Speed ​​estimation device, target classification device, speed estimation method, and target classification method

Abstract

This speed estimation device (2) comprises: a frequency distribution calculation unit (11) that calculates a frequency distribution of a ground control point; a ground control point extraction unit (12) that extracts a ground control point from the frequency distribution; an error ellipse calculation unit (13) that calculates an error ellipse, which is an area that possibly contains a ground control point extracted from the frequency distribution; an error ellipse axis length theoretical value calculation unit (14) that calculates a theoretical value of the axis length of the error ellipse on the basis of the SNR of a received signal; an FDOA moving variance calculation unit (15) that calculates the FDOA variance between received signals on the basis of the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse that possibly contains a ground control point extracted from the frequency distribution; and a target speed component calculation unit (16) that calculates the speed component of a target on the basis of the FDOA variance.

Description

[Technical Field]

[0001] The present disclosure relates to a speed estimation device, a target classification device, a speed estimation method, and a target classification method. [Background technology]

[0002] There is a technology for detecting an unknown radio wave source using a received signal based on radio waves that are emitted from the radio wave source, relayed by a satellite, and received by an antenna. For example, Non-Patent Document 1 describes a technology for locating the position of a radio wave source by performing correlation processing between the received signals and then using information indicating the time difference of arrival (hereinafter abbreviated as TDOA) between the received radio waves and the frequency difference of arrival (hereinafter abbreviated as FDOA), which indicates the Doppler frequency difference between the received radio waves. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] dp Haworth, “Interference localization for eutelsat satellites-the first european transmitter location system,” International journal of satellite communications, vol. 15, 155-183 (1997). Summary of the Invention [Problem to be solved by the invention]

[0004] The conventional technology described in Non-Patent Document 1 can estimate the position of an unknown radio wave source (hereinafter referred to as a target), but has the problem of not being able to estimate the target's motion information. For this reason, the conventional technology cannot obtain target motion information in addition to target position information and use this information to classify targets.

[0005] The present disclosure is intended to solve the above-mentioned problems, and aims to provide a speed estimation device that can estimate target speed information for use in target classification. [Means for solving the problem]

[0006] A speed estimation device according to the present disclosure is a speed estimation device that receives radio waves transmitted from a target that is a radio wave source and arrives via a plurality of satellites, and sequentially acquires control points that are estimated positions of the target estimated based on the arrival time difference and arrival frequency difference between the received signals obtained by correlation processing between the received signals. The speed estimation device includes: a frequency distribution calculation unit that calculates a frequency distribution of the control points that have been coordinate-converted into latitude and longitude; a control point extraction unit that extracts control points that are included in an area with the highest frequency from the frequency distribution; an error ellipse calculation unit that calculates, for each pair of satellites, an error ellipse that is an area in which the control point extracted from the frequency distribution may exist; a theoretical value calculation unit that calculates a theoretical value of the axis length of the error ellipse in which the control point exists based on the signal-to-noise ratio of the received signal; a variance value calculation unit that calculates a variance value of the FDOA between received signals accompanying the movement of the target based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the control point extracted from the frequency distribution exists; and a target speed component calculation unit that calculates a speed component of the target based on the variance value. [Effects of the Invention]

[0007] According to the present disclosure, the control points included in the area with the highest frequency are extracted from the frequency distribution of the control points of the coordinate-transformed radio wave source, and the variance value of the FDOA between the received signals accompanying the movement of the target is calculated based on the difference between the axis length of the error ellipse in which the control points extracted from the frequency distribution exist and the theoretical value of the axis length of the error ellipse calculated based on the signal-to-noise ratio of the received signal. The speed estimation device according to the present disclosure can thereby estimate target speed information to be used for target classification. [Brief explanation of the drawings]

[0008] [Figure 1]1 is a block diagram showing an example of the configuration of a target classifying device according to a first embodiment. [Figure 2] FIG. 10 is a diagram illustrating an example of a frequency distribution of target orientation points. [Figure 3] FIG. 10 is a diagram illustrating an outline of a process for extracting orientation points from a frequency distribution. [Figure 4] FIG. 10 is a diagram showing information on orientation points stored in an orientation point storage unit. [Figure 5] FIG. 10 is a diagram showing the relationship between the value of γ2 and the probability that the orientation point of the target exists within the error ellipse. [Figure 6] FIG. 10 is a diagram showing an error ellipse in which orientation points exist. [Figure 7] FIG. 1 is a diagram illustrating the definition of a velocity vector in a ground coordinate system. [Figure 8] 3 is a flowchart showing a target categorization method according to the first embodiment. [Figure 9] 3 is a flowchart showing a speed estimation method according to the first embodiment. [Figure 10] 10A and 10B are block diagrams showing a hardware configuration for realizing the functions of the speed estimation device according to the first embodiment. [Figure 11] FIG. 10 is a block diagram showing an example of the configuration of a target classifying device according to a second embodiment. [Figure 12] 10 is a flowchart showing a speed estimation method according to the second embodiment. [Figure 13] FIG. 10 is a block diagram showing an example of the configuration of a target classifying device according to a third embodiment. [Figure 14] 11 is a flowchart showing a speed estimation method according to the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Embodiment 1 Fig. 1 is a block diagram showing an example of the configuration of a target classification device 1 according to the first embodiment. In Fig. 1, the target classification device 1 is connected to ground station antennas #1A, #2A, and #3A, which receive radio waves from satellites #1, #2, and #3, respectively. In addition to the target classification device 1, Fig. 1 also shows target A, which is the radio wave source and is the classification target. Target A is a radio wave source whose position is unknown.

[0010] The number of ground station antennas provided corresponds to the number of satellites. In Figure 1, three satellites #1, #2, and #3 are provided as satellites, and three ground station antennas #1A, #2A, and #3A are provided as ground station antennas. Satellites #1, #2, and #3 each receive radio waves from target A and transmit the received radio wave signals to ground station antennas #1A, #2A, and #3A, which in turn receive the radio waves that have arrived via satellites #1, #2, and #3, respectively.

[0011] The target classification device 1 includes a speed estimation device 2 and a target classification unit 3. The speed estimation device 2 includes signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, and reception SNR estimation units 10-1, 10-2, and 10-3. These components configure the positioning processing unit. Note that the signal receiving units 4-1, 4-2, and 4-3 may be provided in ground station antennas #1A, #2A, and #3A.

[0012] Radio waves transmitted from target A and arriving via satellites #1, #2, and #3 are received by ground station antennas #1A, #2A, and #3A. The positioning processing unit performs correlation processing between the signals received by ground station antennas #1A, #2A, and #3A, calculates the TDOA (time difference of arrival) and FDOA (frequency difference of arrival) between the received signals based on the results of the correlation processing, and sequentially acquires the control points of target A by estimating the estimated position of target A based on the TDOA and FDOA.

[0013] The positioning processing unit will now be described in detail. The number of signal receiving units provided corresponds to the number of satellites. Figure 1 shows a case where three signal receiving units 4-1, 4-2, and 4-3 are provided as signal receiving units. The signal receiving units 4-1, 4-2 and 4-3 generate analog signals by performing various signal processing such as amplification, band-pass processing (filtering) and frequency conversion on the RF (radio frequency) outputs from the ground station antennas #1A, #2A and #3A.

[0014] These analog signals are complex signals having in-phase and quadrature components. The signal receivers 4-1, 4-2, and 4-3 convert the analog signals into received signals, which are digital complex signals, to obtain a complex signal vector x(t). In the case of FIG. 1, there are three earth station antennas, so the signal receivers 4-1, 4-2, and 4-3 obtain three received signals: complex signal vectors x1(t), x2(t), and x3(t). These three received signals are output to correlation processors 5-1, 5-2, and 5-3, respectively, and then to received SNR estimation units 10-1, 10-2, and 10-3.

[0015] The correlation processors 5-1, 5-2, and 5-3 calculate TDOA and FDOA information by correlation processing between the received signals acquired by the signal receivers 4-1, 4-2, and 4-3, respectively. For example, the correlation processors 5-1, 5-2, and 5-3 calculate TDOA and FDOA information by extracting peak values ​​of a CAF (Cross Ambiguity Function) according to the method described in Non-Patent Document 1 as correlation processing between the complex signal vectors.

[0016] When target A is a radar wave source, there are multiple peak values ​​of CAF, and as a result, multiple pieces of TDOA and FDOA information are calculated. Signals indicating the TDOA and FDOA information calculated by correlation processors 5-1, 5-2, and 5-3 are output to control point calculation units 6-1, 6-2, and 6-3. The following description will be given assuming that target A is a radar wave source.

[0017] The calculated TDOA for each set of satellites #1, #2, and #3 is denoted by τ 12(i) , τ 23(j) and τ 13(k) and FDOA are respectively, f 12(i) , f 23(j) and f 13(k) Here, i, j, and k each represent a positive integer. The number of CAF peaks calculated from the received signals from satellites #1, #2, and #3 is N 12 , N 23 and N 13 Then, i, j, and k are in the range 1≦i≦N. 12 , 1≦j≦N 23 and 1 ≤ k ≤ N 13 The range of TDOAτ 12(i) and FDOAf 12(i) is output to the control point calculation unit 6-1, and TDOAτ 23(j) and FDOAf 23(j) is output to the control point calculation unit 6-2, and TDOAτ 13(k) and FDOAf 13(k) is output to the orientation point calculation unit 6-3.

[0018] The control point calculation units 6-1, 6-2, and 6-3 use the TDOA and FDOA information to solve the simultaneous equations of the following equations (1) to (7) to calculate control points based on the TDOA and FDOA, respectively. In the following equations (1) to (7), the speed of light is c, and the position vectors of satellites #1, #2, and #3 are p s1 , p s2 , p s3 Let the velocity vectors of satellites #1, #2 and #3 be vs1 , v s2 , v s3 Let the radius of the Earth be R when the Earth is a sphere. E Also, the center frequency of the received signal is f0. Specifically, the orientation point calculation unit 6-1 calculates the orientation point p 12(i) The orientation point calculation unit 6-2 calculates the orientation point p 23(j) The orientation point calculation unit 6-3 calculates the orientation point p 13(k) Calculate. After this, the control point p calculated by the control point calculation unit 6-1 12(i) The signal indicating the orientation point p calculated by the orientation point calculation unit 6-2 is output to the orientation point storage unit 7. 23(j) The signal indicating the orientation point p calculated by the orientation point calculation unit 6-3 is output to the orientation point storage unit 7. 13(k) The signal indicating this is output to the orientation point storage unit 7. TIFF0007749882000001.tif107166

[0019] In addition, since the information on the control point of the target A is calculated corresponding to the set of TDOA and FDOA output from the correlation processing units 5-1, 5-2 and 5-3, the control point calculation units 6-1, 6-2 and 6-3 respectively calculate N 12 , N 23 , N 13 Calculate the orientation points. When solving the above simultaneous equations, either a method of finding a solution through iterative calculations such as Newton's method or steepest descent method, or a method of finding the roots of a polynomial, as described in the reference literature, may be used. (References) K C. Ho and Y. T. Chan, “Geolocation of a known altitude object from TDOA and FDOA measurements” in IEEE Transactions on Aerospace and Electronic Systems, vol. 33, no. 3, pp. 770-783, July 1997.

[0020] In the reference point accumulation unit 7, the reference points calculated by the reference point calculation units 6-1, 6-2, and 6-3 are accumulated together as a set. For example, a set of reference points grouped together is p all =[p 12(i) ,p 23(j) ,p 13(k) and is accumulated in the reference point accumulation unit 7.

[0021] The accumulation of reference points in the reference point accumulation unit 7 is controlled by the accumulation time determination unit 8. When the accumulation time determination unit 8 sets the time when the reference point accumulation unit 7 starts acquiring reference point information to 0, it measures the elapsed time t from that point, and determines whether the elapsed time t has reached a preset accumulation time T. When t < T and the elapsed accumulation time t has not reached the accumulation time T, the reference point accumulation unit 7 continues to accumulate p all , creates a new p all-T and holds it in the reference point accumulation unit 7. When t ≥ T and the elapsed accumulation time t has reached the accumulation time T, the accumulation time determination unit 8 outputs the information indicating p all-T held in the reference point accumulation unit 7 to the coordinate conversion unit 9.

[0022] The coordinate conversion unit 9 converts the three-dimensional vector information of each reference point stored in p all-T output from the reference point accumulation unit 7 into information on latitude φ and longitude θ. The information of the reference points coordinate-converted by the coordinate conversion unit 9 is output to the frequency distribution calculation unit 11 as p all-T-latlon .

[0023] The reception SNR estimators 10-1, 10-2, and 10-3 perform Fourier transforms on the complex signal vectors received by the signal receivers 4-1, 4-2, and 4-3, and estimate the SNRs of the received signals based on the differences between the peak values ​​of the frequency spectrum and the noise floor, etc. The SNRs estimated by the reception SNR estimators 10-1, 10-2, and 10-3 are output to an error ellipse axis length theoretical value calculator 14.

[0024] In addition to the positioning processing unit, the speed estimation device 2 includes a frequency distribution calculation unit 11, a control point extraction unit 12, an error ellipse calculation unit 13, an error ellipse axis length theoretical value calculation unit 14, an FDOA movement variance value calculation unit 15, and a target speed component calculation unit 16. These components generate information for estimating the speed of target A.

[0025] The frequency distribution calculation unit 11 calculates the frequency distribution of the control points based on the information of latitude and longitude obtained by the coordinate conversion unit 9. The frequency distribution of the control points is a distribution for evaluating the density of the control points. FIG. 2 is a diagram showing an example of the frequency distribution of the control points of the target A. The frequency distribution calculation unit 11 calculates the frequency distribution of the control points based on the information of latitude and longitude output from the coordinate conversion unit 9. all-T-latlon 2 is created for the above. For example, the frequency distribution calculation unit 11 generates table data in which the direction of latitude φ is divided into M grids and the direction of longitude θ is divided into N grids, and calculates frequency distribution data in which the number of orientation points present in an area B (hereinafter referred to as a cell) of each grid in the table data is associated with the number of orientation points present. The frequency distribution data calculated by the frequency distribution calculation unit 11 is output to the orientation point extraction unit 12.

[0026] The control point extraction unit 12 extracts control points included in the area with the maximum frequency from the frequency distribution calculated by the frequency distribution calculation unit 11. FIG. 3 is a diagram showing an overview of the process of extracting control points from the frequency distribution, and shows frequency distribution data. In FIG. 3, cell C of (Δθ4, Δφ6) in the frequency distribution is the cell where the most control points exist, that is, the cell with the maximum frequency of control points. As shown in FIG. 3, the control point extraction unit 12 extracts control points existing in cell C with the maximum frequency in the frequency distribution. The set of control points extracted from cell C can be divided into three control points calculated for each set of satellites #1, #2, and #3. The control point extraction unit 12 extracts the control points p corresponding to the set of satellites #1, #2, and #3. ext-12 , p ext-23 and p ext-13 from cell C and output to the error ellipse calculation unit 13. Furthermore, the control point extraction unit 12 calculates the average value of these values, p 12 Bar, p 23 Bar and p 13 The bar is calculated and output to the error ellipse calculation unit 13.

[0027] Here, the reason why the orientation point extraction unit 12 extracts the orientation point included in the area with the maximum frequency will be explained. Fig. 4 is a diagram showing information on orientation points stored in the orientation point storage unit 7. When viewed at a single time, it is difficult to determine whether a control point calculated based on a signal acquired by a radar source or the like is derived from target A, which is the true radio wave source, or is an ambiguity. However, as shown in Figure 4, for example, when looking at the accumulated results of control points over multiple time periods, the ambiguity fluctuates in accordance with the movements of satellites #1, #2, and #3, while the true target A actually exists at that location, so the control point appears in the same location regardless of the movements of satellites #1, #2, and #3. Furthermore, even if target A is moving, the speed is sufficiently small compared to the speed of orbiting satellites #1, #2, and #3. As a result, when viewed over multiple time periods, the behavior of the position fluctuation differs depending on whether the control point is derived from target A or an ambiguity, and if it is derived from target A, it exhibits characteristics that are relatively close to a fixed point. In FIG. 4, symbol D indicates a control point derived from target A, and symbol E indicates an ambiguity control point. By using this characteristic, the speed estimation device 2 can extract the control point derived from target A without using azimuth information.

[0028] The error ellipse calculation unit 13 calculates an error ellipse, which is an area where the orientation point extracted from the frequency distribution may exist, for each set of satellites #1, #2, and #3. For example, the error ellipse calculation unit 13 calculates the error ellipse, which is an area where the orientation point extracted from the frequency distribution may exist, for each set of satellites #1, #2, and #3. ext-12 , p ext-23 and p ext-13 Specifically, the error ellipse calculation unit 13 calculates an error covariance matrix R from each orientation point according to the following equations (8), (9), and (10). 12 , R 23 and R 13 In the following formulas (8), (9) and (10), p ext-12 , p ext-23 and p ext-13 The centroids of each of p ext-12 Bar, p ext-23 Bar and p ext-13 Let's call it a bar. TIFF0007749882000002.tif49166

[0029] Figure 5 shows the γ 2 and the probability that the orientation point of target A exists within the error ellipse (hereinafter referred to as the existence probability of the orientation point). 2 is a χ with two degrees of freedom 2 It is determined by a square distribution, and as shown in Figure 5, the probability of existence of each orientation point changes depending on its value.

[0030] Next, the error ellipse calculation unit 13 calculates the error covariance matrix R 12 , R 23 and R 13 Based on the components of the error ellipse, the axis length σ of the error ellipse is calculated according to the following equations (11), (12), (13), (14), (15), (16), (17), (18), and (19). φ12 , σ θ12 , σ φ23 , σ θ23 , σ φ13 and σ θ13 and the slope φ from the origin 12 , φ 23 and φ 13 The axis length parameters of the error ellipse calculated by the error ellipse calculation unit 13 are output to the FDOA moving variance calculation unit 15. Fig. 6 is a diagram showing an error ellipse in which orientation points exist. In Fig. 6, symbols E1, E2, and E3 are error ellipses in which orientation points exist, and the error ellipse calculation unit 13 calculates the error ellipses E1, E2, and E3 using information on the orientation points extracted from the frequency distribution by the orientation point extraction unit 12. TIFF0007749882000003.tif167166

[0031] The error ellipse axis length theoretical value calculation unit 14 is a theoretical value calculation unit that calculates the theoretical value of the axis length of the error ellipse in which the orientation point exists, based on the SNR of the received signal. The axis length of the error ellipse is a parameter that represents the spread of the ellipse. Furthermore, as described in the above-mentioned reference, for example, in accordance with the following equations (20) and (21), the error ellipse axis length theoretical value calculation unit 14 calculates the theoretical value σ of the TDOA variance value using information on the SNR of the received signal. 2 τ and the theoretical value of the dispersion of FDOA, σ 2 f In the following equations (20) and (21), B is the signal bandwidth, and T is the signal observation time. TIFF0007749882000004.tif34166

[0032] The theoretical value σ of the TDOA dispersion calculated by the error ellipse axis length theoretical value calculation unit 14 2 τ and the theoretical value of the dispersion of FDOA, σ 2 f is output to the FDOA moving dispersion value calculation unit 15. When there are a plurality of observed values, the error ellipse axis length theoretical value calculation unit 14 outputs the arithmetic mean value of these values ​​to the FDOA moving variance value calculation unit 15.

[0033] The FDOA movement variance calculation unit 15 is a variance calculation unit that calculates the variance of the FDOA between received signals accompanying the movement of target A based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists. First, the FDOA moving dispersion value calculation unit 15 calculates the parameter of the axis length of the error ellipse calculated by the error ellipse calculation unit 13 and the theoretical value σ of the TDOA dispersion value calculated by the error ellipse axis length theoretical value calculation unit 14. 2 τ and the theoretical value of the dispersion of FDOA, σ 2 f The FDOA variance value that occurs with the movement of target A is estimated using the above. Here, the theoretical value of the TDOA variance value σ 2 τ and the theoretical value of the dispersion of FDOA, σ 2 f and the variance σ in the space of latitude φ and longitude θ 2 φ and σ 2 θ The relationship between these is expressed by the following formula (22): SN is the error covariance matrix in the space of latitude φ and longitude θ. TIFF0007749882000005.tif18166

[0034] In the above formula (22), D is a 2×2 matrix expressed as D=NE, and N and E are expressed by the following formulas (23) and (24), respectively. p represents the gradient at the position vector p. TIFF0007749882000006.tif25166

[0035] In the above equations (23) and (24), each component of p is expressed by the following equation (25) using information on the latitude φ and longitude θ. TIFF0007749882000007.tif20166

[0036] D -1 =D inv Then, the matrix D inv The (a, b) components of D inv (a, b), P in the above formula (22) SN Each component P SN (1,1), P SN (1,2) and P SN (2,2) can be expressed by the following equations (26), (27), and (28). TIFF0007749882000008.tif30166

[0037] When target A is moving, the FDOA variance value includes the variance value σ 2 f-move On the other hand, if the movement of target A is sufficiently small compared to the satellite momentum, the TDOA variance value does not depend on the movement of target A. Taking this into consideration, the error covariance matrix P SN-v (1,1), P SN-v (1,2) and P SN-v (2,2) can be expressed by the following equations (29), (30), and (31). TIFF0007749882000009.tif30166

[0038] By using the above equations (26), (27), (29), and (31), the variance value σ of the FDOA that occurs as the target A moves can be calculated. 2 f-move can be estimated according to the following equation (32): TIFF0007749882000010.tif15166

[0039] The first term of the numerator in the above formula (32), P SN+v (1,1) and the second term, P SN+v (2,2) is calculated based on the axis length of the error ellipse calculated by the error ellipse calculation unit 13. Also, the theoretical error σ in the space of latitude φ and longitude θ calculated based on the information on the SNR of the received signal φ and σ θ Using the above formula (32), the third term in the numerator, -P SN (1,1) and the fourth term, -P SN (2,2) is calculated. If there is multiple SNR information of the received signal, σ φ and σ θ is the average value of the results calculated for each SNR.

[0040] The FDOA moving dispersion value calculation unit 15 calculates the dispersion value σ that occurs in the FDOA of the received signals from the satellite #1 and the satellite #2 as the target A moves. 2 f-move(12) is calculated according to the following formula (33). TIFF0007749882000011.tif18166

[0041] The FDOA moving dispersion value calculation unit 15 calculates the dispersion value σ that occurs in the FDOA associated with the movement of the target A for the received signals from the satellites #2 and #3. 2 f-move(23) Furthermore, the FDOA moving dispersion value calculation unit 15 calculates the dispersion value σ that occurs in the FDOA as the target A moves for the received signals from the satellites #1 and #3. 2 f-move(13) is calculated according to the following formula (35). TIFF0007749882000012.tif32166

[0042] The target velocity component calculation unit 16 calculates the velocity components of the target A in each direction based on the FDOA variance calculated by the FDOA moving variance calculation unit 15. FIG. 7 is a diagram showing the definition of a velocity vector in the Earth's surface coordinate system. In FIG. 7, the velocity components in the north, east, and zenith directions (vertical directions) on the Earth's surface are defined as v N , v E and v U The velocity v in the Earth's surface coordinate system Surf =[v N ,v E ,v U ] and the velocity v in the ECEF coordinate system target =[v x ,v y ,v z ] can be expressed by the following equations (36) and (37) using a transformation matrix B for performing coordinate transformation. TIFF0007749882000013.tif34166

[0043] The difference ΔFDOA in FDOA that occurs as target A moves can be formulated as shown in the following equation (38) for the received signals from satellite #1 and satellite #2. TIFF0007749882000014.tif51166

[0044] The FDOA variance σ occurring with the movement of target A for the received signals from satellites #1 and #2 2 FDOA,mv can be expressed by the following equation (39). The following equation (39) relates to the position of target A and the velocity of target A at a specific time. TIFF0007749882000015.tif48166

[0045] When multiple observations of target A are made, the average position vector of target A during the observation time is p 12 The average of the velocity components in each direction of target A is v N Bar, VE bar and v U In the following equation (40), the average value p of the position vector of target A in the observations at multiple times for satellite #1 and satellite #2, satellite #2 and satellite #3, and satellite #3 and satellite #1 is 12 Bar, p 23 Bar and p 13 The bars are output from the control point extraction unit 12. TIFF0007749882000016.tif21166

[0046] The above formula (40) can be expressed by the following formulas (41) and (42). TIFF0007749882000017.tif40166

[0047] The transformation matrix B is set to B=[b1, b2, b3]. The variance calculated by the FDOA moving variance calculation unit 15 using the above equations (33), (34), and (35) is expressed as σ on the left side of the above equation (40). 2 FDOA,mv If the target A is a bar, the FDOA variance value σ 2 FDOA,mv(12) bar, σ 2 FDOA,mv(23) Bar and σ 2 FDOA,mv(13) Three equations for the bar are obtained: (43), (44) and (45) below. TIFF0007749882000018.tif47166

[0048] The target velocity component calculation unit 16 calculates the variance value σ of the FDOA associated with the movement of the target A calculated by each of the above equations (43), (44), and (45). 2 FDOA,mv(12) bar, σ 2 FDOA,mv(23) Bar and σ 2 FDOA,mv(13) Using the bar, information v about the components of the velocity vector of target A in each direction is calculated according to the following equations (46), (47), and (48).2 N Bar, V 2 E bar and v 2 U Calculate the bar. TIFF0007749882000019.tif48166

[0049] In the above equations (46), (47), and (48), M is a matrix expressed by the following equation (49), and its (a, b) component is M(a, b). The target velocity component calculation unit 16 calculates information v 2 N Bar, V 2 E bar and v 2 U The bar is the average value p of the position vector of target A. 12 Bar, p 23 Bar and p 13 The result is output together with the bar to the target classification unit 3. TIFF0007749882000020.tif24166

[0050] The target classification unit 3 receives information v about the components of the velocity vector of the target A in each direction. 2 N Bar, V 2 E bar and v 2 U The speed of target A is estimated from the bar, and the average value of the position vector of target A, p 12 Bar, p 23 Bar and p 13 The position information of the target A is estimated from the bar. Then, the target classification unit 3 classifies the target A based on the estimated speed information of the target A and the position information of the target A.

[0051] For example, the target classification unit 3 calculates the estimated position p of the target A using the following equation (50): est Calculate the bar. TIFF0007749882000021.tif17166

[0052] The target classification unit 3 calculates the absolute value (speed) v of the speed of target A using the following formula (51). est The bar is calculated. Although the case where the target classification unit 3 calculates the speed v est of target A and calculates the bar has been shown, the speed estimation device 2 may calculate the speed v est of target A and calculate the bar. In this case, the target speed component calculation unit 16 uses the information v 2 N bar, v 2 E bar and v 2 U bar to estimate the speed of target A. TIFF0007749882000022.tif16166

[0053] In FIG. 1, the speed estimation device 2 including the positioning processing unit is shown, but the positioning processing unit may be provided in a positioning device provided separately from the speed estimation device 2. That is, the speed estimation device 2 may be able to acquire information on the reference point from the positioning device, and it is only necessary to include the frequency distribution calculation unit 11, the reference point extraction unit 12, the error ellipse calculation unit 13, the error ellipse axis length theoretical value calculation unit 14, the FDOA movement dispersion value calculation unit 15, and the target speed component calculation unit 16.

[0054] [[ID=2—6]] Next, the target classification method by the target classification device 1 will be described. FIG. 8 is a flowchart showing the target classification method according to the first embodiment. The parameters v0, v1, v2, and v3 shown in FIG. 8 are constants having a magnitude relationship of v0 < v1 < v2 < v3. The target classification unit 3 estimates the estimated position p est bar of target A and the absolute value (speed) v est bar of the speed of target A according to the above formula (50) and the above formula (51) (step ST1).

[0055] Subsequently, the target classification unit 3 compares the speed v est bar of the target with the constant v1 to determine whether v est bar < v1 (step ST2). v estWhen the bar is <v1 (step ST2; YES), the target classification unit 3 estimates the position p of target A est Determine whether the bar exists on land (step ST3). The estimated position p of target A est When the bar does not exist on land (step ST3; NO), the target classification unit 3 classifies target A as a ship (step ST4).

[0056] The estimated position p of target A est When the bar exists on land (step ST3; YES), the target classification unit 3 determines the speed v of the target est By comparing the bar with a constant v0, v est Determine whether the bar <v0 (step ST5). Here, v est When the bar <v0 (step ST5; YES), the target classification unit 3 classifies target A as a fixed station or a vehicle in a stationary state (step ST6). v est The bar <v1, and v est The bar ≥ v0, that is, v0 ≤ v est When the bar <v1 (step ST5; NO), the target classification unit 3 classifies target A as a vehicle (step ST7).

[0057] On the other hand, v est When the bar ≥ v1 (step ST2; NO), the target classification unit 3 determines v1 < v est Determine whether the bar <v2 (step ST8). v1 < v est When the bar <v2 (step ST8; YES), the target classification unit 3 classifies target A as a drone or a rotary-wing aircraft (step ST9).

[0058] v1 < v est When the bar is not <v2 (step ST8; YES), the target classification unit 3 determines v2 < v est Determine whether the bar <v3 (step ST10). v2 < v est When the bar <v3 (step ST10; YES), the target classification unit 3 classifies target A as a civil aircraft (step ST11). v2 < v estWhen it is not bar <v3> (step ST10; NO), the target classification unit 3 classifies that the target A is a military aircraft (step ST12).

[0059] Next, the speed estimation method by the speed estimation device 2 will be described. FIG. 9 is a flowchart showing the speed estimation method according to the first embodiment, and shows a series of operations by the speed estimation device 2. The signal reception units 4-1, 4-2, and 4-3 perform AD conversion processing on the signals received from the satellites #1, #2, and #3 by the ground station antennas #1A, #2A, and #3A, and then acquire complex baseband signals in digital form (step ST1A). Specifically, first, the signal reception units 4-1, 4-2, and 4-3 perform various signal processes such as amplification processing, band-pass processing (filter processing), and frequency conversion processing on the RF (high-frequency) outputs of the ground station antennas #1A, #2A, and #3 to generate analog signals. This analog signal is a complex signal having an in-phase component and a quadrature component. Then, the signal reception units 4-1, 4-2, and 4-3 convert this analog signal into a received signal that is a complex signal in digital form, thereby acquiring a complex signal vector. The signals indicating the complex signal vectors acquired by the signal reception units 4-1, 4-2, and 4-3 are output to the correlation processing units 5-1, 5-2, and 5-3 and the received SNR estimation units 10-1, 10-2, and 10-3.

[0060] Next, the received SNR estimation units 10-1, 10-2, and 10-3 estimate the SNR of the received signals acquired by the signal reception units 4-1, 4-2, and 4-3 (step ST2A). For example, the received SNR estimation units 10-1, 10-2, and 10-3 perform Fourier transform on the complex signal vectors received by the signal reception units 4-1, 4-2, and 4-3, and estimate the SNR of the received signals based on the difference between the peak value of the frequency spectrum and the noise floor, etc. The SNRs respectively estimated by the received SNR estimation units 10-1, 10-2, and 10- are output to the error ellipse axis length theoretical value calculation unit 14.

[0061] The correlation processing units 5-1, 5-2, and 5-3 calculate TDOA and FDOA information by correlation processing between the received signals acquired by the signal receiving units 4-1, 4-2, and 4-3, respectively, and the control point calculation units 6-1, 6-2, and 6-3 calculate control points based on the TDOA and FDOA, respectively, using the TDOA and FDOA information (step ST3A). For example, the correlation processing units 5-1, 5-2, and 5-3 calculate TDOA and FDOA information by extracting peak values ​​of CAF as correlation processing between complex signal vectors. The control point calculation units 6-1, 6-2, and 6-3 use the information on TDOA and FDOA to solve the simultaneous equations of the above formulas (1) to (7), thereby calculating control points based on the TDOA and FDOA, respectively.

[0062] The accumulation time determination unit 8 accumulates the information on the control points calculated by the control point calculation units 6-1, 6-2, and 6-3, respectively, and the SNRs estimated by the reception SNR estimation units 10-1, 10-2, and 10-3, in the control point accumulation unit 7 for a fixed time (accumulation time T) (step ST4A). When the elapsed time t reaches the accumulation time T, the accumulation time determination unit 8 outputs the information on the control points and the SNRs held in the control point accumulation unit 7 to the coordinate conversion unit 9. The coordinate conversion unit 9 converts the three-dimensional vector information of each control point output from the control point accumulation unit 7 into latitude and longitude information. The information on the control points coordinate-converted by the coordinate conversion unit 9 is output to the frequency distribution calculation unit 11.

[0063] The frequency distribution calculation unit 11 calculates the frequency distribution of the control points based on the information of the latitude φ and longitude θ of the control points whose coordinates have been converted by the coordinate conversion unit 9 (step ST5A). The frequency distribution data calculated by the frequency distribution calculation unit 11 is output to the control point extraction unit 12.

[0064] The control point extraction unit 12 extracts control points that exist in the area with the maximum frequency from the frequency distribution calculated by the frequency distribution calculation unit 11 (step ST6A). For example, the control point extraction unit 12 extracts control points corresponding to the set of satellites #1, #2, and #3, and outputs these together with their average values ​​to the error ellipse calculation unit 13.

[0065] The error ellipse calculation unit 13 calculates the center of gravity of the distribution of the control points extracted by the control point extraction unit 12, and calculates three error ellipses, which are areas where these control points may exist, for each pair of satellites #1, #2, and #3 (step ST7A). A signal indicating the error ellipse calculated by the error ellipse calculation unit 13 is output to the FDOA moving variance value calculation unit 15.

[0066] The error ellipse axis length theoretical value calculation unit 14 calculates the theoretical value of the axis length of the error ellipse in which the orientation point exists based on the SNR of the received signal (step ST8A). Information indicating the theoretical value of the axis length of the error ellipse calculated by the error ellipse axis length theoretical value calculation unit 14 is output to the FDOA moving variance value calculation unit 15.

[0067] The FDOA movement variance calculation unit 15 calculates the variance value of the FDOA between the received signals accompanying the movement of target A based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists (step ST9A). The target velocity component calculation unit 16 calculates the velocity components of the target A in each direction based on the FDOA variance calculated by the FDOA moving variance calculation unit 15 (step ST10A). The target classification unit 3 classifies the target A based on the average value of the control points obtained in step ST6A and the speed information of the target A calculated using the speed component of the target A obtained in step ST10A.

[0068] Next, a hardware configuration for realizing the functions of the speed estimation device 2 will be described. The functions of the signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, reception SNR estimators 10-1, 10-2, and 10-3, frequency distribution calculation unit 11, control point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target speed component calculation unit 16 provided in the speed estimation device 2 are realized by processing circuits. That is, the speed estimation device 2 includes a processing circuit for executing the processes from step ST1A to step ST10A shown in FIG. 9. The processing circuit may be dedicated hardware, or may be a CPU (Central Processing Unit) that executes a program stored in memory.

[0069] Fig. 10A is a block diagram showing a hardware configuration for realizing the functions of the speed estimation device 2. Fig. 10B is a block diagram showing a hardware configuration for executing software for realizing the functions of the speed estimation device 2. In Figs. 10A and 10B, input interface 100 is an interface that relays signals that the speed estimation device 2 acquires from ground station antennas #1A, #2A, and #3A. Output interface 101 is an interface that relays information indicating the speed components in each direction of target A that is output from the speed estimation device 2 to the target classification unit 3.

[0070] 10A, the processing circuit 102 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a combination thereof. The functions of the signal receiving units 4-1, 4-2, and 4-3, the correlation processing units 5-1, 5-2, and 5-3, the orientation point calculation units 6-1, 6-2, and 6-3, the orientation point accumulation unit 7, the accumulation time determination unit 8, the coordinate conversion unit 9, the reception SNR estimation units 10-1, 10-2, and 10-3, the frequency distribution calculation unit 11, the orientation point extraction unit 12, the error ellipse calculation unit 13, the error ellipse axis length theoretical value calculation unit 14, the FDOA moving variance value calculation unit 15, and the target speed component calculation unit 16 provided in the speed estimation device 2 may be realized by separate processing circuits, or these functions may be realized together by a single processing circuit.

[0071] 10B, the functions of the signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, orientation point calculation units 6-1, 6-2, and 6-3, orientation point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, reception SNR estimation units 10-1, 10-2, and 10-3, frequency distribution calculation unit 11, orientation point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target speed component calculation unit 16 provided in the speed estimation device 2 are realized by software, firmware, or a combination of software and firmware. The software or firmware is written as a program and stored in the memory 104.

[0072] The processor 103 reads out and executes the program stored in the memory 104, thereby realizing the functions of the signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, reception SNR estimation units 10-1, 10-2, and 10-3, frequency distribution calculation unit 11, control point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target speed component calculation unit 16, which are provided in the speed estimation device 2. For example, the speed estimation device 2 includes a memory 104 for storing a program that, when executed by the processor 103, results in the processing of steps ST1A to ST10A shown in FIG. These programs cause a computer to execute the processing procedures or methods performed by the signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, reception SNR estimation units 10-1, 10-2, and 10-3, frequency distribution calculation unit 11, control point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target velocity component calculation unit 16. The memory 104 may be a computer-readable storage medium storing programs for causing the computer to function as signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, orientation point calculation units 6-1, 6-2, and 6-3, orientation point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, reception SNR estimation units 10-1, 10-2, and 10-3, frequency distribution calculation unit 11, orientation point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target velocity component calculation unit 16.

[0073] Memory 104 may be, for example, a non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically-EPROM) (registered trademark), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a DVD, etc.

[0074] Some of the functions of the signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, reception SNR estimation units 10-1, 10-2, and 10-3, frequency distribution calculation unit 11, control point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target speed component calculation unit 16 provided in the speed estimation device 2 may be realized by dedicated hardware, and the other functions may be realized by software or firmware.

[0075] For example, each function of the signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, and reception SNR estimation units 10-1, 10-2, and 10-3 may be realized by a processing circuit 102 which is dedicated hardware, and each function of the frequency distribution calculation unit 11, control point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target speed component calculation unit 16 may be realized by the processor 103 reading and executing a program stored in the memory 104. In this way, the processing circuit can realize the above functions by hardware, software, firmware, or a combination of these.

[0076] 10B, the speed estimation device 2 is configured using a single processor 103, but is not limited to this. For example, the speed estimation device 2 may be realized using a plurality of processors that operate in cooperation with each other.

[0077] As described above, the speed estimation device 2 according to the first embodiment includes a frequency distribution calculation unit 11 that calculates the frequency distribution of the control points, a control point extraction unit 12 that extracts the control points included in the area where the frequency is maximum from the frequency distribution, an error ellipse calculation unit 13 that calculates an error ellipse, which is an area where the control points extracted from the frequency distribution may exist, for each pair of satellites, an error ellipse axis length theoretical value calculation unit 14 that calculates the theoretical value of the axis length of the error ellipse where the control points exist based on the SNR of the received signal, an FDOA movement variance calculation unit 15 that calculates the variance value of the FDOA between the received signals accompanying the movement of the target A based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse where the control points extracted from the frequency distribution exist, and a target speed component calculation unit 16 that calculates the speed component of the target based on the variance value. Based on the difference between the theoretical value of the axis length of the error ellipse in which the control point exists, estimated based on the SNR of the received signal, and the axis length of the error ellipse in which the control point exists, extracted from the frequency distribution of the control point, the FDOA variance value between the received signals accompanying the movement of target A is calculated, and the speed component of target A is calculated based on this variance value. This allows the speed estimation device 2 to estimate speed information of target A to be used for classifying target A.

[0078] The target classification device 1 according to the first embodiment includes a speed estimation device 2 and a target classification unit 3 that classifies target A based on speed information of target A estimated from the speed component of target A calculated by a target speed component calculation unit 16 and position information of target A. This allows the target classification device 1 to classify target A using the speed information of target A in addition to the position information of target A.

[0079] The speed estimation method according to the first embodiment includes the steps of: step ST5A in which a frequency distribution calculation unit 11 calculates a frequency distribution; step ST6A in which a control point extraction unit 12 extracts a control point included in a region with the highest frequency from the frequency distribution; step ST7A in which an error ellipse calculation unit 13 calculates an error ellipse, which is a region in which the control point extracted from the frequency distribution may exist, for each pair of satellites; step ST8A in which a theoretical error ellipse axis length calculation unit 14 calculates a theoretical value of the axis length of the error ellipse in which the control point exists, based on the signal-to-noise ratio of the received signal; step ST9A in which an FDOA moving variance calculation unit 15 calculates a variance value of the FDOA based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the control point extracted from the frequency distribution exists; and step ST10A in which a target speed component calculation unit 16 calculates a speed component of the target A based on the variance value of the FDOA. By performing this method, the speed estimation device 2 can estimate speed information of the target A to be used for classifying the target A.

[0080] The target classification method according to the first embodiment includes step ST1 in which the speed estimation device 2 calculates the speed components of target A, and steps ST2 to ST12 in which the target classification unit 3 classifies target A based on the speed information of target A estimated from the speed components of target A and the position information of target A. By executing this method, the target classification device 1 can classify target A using the speed information of target A in addition to the position information of target A.

[0081] Embodiment 2 Fig. 11 is a block diagram showing an example of the configuration of a target classification device 1A according to embodiment 2. In Fig. 11, the target classification device 1A is connected to ground station antennas #1A, #2A, and #3A, which receive radio waves from satellites #1, #2, and #3, respectively, in the same way as the target classification device 1. In addition to the target classification device 1A, Fig. 11 also shows target A, which is the source of the radio waves and is the target to be classified.

[0082] The number of ground station antennas provided corresponds to the number of satellites. In Figure 11, three satellites #1, #2, and #3 are provided as satellites, and three ground station antennas #1A, #2A, and #3A are provided as ground station antennas. Satellites #1, #2, and #3 each receive radio waves from target A and transmit the received radio wave signals to ground station antennas #1A, #2A, and #3A, which in turn receive the radio waves that have arrived via satellites #1, #2, and #3, respectively.

[0083] The target classification device 1A includes a speed estimation device 2A and a target classification unit 3A. Like the speed estimation device 2, the speed estimation device 2A includes a positioning processing unit consisting of signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, and reception SNR estimation units 10-1, 10-2, and 10-3. Note that the signal receiving units 4-1, 4-2, and 4-3 may be included in ground station antennas #1A, #2A, and #3A. The operation of the positioning processing unit is the same as in the first embodiment.

[0084] In addition to the positioning processing unit, the speed estimation device 2A also includes a frequency distribution calculation unit 11, a control point extraction unit 12, an error ellipse calculation unit 13, an error ellipse axis length theoretical value calculation unit 14, an FDOA moving variance calculation unit 15, and a target speed calculation unit 17. These components generate information for estimating the speed of target A. The frequency distribution calculation unit 11, the control point extraction unit 12, the error ellipse calculation unit 13, the error ellipse axis length theoretical value calculation unit 14, and the FDOA moving variance calculation unit 15 in the speed estimation device 2A function in the same way as in the speed estimation device 2.

[0085] In the speed estimation device 2 according to the first embodiment, the target speed component calculation unit 16 calculates the speed components of target A in each direction, and then the target classification unit 3 calculates the speed of target A. This has the advantage that the motion information of target A can be obtained three-dimensionally. However, depending on the positional relationship between the satellite and target A, the matrix M expressed by the above equation (49) may become singular, which may cause an error in the calculated speed vector and therefore an error in the speed information used for target classification.

[0086] In contrast, in the speed estimation device 2A, the target speed calculation unit 17 calculates multiple speeds of the target A based on the FDOA variance value calculated by the FDOA moving variance calculation unit 15, and calculates the arithmetic mean of the multiple speeds of the target A as the speed of the target A. This allows the speed estimation device 2A to calculate the speed of the target A more robustly.

[0087] Specifically, the target speed calculation unit 17 calculates the speed information of the target A using each of the above equations (43), (44), and (45), and sets the average value of these to the speed of the target A. When the target A is moving along the ground surface, the vertical velocity component v U is the northward velocity component v N and the eastward velocity component v E In this case, the above equations (43), (44), and (45) can be transformed into the following equations (52), (53), and (54). TIFF0007749882000023.tif30166

[0088] Furthermore, the northward velocity component of target A, v N and the eastward velocity component v E Assuming there is no significant difference between N ≒v E = vbar, the above equations (52), (53) and (54) can be simplified to the following equations (55), (56) and (57). TIFF0007749882000024.tif31166

[0089] By independently using the above equations (55), (56), and (57), the speed v of target A can be calculated. est The bar is expressed by the following equations (58), (59) and (60). The target speed calculation unit 17 calculates the variance value σ of the FDOA between the received signals as the target A moves. 2 F-move-12 , σ 2 F-move-23 and σ 2 F-move-13 By using the above, the speed v of target A can be calculated according to the following equations (58), (59) and (60). est Calculate the bars in three ways. TIFF0007749882000025.tif49166

[0090] The target speed calculation unit 17 calculates the arithmetic mean of the multiple speeds of the target A. For example, the target speed calculation unit 17 calculates the arithmetic mean of the three speeds v of the target A calculated from the above equations (58), (59), and (60) in accordance with the following equation (61): est The arithmetic mean value of the bars is calculated as the final target speed A, v est Calculated as bars. TIFF0007749882000026.tif19166

[0091] By finding the speed of target A from the above equation (61), the noise component can be reduced due to the averaging effect, and the inverse matrix calculation shown in the above equation (49) becomes unnecessary. This makes it possible to avoid cases where the matrix M becomes singular depending on the positional relationship between the target A and the satellite, making it difficult to perform the inverse matrix calculation. This allows the speed estimation device 2A to more robustly calculate the speed of the target A.

[0092] Next, a speed estimation method according to the second embodiment will be described. 12 is a flowchart showing a speed estimation method according to embodiment 2, illustrating a series of operations performed by speed estimation device 2A. The processing from step ST1B to step ST9B in FIG. 12 is similar to the processing from step ST1A to step ST9A in FIG.

[0093] The target speed calculation unit 17 calculates multiple speeds of the target A based on the FDOA variance value calculated by the FDOA moving variance calculation unit 15, and calculates the arithmetic mean of the multiple speeds of the target A as the speed of the target A (step ST10B). Next, the target classification unit 3A calculates the average value p of the control points obtained in step ST6B. est bar and the velocity information v of target A obtained in step ST10B. est For example, the target classification unit 3A executes the target classification method shown in FIG.

[0094] Next, a hardware configuration for realizing the functions of the speed estimation device 2A will be described. The functions of the signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, reception SNR estimation units 10-1, 10-2, and 10-3, frequency distribution calculation unit 11, control point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target speed calculation unit 17 provided in the speed estimation device 2A are realized by processing circuits. That is, the speed estimation device 2A includes a processing circuit for executing the processes from step ST1B to step ST10B shown in FIG. 12. The processing circuit may be dedicated hardware, or may be a CPU that executes a program stored in memory.

[0095] 10B, the speed estimation device 2A is configured using a single processor 103, but is not limited to this. For example, the speed estimation device 2A may be realized using a plurality of processors that operate in cooperation with each other.

[0096] As described above, the speed estimation device 2A according to the second embodiment includes a frequency distribution calculation unit 11 that calculates the frequency distribution of the control points, a control point extraction unit 12 that extracts the control points included in the area where the frequency is maximum from the frequency distribution, an error ellipse calculation unit 13 that calculates an error ellipse, which is an area where the control points extracted from the frequency distribution may exist, for each pair of satellites, an error ellipse axis length theoretical value calculation unit 14 that calculates the theoretical value of the axis length of the error ellipse where the control points exist based on the SNR of the received signal, an FDOA movement variance calculation unit 15 that calculates the variance value of the FDOA between the received signals accompanying the movement of the target A based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse where the control points extracted from the frequency distribution exist, and a target speed calculation unit 17 that calculates multiple speeds of the target A based on the variance value and calculates the arithmetic average of the multiple speeds of the target A as the speed of the target A. The speed estimation device 2A calculates the FDOA variance value between the received signals accompanying the movement of target A based on the difference between the theoretical value of the axis length of the error ellipse in which the control point exists, estimated based on the SNR of the received signal, and the axis length of the error ellipse in which the control point exists, extracted from the frequency distribution of the control point, and calculates the speed of target A based on this variance value. This allows the speed estimation device 2A to estimate speed information of target A to be used for classifying target A. Furthermore, the speed estimation device 2A can calculate the speed of target A more robustly than the speed estimation device 2.

[0097] The target classification device 1A according to the second embodiment includes a speed estimation device 2A and a target classification unit 3A that classifies target A based on speed information of target A estimated from the speed components of target A calculated by a target speed calculation unit 17, and position information of target A. This allows the target classification device 1A to classify target A using the speed information of target A in addition to the position information of target A. Furthermore, since the speed estimation device 2A can calculate the speed of target A more robustly, the target classification device 1A can consequently stably output the classification result of target A.

[0098] The speed estimation method according to the second embodiment includes a step ST5B in which the frequency distribution calculation unit 11 calculates the frequency distribution, a step ST6B in which the control point extraction unit 12 extracts the control points included in the area with the maximum frequency from the frequency distribution, a step ST7B in which the error ellipse calculation unit 13 calculates an error ellipse, which is an area in which the control points extracted from the frequency distribution may exist, for each pair of satellites, a step ST8B in which the error ellipse axis length theoretical value calculation unit 14 calculates the theoretical value of the axis length of the error ellipse in which the control point exists, based on the signal-to-noise ratio of the received signal, a step ST9B in which the FDOA moving variance calculation unit 15 calculates the variance value of the FDOA based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the control point extracted from the frequency distribution exists, and a step ST10B in which the target speed calculation unit 17 calculates a plurality of speeds of the target A based on the variance value of the FDOA, and calculates the arithmetic average of the plurality of speeds of the target A as the speed of the target A. By executing this method, the speed estimation device 2A can estimate speed information of the target A to be used for classifying the target A. Furthermore, the speed estimation device 2A can calculate the speed of the target A more robustly than the speed estimation device 2.

[0099] The target classification method according to the second embodiment includes step ST1 in which the speed estimation device 2A calculates speed information of target A, and steps ST2 to ST12 in which the target classification unit 3A classifies target A based on the speed information of target A and position information of target A. By executing this method, the target classification device 1A can classify target A using the speed information of target A in addition to the position information of target A. Furthermore, since the speed estimation device 2A can calculate the speed of target A more robustly, the target classification device 1A can consequently stably output the classification result of target A.

[0100] Embodiment 3 Fig. 13 is a block diagram showing an example of the configuration of a target classification device 1B according to embodiment 3. In Fig. 11, target classification device 1B is connected to ground station antennas #1A, #2A, and #3A, which receive radio waves from satellites #1, #2, and #3, respectively, similar to target classification device 1. In addition to target classification device 1B, Fig. 13 also shows target A, which is the source of the radio waves and is the target to be classified.

[0101] The number of ground station antennas provided corresponds to the number of satellites. In Figure 13, three satellites #1, #2, and #3 are provided as satellites, and three ground station antennas #1A, #2A, and #3A are provided as ground station antennas. Satellites #1, #2, and #3 each receive radio waves from target A and transmit the received radio wave signals to ground station antennas #1A, #2A, and #3A, which in turn receive the radio waves that have arrived via satellites #1, #2, and #3, respectively.

[0102] The target classification device 1B includes a speed estimation device 2B and a target classification unit 3B. Like the speed estimation device 2, the speed estimation device 2B includes a positioning processing unit consisting of signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, and reception SNR estimation units 10-1, 10-2, and 10-3. Note that the signal receiving units 4-1, 4-2, and 4-3 may be included in ground station antennas #1A, #2A, and #3A. The operation of the positioning processing unit is the same as in the first embodiment.

[0103] In addition to the positioning processing unit, the speed estimation device 2B includes a frequency distribution calculation unit 11, a control point extraction unit 12, an error ellipse calculation unit 13, an error ellipse axis length theoretical value calculation unit 14, an FDOA moving variance calculation unit 15, and a target planar direction velocity component calculation unit 18. These components generate information for estimating the speed of target A. The frequency distribution calculation unit 11, the control point extraction unit 12, the error ellipse calculation unit 13, the error ellipse axis length theoretical value calculation unit 14, and the FDOA moving variance calculation unit 15 in the speed estimation device 2B function in the same way as in the speed estimation device 2.

[0104] In the speed estimation device 2B, the target plane direction velocity component calculation unit 18 calculates the velocity component of the target A in the plane direction based on the FDOA variance value calculated by the FDOA moving variance value calculation unit 15. The velocity component of the target A in the plane direction is the velocity component in the direction of the earth's surface plane, and for example, the velocity component v in the north direction N and the eastward velocity component v E The planar velocity components of target A may be a southerly velocity component and a westerly velocity component. By using the planar velocity components of target A, speed estimation device 2B can more robustly calculate the speed of target A while retaining information on the velocity vector of target A.

[0105] The target plane direction velocity component calculation unit 18 calculates the vertical velocity component v U is the northward velocity component v N and the eastward velocity component v E Under the assumption that the velocity component v in the north direction is sufficiently small compared to N and the eastward velocity component v E Specifically, by using the above equations (43), (44), and (45), the vertical velocity component v U Under the condition that ≒0, the northward velocity component v N and the eastward velocity component v E has three relationships shown in the following equations (62), (63), and (64). TIFF0007749882000027.tif49166

[0106] By using the above equations (62), (63) and (64), the northward velocity component v N and the eastward velocity component v E can be expressed as the arithmetic mean shown in the following equations (65) and (66). The target plane direction velocity component calculation unit 18 calculates the north direction velocity component v N and the eastward velocity component v E Calculate. TIFF0007749882000028.tif28166

[0107] Depending on the positional relationship between the satellite and target A, if the denominator terms in the above equations (55), (56), and (57) become extremely small, that is, if the conditions shown in the following equations (67), (68), and (69) hold for a certain small constant ε, then the terms are omitted and calculation averaging is performed. This gives us the calculated v N 2 and v E 2 Since it is possible to exclude those that take singular values ​​from the vectors, the speed estimation device 2B can determine the speed of the target A more robustly than the speed estimation device 2. Furthermore, the speed estimation device 2B can obtain more information regarding the movement of the target A than the speed estimation device 2A. TIFF0007749882000029.tif34166

[0108] Next, a speed estimation method according to the third embodiment will be described. 14 is a flowchart showing a speed estimation method according to embodiment 3, illustrating a series of operations performed by speed estimation device 2 B. The processes from step ST1C to step ST9C in FIG. 14 are similar to the processes from step ST1A to step ST9A in FIG.

[0109] The target planar direction velocity component calculation unit 18 calculates the velocity component in the planar direction of the target A based on the FDOA variance value calculated by the FDOA moving variance value calculation unit 15 (step ST10C). The target classification unit 3B calculates the average value p of the control points obtained in step ST6C. est The north direction velocity component v, which is the horizontal velocity component of target A obtained in step ST10C. N and the eastward velocity component v E For example, the target A is classified by the target classification unit 3B executing the target classification method shown in FIG.

[0110] Next, a hardware configuration for realizing the functions of the speed estimation device 2B will be described. The functions of the signal receiving units 4-1, 4-2, and 4-3, correlation processing units 5-1, 5-2, and 5-3, control point calculation units 6-1, 6-2, and 6-3, control point accumulation unit 7, accumulation time determination unit 8, coordinate conversion unit 9, reception SNR estimators 10-1, 10-2, and 10-3, frequency distribution calculation unit 11, control point extraction unit 12, error ellipse calculation unit 13, error ellipse axis length theoretical value calculation unit 14, FDOA moving variance value calculation unit 15, and target plane direction velocity component calculation unit 18 included in the speed estimation device 2B are realized by processing circuits. That is, the speed estimation device 2B includes a processing circuit for executing the processes from step ST1C to step ST10C shown in FIG. 14. The processing circuit may be dedicated hardware or a CPU that executes a program stored in memory.

[0111] 10B, the speed estimation device 2B is configured using a single processor 103, but is not limited to this. For example, the speed estimation device 2B may be realized using a plurality of processors that operate in cooperation with each other.

[0112] As described above, the speed estimation device 2B according to the third embodiment includes a frequency distribution calculation unit 11 that calculates the frequency distribution of the control points, a control point extraction unit 12 that extracts the control points included in the region with the maximum frequency from the frequency distribution, an error ellipse calculation unit 13 that calculates, for each pair of satellites, an error ellipse which is a region in which the control points extracted from the frequency distribution may exist, an error ellipse axis length theoretical value calculation unit 14 that calculates the theoretical value of the axis length of the error ellipse in which the control points exist based on the SNR of the received signal, an FDOA movement variance value calculation unit 15 that calculates the variance value of the FDOA between the received signals accompanying the movement of the target A based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the control points extracted from the frequency distribution exist, and a target planar direction velocity component calculation unit 18 that calculates the velocity component in the planar direction of the target A based on the variance value. The FDOA variance value between the received signals accompanying the movement of target A is calculated based on the difference between the theoretical value of the axis length of the error ellipse in which the control point exists, estimated based on the SNR of the received signal, and the axis length of the error ellipse in which the control point exists, extracted from the frequency distribution of the control point, and the speed component of target A in the planar direction is calculated based on the FDOA variance value. This allows the speed estimation device 2B to estimate speed information of target A to be used for classifying target A. Furthermore, speed estimation device 2B can robustly calculate the magnitude of the velocity components of target A in the north-south and east-west directions with respect to the positional relationship between the satellite and target A. In other words, speed estimation device 2B can estimate the velocity of target A more robustly than speed estimation device 2, and can obtain more information regarding the movement of target A than speed estimation device 2A.

[0113] The target classification device 1B according to the third embodiment includes a speed estimation device 2B and a target classification unit 3 that classifies target A based on the planar direction velocity component information of target A calculated by a target planar direction velocity component calculation unit 18 and the position information of target A. As a result, the target classification device 1B can classify target A using the speed information of target A in addition to the position information of target A. Furthermore, since the speed estimation device 2B can calculate the speed of the target A more robustly, the target classification device 1B can consequently output the classification result of the target A stably.

[0114] The speed estimation method according to the third embodiment includes a step ST5C in which the frequency distribution calculation unit 11 calculates the frequency distribution, a step ST6C in which the control point extraction unit 12 extracts the control points included in the area with the maximum frequency from the frequency distribution, a step ST7C in which the error ellipse calculation unit 13 calculates an error ellipse, which is an area in which the control points extracted from the frequency distribution may exist, for each pair of satellites, a step ST8C in which the error ellipse axis length theoretical value calculation unit 14 calculates the theoretical value of the axis length of the error ellipse in which the control point exists, based on the signal-to-noise ratio of the received signal, a step ST9C in which the FDOA moving variance value calculation unit 15 calculates the variance value of the FDOA based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the control point extracted from the frequency distribution exists, and a step ST10C in which the target planar direction velocity component calculation unit 18 calculates the velocity component in the planar direction of the target A based on the variance value of the FDOA. By executing this method, the speed estimation device 2B can estimate speed information of the target A to be used for classifying the target A. Furthermore, the speed estimation device 2B can estimate the speed of the target A more robustly than the speed estimation device 2, and can obtain more information regarding the movement of the target A than the speed estimation device 2A.

[0115] The target classification method according to the third embodiment includes step ST1 in which the speed estimation device 2B calculates speed component information of the target A in a planar direction, and steps ST2 to ST12 in which the target classification unit 3B classifies the target A based on the speed component information of the target A in the planar direction and position information of the target A. By executing this method, the target classification device 1B can classify the target A using the speed information of the target A in addition to the position information of the target A. Furthermore, since the speed estimation device 2B can calculate the speed of the target A more robustly, the target classification device 1B can consequently output the classification result of the target A stably.

[0116] It is possible to combine the embodiments, modify any of the components of the embodiments, or omit any of the components of the embodiments. [Industrial Applicability]

[0117] A speed estimation device according to the present disclosure can be used, for example, in a monitoring system using a satellite constellation. [Explanation of symbols]

[0118] 1, 1A, 1B Target classification device, 2, 2A, 2B Speed ​​estimation device, 3, 3A, 3B Target classification unit, 4-1 to 4-3 Signal receiving unit, 5-1 to 5-3 Correlation processing unit, 6-1 to 6-3 Control point calculation unit, 7 Control point accumulation unit, 8 Accumulation time determination unit, 9 Coordinate conversion unit, 10-1 to 10-3 Received SNR estimation unit, 11 Frequency distribution calculation unit, 12 Control point extraction unit, 13 Error ellipse calculation unit, 14 Error ellipse axis length theoretical value calculation unit, 15 FDOA movement variance value calculation unit, 16 Target velocity component calculation unit, 17 Target speed calculation unit, 18 Target plane direction velocity component calculation unit, 100 Input interface, 101 Output interface, 102 Processing circuit, 103 Processor, 104 Memory.

Claims

1. A speed estimation device that receives radio waves transmitted from a target that is a radio wave source and arrives via a plurality of satellites, and sequentially acquires a control point that is an estimated position of the target, the control point being estimated based on the arrival time difference and arrival frequency difference between the received signals obtained by correlation processing between the received signals, a frequency distribution calculation unit that calculates a frequency distribution of the control points that have been converted into latitude and longitude coordinates; a control point extraction unit that extracts a control point that exists in an area where the frequency is maximum from the frequency distribution; an error ellipse calculation unit that calculates an error ellipse, which is an area where the orientation point extracted from the frequency distribution may exist, for each pair of satellites; a theoretical value calculation unit that calculates a theoretical value of the axis length of an error ellipse in which the orientation point exists based on the signal-to-noise ratio of the received signal; a variance value calculation unit that calculates a variance value of the arrival frequency difference between the received signals accompanying movement of the target based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists; a target velocity component calculation unit that calculates a velocity component of the target based on the variance value.

2. A speed estimation device that receives radio waves transmitted from a target that is a radio wave source and arrives via a plurality of satellites, and sequentially acquires a control point that is an estimated position of the target, the control point being estimated based on the arrival time difference and arrival frequency difference between the received signals obtained by correlation processing between the received signals, a frequency distribution calculation unit that calculates a frequency distribution of the control points that have been converted into latitude and longitude coordinates; a control point extraction unit that extracts a control point that exists in an area where the frequency is maximum from the frequency distribution; an error ellipse calculation unit that calculates an error ellipse, which is an area where the orientation point extracted from the frequency distribution may exist, for each pair of satellites; a theoretical value calculation unit that calculates a theoretical value of the axis length of an error ellipse in which the orientation point exists based on the signal-to-noise ratio of the received signal; a variance value calculation unit that calculates a variance value of the arrival frequency difference between the received signals accompanying movement of the target based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists; a target speed calculation unit that calculates a plurality of speeds of the target based on the variance value and calculates an arithmetic average of the plurality of speeds of the target as the speed of the target.

3. A speed estimation device that receives radio waves transmitted from a target that is a radio wave source and arrives via a plurality of satellites, and sequentially acquires a control point that is an estimated position of the target, the control point being estimated based on the arrival time difference and arrival frequency difference between the received signals obtained by correlation processing between the received signals, a frequency distribution calculation unit that calculates a frequency distribution of the control points that have been converted into latitude and longitude coordinates; a control point extraction unit that extracts a control point that exists in an area where the frequency is maximum from the frequency distribution; an error ellipse calculation unit that calculates an error ellipse, which is an area where the orientation point extracted from the frequency distribution may exist, for each pair of satellites; a theoretical value calculation unit that calculates a theoretical value of the axis length of an error ellipse in which the orientation point exists based on the signal-to-noise ratio of the received signal; a variance value calculation unit that calculates a variance value of the arrival frequency difference between the received signals accompanying movement of the target based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists; a target planar direction velocity component calculation unit that calculates a velocity component in a planar direction of the target based on the variance value.

4. The speed estimation device according to claim 1; a target classification unit that classifies the target based on speed information of the target estimated from the velocity component of the target calculated by the target velocity component calculation unit and position information of the target.

5. The speed estimation device according to claim 2; a target classification unit that classifies the target based on the speed information of the target calculated by the target speed calculation unit and position information of the target.

6. A speed estimation device according to claim 3; a target classification unit that classifies the target based on the velocity component information in the planar direction of the target calculated by the target planar direction velocity component calculation unit and position information of the target.

7. A speed estimation method executed by the speed estimation device according to claim 1, comprising: a step in which the frequency distribution calculation unit calculates the frequency distribution; a step in which the orientation point extraction unit extracts orientation points that exist in an area with a maximum frequency from the frequency distribution; a step in which the error ellipse calculation unit calculates an error ellipse, which is an area where the orientation point extracted from the frequency distribution may exist, for each pair of satellites; The theoretical value calculation unit calculates a theoretical value of an axis length of an error ellipse in which the orientation point exists based on the signal-to-noise ratio of the received signal; The variance value calculation unit calculates the variance value based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists; a step in which the target velocity component calculation unit calculates a velocity component of the target based on the variance value.

8. A speed estimation method executed by the speed estimation device according to claim 2, comprising: a step in which the frequency distribution calculation unit calculates the frequency distribution; a step in which the orientation point extraction unit extracts orientation points that exist in an area with a maximum frequency from the frequency distribution; a step in which the error ellipse calculation unit calculates an error ellipse, which is an area where the orientation point extracted from the frequency distribution may exist, for each pair of satellites; The theoretical value calculation unit calculates a theoretical value of an axis length of an error ellipse in which the orientation point exists based on the signal-to-noise ratio of the received signal; The variance value calculation unit calculates the variance value based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists; the target speed calculation unit calculates a plurality of speeds of the target based on the variance value, and calculates an arithmetic average of the plurality of speeds of the target as the speed of the target.

9. A speed estimation method executed by the speed estimation device according to claim 3, comprising: a step in which the frequency distribution calculation unit calculates the frequency distribution; a step in which the orientation point extraction unit extracts orientation points that exist in an area with a maximum frequency from the frequency distribution; a step in which the error ellipse calculation unit calculates an error ellipse, which is an area where the orientation point extracted from the frequency distribution may exist, for each pair of satellites; The theoretical value calculation unit calculates a theoretical value of an axis length of an error ellipse in which the orientation point exists based on the signal-to-noise ratio of the received signal; The variance value calculation unit calculates the variance value based on the difference between the theoretical value of the axis length of the error ellipse and the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists; a step in which the target planar direction velocity component calculation unit calculates a planar direction velocity component of the target based on the variance value.

10. A target classification method performed by the target classification device of claim 4, comprising: a step of calculating a velocity component of the target by the velocity estimation device according to claim 1; a step in which the target classification unit classifies the target based on speed information of the target estimated from the velocity component of the target and position information of the target.

11. A target classification method performed by the target classification device of claim 5, comprising: a step of calculating speed information of the target by the speed estimation device according to claim 2; a step in which the target classification unit classifies the target based on speed information of the target and position information of the target.

12. A target classification method performed by the target classification device of claim 6, comprising: a step of calculating velocity component information in a planar direction of the target by the velocity estimation device according to claim 3; a step in which the target classification unit classifies the target based on velocity component information in a planar direction of the target and position information of the target.

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