of the target shape data does not necessarily match the resolution of the radar apparatus, the RCS distribution and the point image response function are subjected to convolution integration to generate a dictionary image for recognition / identification. The dictionary image is displayed on the display means together with the radar image. Therefore, even if the radar image is different from the target image using visible light that is familiar to everyday life, the operator can easily recognize and identify the target by comparing.

Japanese Patent No. 2738244 (FIGS. 1 and 2)

  In the conventional radar apparatus disclosed in Patent Document 1, for example, a technique such as GTD (Geometrical Theory of Diffraction) is used to calculate the RCS distribution. In this case, a target is stored in the target shape data storage means. It is necessary to store data approximated by a polyhedron composed of planes. In the conventional radar apparatus, when the surface of the polyhedral shape model to be stored is not sufficiently small, the accuracy of the convolution-integrated pseudo image may be lowered. On the other hand, when the surface of the polyhedron shape model is too large, there is a problem in the data of the polyhedron stored in the target shape data storage means, such as the calculation time being increased or the calculation exceeding the storage capacity of the computer.

  The present invention has been made to solve the above-described problems, and allows the creation of a polyhedron model with uniform reliability used for target identification in consideration of the size of a plane constituting the polyhedron model. It is an object of the present invention to obtain a radar device that calculates an RCS distribution using a model creation device and shape data storage means that stores the polyhedron model.

Polyhedral model creating device according to the invention, based on the target of the three-dimensional shape information that is input from the outside, to create a polyhedral model of the target, a polyhedron model creating apparatus for storing a polyhedral model created shape data storage means The polyhedron model generating means for generating the target polyhedron model based on the target three-dimensional shape information input from the outside, the number of faces of the generated polyhedron model, the target surface area included in the shape information and the radar Based on the wavelength or frequency of the observed wave, calculate the value obtained by multiplying the average area of the plane when the target is represented by a polyhedral model by the square of the wavelength, and the reference coefficient determined according to the calculated value and the target type Is calculated by the polyhedron model generation means only when the calculated difference is compared with a preset allowable error and the difference is within the allowable error. It is intended to accumulate polyhedral model in the shape data storage means.

  According to the present invention, since the target polyhedron model is created and stored in consideration of the size of the plane constituting the polyhedron shape model, in the radar device, when the target is identified, these stored polyhedron models are stored. If the RCS distribution is calculated using the data, it is possible to prevent the accuracy of the pseudo image from being lowered or the arithmetic processing from being hindered.

Embodiment 1 FIG.
FIG. 1 is a block diagram showing a basic configuration of a polyhedron model creating apparatus according to Embodiment 1 of the present invention. In the figure, the polyhedral model creating apparatus 10 includes a polyhedral model generation unit 200 and a model evaluation unit 300. The polyhedron model generation unit 200 is a unit that generates a target polyhedron model based on target solid shape information given from the outside. The model evaluation unit 300 is a means for outputting only a polyhedron model in which a predetermined restriction is given to the size of a plane to be configured from among the polyhedron models generated by the polyhedron model generation unit 200. The coefficient calculation unit 310, the coefficient comparison Unit 320 and switching unit 330.
FIG. 2 is an explanatory diagram illustrating a display example of a target polyhedron model.

Next, the operation will be described.
First, the polyhedron model generation unit 200 generates a polyhedron model based on the target solid shape information given from the outside. Here, the target three-dimensional shape information is three-dimensional model data obtained by measurement using a stereo photograph or laser light. Alternatively, it may be three-dimensional model data constructed based on a target drawing, photograph, specification table, or the like. Further, the polyhedral model, for example, as shown in FIG. 2, a numerical data representing a combination of multiple planes the three-dimensional shape of the target.
The polyhedron model generation unit 200 converts the target into polyhedron model data composed of planes based on the three-dimensional model data. The principle is described in, for example, published by Nikkan Kogyo Shimbun, Keiichi Shioya “Shape processing technology in 3D CAD / CAM”.
Next, the model evaluation unit 300 evaluates the polyhedron model generated by the polyhedron model generation unit 200 as will be described later, and outputs and stores the polyhedron model data determined to be appropriate to the shape data storage unit 20. . On the other hand, if it is determined that it is not appropriate, the result is returned to the polyhedron model generation unit 200 to regenerate the polyhedron model.

The operation in the model evaluation unit 300 will be described in detail.
The coefficient calculation unit 310 uses, as input data, the number of faces N of the polyhedron model, the target surface area S included in the target three-dimensional shape information, and the wavelength λ (or frequency) of the observation wave. Based on these input data, the coefficient calculation unit 310 calculates the coefficient α by, for example, processing based on Expression (1).
α = S / N · λ ² (1)
As is clear from the equation (1), the coefficient α is a value obtained by normalizing the average area of the plane when the target is represented by a polyhedral model by the square of the wavelength. Next, the coefficient comparison unit 320 compares the difference between the coefficient α calculated by the coefficient calculation unit 310 and the reference coefficient k with a preset allowable error δ. The reference coefficient k is a value determined according to the target type. When the comparison result is within the allowable error, the switching unit 330 is controlled to switch so that the polyhedron model data from the polyhedron model generation unit 200 is sent to the shape data storage unit 20 and stored. For example, when the coefficient α is significantly smaller than the reference coefficient k, it means that the face of the polyhedron model is small or the number of faces is too large, so the polyhedron model generation unit 200 increases the face. The polyhedron model is regenerated by operating to increase the number of faces. On the other hand, when the coefficient α is significantly larger than the reference coefficient k, it means that the face of the polyhedron model is large or the number of faces is too small. Therefore, the polyhedron model generation unit 200 reduces the face. The polyhedron model is regenerated by operating to reduce the number of faces.
On the other hand, when the comparison result exceeds the allowable error, the switching unit 330 is switched and controlled so that the polyhedral model data is fed back to the polyhedral model generation unit 200.

  As described above, according to the first embodiment, with respect to the polyhedron model generated by the polyhedron model generation unit 200, the model evaluation unit 300 normalizes the average area of the plane constituting the polyhedron model by the square of the wavelength. Since the surface size of the polyhedron model is constrained based on the quantity, a polyhedron model database with uniform reliability can be constructed for use in identifying targets by the radar device. Further, only shape data that can be calculated in a realistic time and whose calculation accuracy is guaranteed can be stored in the shape data storage means 20. Furthermore, by manipulating and setting the reference coefficient k according to the target type such as an aircraft or a ship, for example, the shape data of the polyhedron model with uniform calculation accuracy can be accumulated for each target type.

Embodiment 2. FIG.
FIG. 3 is a block diagram showing a basic configuration of a polyhedral model creation apparatus according to Embodiment 2 of the present invention. In the figure, parts corresponding to those in FIG. Here, it is different from FIG. 1 in that a surface area calculation unit 400 is newly provided.
In the surface area calculation unit 400, the data of the polyhedron model generated by the polyhedron model generation unit 200 is input, the sum of the surface areas of all the surfaces constituting the polyhedron model is calculated, and the model evaluation unit 300 is set as the target surface area S. Output to. The model evaluation unit 300 performs the same model evaluation process as described in the first embodiment using the target surface area S.
As described above, according to the second embodiment, since the target surface area S is calculated from the polyhedron model, it is not necessary to include the target surface area in the target solid shape information given from the outside.

Embodiment 3. FIG.
4 is a block diagram showing a basic configuration of a polyhedron model creating apparatus according to Embodiment 3 of the present invention. In the figure, portions corresponding to those in FIG. 1 are denoted by the same reference numerals, and description thereof will be omitted in principle. Here, in place of the model evaluation unit 300 of FIG. 1, a model evaluation unit 301 that performs different processing is provided. The model evaluation unit 301 includes a maximum area calculation unit 340, a coefficient calculation unit 311, a coefficient comparison unit 321, and a switching unit 320.

Next, the operation will be described.
In the model evaluation unit 300, the maximum area calculation unit 340 extracts the one having the maximum area S _max from the surfaces constituting the polyhedron model generated by the polyhedron model generation unit 200. The coefficient calculation unit 311 calculates the coefficient β by, for example, processing based on the equation (2) based on the maximum area S _max and the wavelength λ (or frequency) of the observation wave.
β = S _max / λ ² (2)
As is clear from the equation (2), the coefficient β is a value obtained by normalizing the maximum area S _max of the plane formed when the target is represented by a polyhedral model by the square of the wavelength λ. The coefficient comparison unit 321 compares the difference between the coefficient β and the reference coefficient k with the allowable error δ, and if it is within the allowable error, sends the polyhedral model data from the polyhedral model generation unit 200 to the shape data storage unit 20. The switching unit 330 is controlled to be accumulated. On the other hand, when the comparison result exceeds the allowable error, the switching unit 330 is switched and controlled so that the polyhedral model data is fed back to the polyhedral model generation unit 200.

  As described above, according to the third embodiment, with respect to the polyhedron model generated by the polyhedron model generation unit 200, the model evaluation unit 301 normalizes the maximum area of the plane constituting the polyhedron model by the square of the wavelength. Since the surface size of the polyhedral model is constrained on the basis of the value, only shape data that can be calculated in a realistic time and whose accuracy is guaranteed to some extent is stored in the shape data storage means 20. be able to. Further, by operating and setting the reference coefficient k according to the target type such as an aircraft or a ship, for example, the shape data of the polyhedron model with the same calculation accuracy can be accumulated for each target type.

Embodiment 4 FIG.
FIG. 5 is a block diagram showing a basic configuration of a polyhedron model creating apparatus according to Embodiment 4 of the present invention. In the figure, portions corresponding to those in FIG. 1 are denoted by the same reference numerals, and description thereof will be omitted in principle. Here, instead of the model evaluation unit 300 of FIG. 1, a model evaluation unit 302 that performs different processing is provided. The model evaluation unit 302 newly includes a reference coefficient calculation unit 350 for generating the reference coefficient k internally instead of inputting the reference coefficient k from the outside.

Next, the operation will be described.
In the model evaluation unit 302, the reference coefficient calculation unit 350 uses the target surface area S and the wavelength λ of the observation wave to calculate the reference coefficient k by, for example, processing based on Expression (3). However, N ₀ is a standard number of planes given in advance.
k = S / N ₀ · λ ² (3)
Therefore, the coefficient comparison unit 320 compares the difference between the coefficient α and the calculated reference coefficient k with the allowable error δ and performs the model evaluation process in the same manner as described in the first embodiment. In the third embodiment, the value k obtained by providing the reference coefficient calculation unit 350 may be used as a reference coefficient for taking a difference from the coefficient β.

As described above, according to the fourth embodiment, since the reference coefficient k is calculated by the reference coefficient calculation unit 350, the model evaluation unit 302 calculates the reference coefficient k as in each of the above embodiments. There is no need to get from outside.
In the fourth embodiment, the reference coefficient k is calculated by the reference coefficient calculation unit 350, but it may be used by giving it as a constant in advance.

Embodiment 5. FIG.
FIG. 6 is a block diagram showing a basic configuration of a polyhedron model creating apparatus according to Embodiment 5 of the present invention. In each of the above embodiments, the polyhedron model generation unit 200 has been used. In the fifth embodiment, the function of the polyhedron model generation unit is performed by an operator 410 and an input / output device 420 such as a personal computer or a workstation. It is composed.
Shape information is input to the input / output device 420 from the outside. Based on the displayed shape information, the operator 410 operates the input / output device 420 to operate a predetermined processing program, and the target polyhedron model. Is generated. The model evaluation unit 300 (or 301, 302) evaluates the polyhedron model by the method described in each embodiment, and stores the polyhedron model conforming to the reference in the shape data storage unit 20. On the other hand, if the standard is not met, the operator 410 is warned via the input / output device 420, and the operator 410 corrects the target polyhedron model and outputs it again to the model evaluation unit 300 (or 301, 302).

  As described above, according to the fifth embodiment, the operator 410 evaluates and stores the polyhedron model conforming to the standard with respect to the polyhedron model generated by the input / output device 420. Although it takes time, it is possible to form a polyhedral model suitable for the actual situation of evaluation.

Embodiment 6. FIG.
FIG. 7 is a block diagram showing a basic configuration of a polyhedron model creating apparatus according to Embodiment 6 of the present invention. In the figure, the polyhedral model creation device 10 includes a polyhedral model generation unit 201 and a number-of-surfaces calculation unit 360.
Next, the operation will be described.
The number-of-surfaces calculation unit 360 forms a polyhedron model by processing based on Expression (4) based on the target surface area S, the wavelength λ (or frequency) of the observation wave, and the coefficient k _α included in the target three-dimensional shape information. The number N of faces to be calculated is calculated and output to the polyhedron model generation unit 201. However, the coefficient k _α is a reference coefficient for the coefficient α described in the first embodiment (that is, a value obtained by normalizing the average area of the plane when the target is represented by a polyhedral model by the square of the wavelength), and is a predetermined value. It is.
N = S / k _α · λ ² (4)
The polyhedron model generation unit 201 generates a target polyhedron model having the given number of faces N and sends it to the shape data storage means 20 for storage.

  As described above, according to the sixth embodiment, the polyhedron model generation unit 201 is configured to generate the target polyhedron model calculated by the number-of-surfaces calculation unit 360 and satisfying the number of surfaces N. A database of polyhedron models with uniform reliability used to identify targets can be constructed. Further, since the model evaluation process is not performed as in the first to fifth embodiments and there is no feedback loop, the polyhedral model can be accumulated in real time.

Embodiment 7. FIG.
FIG. 8 is a block diagram showing a basic configuration of a polyhedron model creating apparatus according to Embodiment 7 of the present invention. In the figure, the polyhedron model creating apparatus 10 is a polyhedron model generating unit 202 and an average area / maximum area calculating unit 370. .
Next, the operation will be described.
The average area and maximum area calculation unit 370, the wavelength of the observation wave lambda (or frequency) and the coefficient k _alpha or k _beta, the average area S _ave or maximum plane constituting the polyhedral model by processing based on formula (5) The area S _max is calculated and output to the polyhedron model generation unit 202. However, the coefficient k _α is a reference coefficient for the coefficient α of the first embodiment, and the coefficient k _β is a reference coefficient for the coefficient β of the third embodiment.
S _ave = k _α・ λ ²
S _max = k _β · λ ² (5)
Therefore, the polyhedron model generation unit 202 generates a target polyhedron model having a given average area _Save or maximum area S _max and stores it in the shape data storage unit 20.

As described above, since the polyhedron model generation unit 202 is configured to generate a target polyhedron model that satisfies the average area _Save or the maximum area _Smax calculated by the average area / maximum area calculation unit 370, the radar apparatus The database of polyhedron models with uniform reliability used for identifying targets can be constructed. Further, since the model evaluation process is not performed as in the first to fifth embodiments and there is no feedback loop, the polyhedral model can be accumulated in real time.

Embodiment 8. FIG.
FIG. 9 is a block diagram showing a basic configuration of a polyhedron model creating apparatus according to Embodiment 8 of the present invention. In the figure, parts corresponding to those in FIG. Here, instead of the model evaluation unit 300 of FIG. 1, a model evaluation unit 303 that performs different processing is provided. The model evaluation unit 303 includes only the coefficient calculation unit 310 without using the coefficient comparison unit.
Next, the operation will be described.
In the model evaluation unit 303, the coefficient calculation unit 310 calculates the coefficient α by the processing based on the formula (1) as in the first embodiment. The calculated coefficient α is stored in the shape data storage unit 20 together with the polyhedron model data generated by the polyhedron model generation unit 200. By doing so, the radar apparatus side uses the shape data storage means 20 to read out the polyhedron model and the coefficient α, take the difference from the reference coefficient k in the same manner as described in the first embodiment, and set a preset allowable error. Compare with δ. Then, the RCS distribution is calculated by extracting a polyhedron model that is within an allowable error, that is, a constraint on the size of the surface.

As described above, according to the eighth embodiment, the coefficient α (index) calculated by the model evaluation unit 303 is accumulated together with the polyhedron model generated by the polyhedron model generation unit 200. When identifying a target based on the accumulated polyhedron model, by extracting the polyhedron model that constrains the size of the surface using this coefficient α, the reliability of the shape data, and thus the reliability of the identification result Can be grasped quantitatively. In addition, since the polyhedron model is configured not to make a comparison for matching the reference, there is no feedback loop, and the polyhedron model can be accumulated in real time.
In this example, the coefficient α is calculated and accumulated, but instead, the maximum area calculation unit 340 and the coefficient calculation unit 311 used in the third embodiment are provided to calculate the coefficient β. The same effect can be obtained even if the polyhedron model in which the radar apparatus side performs the same processing as in the third embodiment and restricts the size of the surface is extracted. Further, instead of accumulating the coefficient α or β, a value obtained by calculating a difference from the reference coefficient k may be accumulated as an index.

It is a block diagram which shows the basic composition of the polyhedron model production apparatus by Embodiment 1 of this invention. It is explanatory drawing showing the example of a display of the target polyhedron model which concerns on Embodiment 1 of this invention. It is a block diagram which shows the basic composition of the polyhedron model production apparatus by Embodiment 2 of this invention. It is a block diagram which shows the basic composition of the polyhedral model production apparatus by Embodiment 3 of this invention. It is a block diagram which shows the basic composition of the polyhedron model production apparatus by Embodiment 4 of this invention. It is a block diagram which shows the basic composition of the polyhedron model production apparatus by Embodiment 5 of this invention. It is a block diagram which shows the basic composition of the polyhedron model production apparatus by Embodiment 6 of this invention. It is a block diagram which shows the basic composition of the polyhedron model production apparatus by Embodiment 7 of this invention. It is a block diagram which shows the basic composition of the polyhedron model production apparatus by Embodiment 8 of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Polyhedron model production apparatus, 20 Shape data storage means, 200, 201, 202 Polyhedron model generation part, 300, 301, 302, 303 Model evaluation part, 310, 311 Coefficient calculation part, 320, 321 Coefficient comparison part, 330 Switching part , 350 reference coefficient calculation unit 360 surface number calculation unit, 370 average area / maximum area calculation unit, 400 surface area calculation unit, 410 operator, 420 input / output device.

Claims (13)

A polyhedron model creation device that creates a target polyhedron model based on the target solid shape information input from the outside, and accumulates the created polyhedron model in the shape data storage means,
A polyhedron model generating means for generating a target polyhedron model based on the target solid shape information input from the outside;
Based on the number of faces of the generated polyhedron model, the surface area of the target included in the shape information, and the wavelength or frequency of the radar observation wave, the average area of the plane when the target is represented by the polyhedron model is the square of the wavelength. Calculate the multiplied value, calculate the difference between the calculated value and the reference coefficient determined according to the target type, compare this calculated difference with a preset tolerance, and the difference is within the tolerance polyhedron model creating device you characterized in that a model evaluation means for storing a polyhedral model generated by the polyhedral model generating means in the shape data storage unit only if were. Surface area calculation means for calculating the sum of the surface areas of all the faces constituting the polyhedron model generated by the polyhedron model generation means,
The model evaluation means uses the sum of the surface areas of all the planes constituting the polyhedral model calculated by the surface area calculation means instead of the target surface area included in the shape information, and calculates the average area of the planes as the wavelength. polyhedral model creation apparatus according to claim 1, characterized in that to calculate the value obtained by multiplying the square of the. A polyhedron model creation device that creates a target polyhedron model based on the target solid shape information input from the outside, and accumulates the created polyhedron model in the shape data storage means,
A polyhedron model generating means for generating a polyhedron model of the target based on the target three-dimensional shape information;
The maximum area is extracted from the faces that make up the generated polyhedron model, and based on this maximum area and the wavelength or frequency of the observation wave, the maximum area of the plane that constitutes the target is represented by the polyhedron model. Calculate the value multiplied by the square of the wavelength of the observed wave, calculate the difference between this calculated value and the reference coefficient determined according to the target type, and compare this calculated difference with a preset tolerance. , polyhedron modeling you characterized in that a model evaluation means for storing a polyhedral model generated by the polyhedral model generating means only when the difference was within the allowable error in the shape data storage means apparatus. It is provided with a reference coefficient calculation means for calculating a reference coefficient determined according to the type of the target based on the target surface area, the wavelength of the observation wave and the number of standard surfaces given in advance in the solid shape information. The polyhedron model creation device according to any one of claims 1 to 3 . Based on the three-dimensional shape information is input from the outside appears claim from claim 1 to the input-output device for generating a polyhedral model of the target by an operation of an operator, characterized by comprising in place of the polyhedral model generation means polyhedral model creating apparatus according to any one of the four. A polyhedron model creation device that creates a target polyhedron model based on the target solid shape information input from the outside, and accumulates the created polyhedron model in the shape data storage means,
The surface area of the target included in the 3D shape information of the target input from the outside, the wavelength or frequency of the radar observation wave, and the predetermined average plane area when the target is represented by a polyhedral model are squared of the wavelength. in based on the multiplied value, and the surface number calculating means for calculating the number of surfaces to constitute a polyhedral model,
Based on the number of surfaces the shape information and the calculated of the target to generate a polyhedral model of the target consisting of the surface number, you comprising the polyhedral model generating means for storing the shape data storage means multi Face body model creation device. A polyhedron model creation device that creates a target polyhedron model based on the target solid shape information input from the outside, and accumulates the created polyhedron model in the shape data storage means,
Calculate the average area of the planes that make up the polyhedron model based on the wavelength or frequency of the observation wave and a predetermined value obtained by multiplying the average area of the plane when the target is represented by the polyhedron model by the square of the wavelength. An average area calculating means;
A polyhedron model generation unit that generates a target polyhedron model having the average area based on the target solid shape information given from the outside and the calculated average area and stores the target polyhedron model in the shape data storage unit. and polyhedron model creating apparatus you. A polyhedron model creation device that creates a target polyhedron model based on the target solid shape information input from the outside, and accumulates the created polyhedron model in the shape data storage means,
Calculate the maximum area of the planes that make up the polyhedron model based on the wavelength or frequency of the observation wave and the predetermined value obtained by multiplying the maximum area of the plane when the target is represented by the polyhedron model by the square of the wavelength. Maximum area calculation means;
A polyhedron model generation unit that generates a target polyhedron model having the maximum area based on the target solid shape information given from the outside and the calculated maximum area and stores the target polyhedron model in the shape data storage unit is provided. and polyhedron model creating apparatus you. A polyhedron model generating means for generating a target polyhedron model based on the target solid shape information input from the outside;
The number of faces of that were generated polyhedral model, on the basis of the wavelength or frequency of the three-dimensional surface area of the targets included in the shape information and the radar observations wave, the average area of a plane configuration when representing the targets polyhedral model A polyhedron model creating apparatus comprising: a model evaluation unit that calculates a value multiplied by the square of a wavelength and stores the value in the shape data storage unit together with the generated data of the target polyhedron model. A polyhedron model generating means for generating a target polyhedron model based on the target solid shape information input from the outside;
The maximum area is extracted from the faces that make up the generated polyhedron model, and based on this maximum area and the wavelength or frequency of the observation wave, the maximum area of the plane that constitutes the target is represented by the polyhedron model. A polyhedron model creation apparatus comprising: a model evaluation unit that calculates a value multiplied by the square of the wavelength of the observation wave and accumulates the generated data of the target polyhedron model in a shape data accumulation unit. The model evaluation means calculates a difference between the calculated multiplied value and a reference coefficient determined according to the target type, and instead of the multiplied value, the calculated difference is used as shape data together with the data of the target polyhedral model. The polyhedron model creation apparatus according to claim 9 or 10 , wherein the polyhedron model creation apparatus stores the data in a storage unit. Using the shape data storage means that accumulates a polyhedral model of the generated target by polyhedral model creating apparatus according to any one of claims 1 to claim 8, tracking target using a polyhedral model of stored target A radar device characterized by calculating an effective reflection area distribution of the. The target polyhedron model generated by the polyhedron model creation device according to claim 9 or 10 and a shape data storage means for storing a multiplied value or a difference value are used to multiply the read target polyhedron model. A polyhedron model in which a predetermined constraint is imposed on the size of a surface is extracted based on a value or a difference value, and an effective reflection area distribution of a tracking target is calculated using the extracted polyhedron model. Radar device.

Images