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

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

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

[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 the 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.

[0003] d. p. Haworth, “Interference localization for eutelsat satellites-the first European transmitter location system,” International journal of satellite communications, vol. 15, 155-183 (1997).

[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.

[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, and 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 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 velocity component calculation unit that calculates a velocity component of the target based on the variance value.

[0007] According to the present disclosure, a control point included in an area with the maximum frequency is extracted from the frequency distribution of the control points of the coordinate-transformed radio wave source, a variance value of the FDOA between 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 point extracted from the frequency distribution exists and the theoretical value of the axis length of the error ellipse calculated based on the signal-to-noise ratio of the received signal, and a velocity component of the target is calculated based on this variance value. In this way, the speed estimation device according to the present disclosure can estimate speed information of the target to be used for target classification.

[0008] FIG. 1 is a block diagram showing an example of the configuration of a target classification device according to embodiment 1. FIG. 2 is a diagram showing an example of a frequency distribution of target control points. FIG. 3 is a diagram showing an outline of a process for extracting control points from the frequency distribution. FIG. 4 is a diagram showing information of control points stored in a control point storage unit. ２and the probability that the target control point exists within the error ellipse. FIG. 10A is a diagram showing the relationship between the value of and the probability that the target control point exists within the error ellipse. FIG. 10B is a diagram showing the error ellipse in which the control point exists. FIG. 10C is a diagram showing the definition of a velocity vector in the Earth's surface coordinate system. FIG. 10D is a flowchart showing a target classification method according to embodiment 1. FIG. 10E is a flowchart showing a speed estimation method according to embodiment 1. FIG. 10F is a block diagram showing a hardware configuration that realizes the functions of the speed estimation device according to embodiment 1. FIG. 10G is a block diagram showing an example configuration of a target classification device according to embodiment 2. FIG. 10H is a flowchart showing a speed estimation method according to embodiment 2. FIG. 10H is a block diagram showing an example configuration of a target classification device according to embodiment 3. FIG. 10I is a flowchart showing a speed estimation method according to embodiment 3.

[0009] Embodiment 1. Fig. 1 is a block diagram showing an example of the configuration of a target classification device 1 according to embodiment 1. 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 earth station antennas provided corresponds to the number of satellites. In Fig. 1, three satellites #1, #2, and #3 are provided as satellites, and three earth station antennas #1A, #2A, and #3A are provided as earth station antennas. Satellites #1, #2, and #3 each receive radio waves from target A and transmit the received radio wave signals to earth station antennas #1A, #2A, and #3A. Earth station antennas #1A, #2A, and #3A receive radio waves that arrive 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 make up the positioning processing unit. Note that the signal receiving units 4-1, 4-2, and 4-3 may be provided in the 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 estimates the control point, which is the estimated position of target A, based on the TDOA and FDOA, thereby sequentially acquiring the control point of target A.

[0013] The positioning processing unit will be described in detail. The number of signal receiving units provided corresponds to the number of satellites. FIG. 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 perform various signal processing such as amplification, band-pass filtering, and frequency conversion on the RF (radio frequency) output from the ground station antennas #1A, #2A, and #3A to generate analog signals.

[0014] These analog signals are complex signals having an in-phase component and a quadrature component. Then, the signal receivers 4-1, 4-2, and 4-3 convert the analog signals into received signals, which are complex signals in digital format, to obtain the complex signal vector x(t). In the case of FIG. 1, since there are three earth station antennas, the signal receivers 4-1, 4-2, and 4-3 obtain the complex signal vector x(t). １ (t), x ２ (t) and x ３A total of three received signals (t) are obtained. These three received signals are output to correlation processing units 5-1, 5-2 and 5-3, and then output to reception SNR estimation units 10-1, 10-2 and 10-3, respectively.

[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 the correlation processing between the complex signal vectors.

[0016] If target A is a radar wave source, there will be multiple CAF peak values, and as a result, multiple pieces of TDOA and FDOA information will be 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 expressed as τ １２（ｉ） , τ ２３（ｊ） and τ １３（ｋ） and FDOA is respectively １２（ｉ） , f ２３（ｊ） and f １３（ｋ） Here, i, j, and k each represent a positive integer. The number of peaks of the CAF calculated from the received signals between satellites #1, #2, and #3 is N １２ , N ２３ and N １３ Then, i, j, and k are in the range of 1≦i≦N. １２ , 1≦j≦N ２３ and 1≦k≦N １３ The range of TDOAτ is met. １２（ｉ） and FDOAf １２（ｉ） is output to the orientation point calculation unit 6-1, and TDOAτ ２３（ｊ） and FDOAf ２３（ｊ）is output to the orientation 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 v ｓ１ , v ｓ２ , v ｓ３ Let the radius of the Earth be R when the Earth is a sphere. Ｅ The center frequency of the received signal is f ０ 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） After that, the orientation point p calculated by the orientation point calculation unit 6-1 is calculated. 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 the above is output to the orientation point storage unit 7.

[0019] Since the information on the orientation 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 orientation point calculation units 6-1, 6-2, and 6-3 respectively calculate N １２ , N ２３ , N １３The above simultaneous equations are solved by calculating the number of orientation points. Either of the methods for finding a solution through iterative calculations, such as Newton's method or steepest descent method, or the method for finding the roots of a polynomial, as described in reference literature, may be used. (Reference) K. C. Ho and Y. T. Chan, "Gelocation 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] The orientation points calculated by the orientation point calculation units 6-1, 6-2, and 6-3 are collected into a single set and stored in the orientation point storage unit 7. For example, the collected set of orientation points is ａｌｌ = [p １２（ｉ） , p ２３（ｊ） , p １３（ｋ） ] and stored in the orientation point storage unit 7.

[0021] The accumulation of the orientation points in the orientation point accumulation unit 7 is controlled by an accumulation time determination unit 8. The accumulation time determination unit 8 measures the elapsed time t from the time when the orientation point accumulation unit 7 starts to acquire the information of the orientation points, assuming that this time is 0, and determines whether the elapsed time t has reached a preset accumulation time T. If t<T and the elapsed time t of accumulation has not reached the accumulation time T, the accumulation time determination unit 8 determines whether the orientation point accumulation unit 7 has stored the information of the orientation points. ａｌｌ Continue accumulating new p ａｌｌ－Ｔ and stores it in the orientation point storage unit 7. When t≧T and the elapsed time of storage t reaches the storage time T, the storage time determination unit 8 creates p stored in the orientation point storage unit 7. ａｌｌ－Ｔ The coordinate conversion unit 9 outputs information indicating the above.

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

[0023] The reception SNR estimation units 10-1, 10-2, and 10-3 perform a 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 signal based on the difference between the peak value of the frequency spectrum and the noise floor, etc. The SNRs estimated by the reception SNR estimation units 10-1, 10-2, and 10-3, respectively, are output to an error ellipse axis length theoretical value calculation unit 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, a theoretical error ellipse axis length calculation unit 14, an FDOA moving variance 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 latitude and longitude information 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 target A. The frequency distribution calculation unit 11 creates the frequency distribution shown in FIG. 2 for the pall-T-latlon output from the coordinate conversion unit 9. 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 control points present in area B (hereinafter referred to as cells) of each grid in the table data is associated with the number of control points present. The frequency distribution data calculated by the frequency distribution calculation unit 11 is output to the control point extraction unit 12.

[0026] The orientation point extraction unit 12 extracts orientation 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 orientation points from the frequency distribution, and shows frequency distribution data. In FIG. 3, the (Δθ ４ , Δφ ６) is the cell in which the most control points exist, that is, the cell with the highest frequency of control points. As shown in FIG. 3, the control point extraction unit 12 extracts the control points existing in cell C, which has 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 control point extraction unit 12 extracts the control point included in the region with the highest frequency will be explained. FIG. 4 is a diagram showing the information of control points accumulated in the control point accumulation 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 wave source or the like originates from target A, which is the true radio wave source, or is an ambiguity. However, as shown in FIG. 4, for example, when the accumulation results of control points over multiple time periods are viewed, the ambiguity fluctuates in accordance with the movement 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 movement of satellites #1, #2, and #3. Furthermore, even if target A is moving, the speed is sufficiently small compared to the orbiting satellites #1, #2, and #3. As a result, when viewed over multiple time periods, the behavior of the position fluctuation of the control point differs depending on whether it originates from target A or is an ambiguity. If it originates from target A, it exhibits characteristics that are relatively close to a fixed point. 4, the reference character D indicates a control point derived from the target A, and the reference character E indicates a control point of the ambiguity. By using this characteristic, the speed estimation device 2 can extract the control point derived from the target A without using the direction 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 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. 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 in accordance with 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 centers of gravity of each of ｅｘｔ－１２ Bar, p ｅｘｔ－２３ Bar and p ｅｘｔ－１３ Let's call it a bar.

[0029] FIG. 5 shows the ２ 1 is a diagram showing the relationship between the value of γ 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 FIG. 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 １３The 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.

[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 document, for example, the error ellipse axis length theoretical value calculation unit 14 calculates the theoretical value σ of the variance of the TDOA using information on the SNR of the received signal according to the following equations (20) and (21): ２ τ and the theoretical value of the variance of FDOA, σ ２ ｆ In the following equations (20) and (21), B is the signal bandwidth, and T is the signal observation time.

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

[0033] The FDOA moving variance calculation unit 15 is a variance calculation unit that calculates the variance 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 orientation point extracted from the frequency distribution exists. First, the FDOA moving variance calculation unit 15 calculates the variance 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 calculated by the error ellipse calculation unit 13 and the theoretical value σ of the variance of the TDOA calculated by the error ellipse axis length theoretical value calculation unit 14. ２ τand the theoretical value of the variance of FDOA, σ ２ ｆ The variance value of the FDOA that occurs with the movement of the target A is estimated using the above equation. Here, the theoretical value of the variance value of the TDOA, σ ２ τ and the theoretical value of the variance 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 P ＳＮ is the error covariance matrix in the space of latitude φ and longitude θ.

[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 in the position vector p.

[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.

[0036] D －１ =D ｉｎｖ Let 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).

[0037] When target A is moving, the variance of the FDOA includes the variance σ ２ ｆ－ｍｏｖｅ On the other hand, if the amount of movement of target A is sufficiently small compared to the satellite momentum, the variance value of TDOA 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).

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

[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 of the SNR of the received signal is φ and σ θ Using the above formula (32), the third term of the numerator, −P ＳＮ (1,1) and the fourth term -P ＳＮ (2, 2) is calculated. When there is a plurality of pieces of information on the SNR 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 occurring in the FDOA of the received signals from the satellites #1 and #2 as the target A moves. ２ f-move(12) is calculated according to the following formula (33).

[0041] The FDOA moving dispersion value calculation unit 15 calculates the dispersion value σ occurring in the FDOA of the received signals from the satellites #2 and #3 as the target A moves. ２ 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).

[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. Figure 7 is a diagram showing the definition of a velocity vector in the Earth's surface coordinate system. In Figure 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 in the Earth's surface coordinate system is v 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.

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

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

[0045] When multiple targets A are observed, the average position vector of target A during the observation time is p １２ bar, and the average of the velocity components in each direction of target A is v Ｎ Bar, V Ｅ Bar and v Ｕ In the following equation (40), the average value p of the position vector of target A in the observations of satellites #1 and #2, satellites #2 and #3, and satellites #3 and #1 at multiple times is １２ Bar, p２３ Bar and p １３ The bar is output from the orientation point extraction unit 12 .

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

[0047] The transformation matrix B is defined as B = [b １ , b ２ , b ３ 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 When the target A moves, the variance value σ of the FDOA is ２ FDOA, mv (12) bar, σ ２ FDOA, mv(23) bar and σ ２ Three equations for FDOA,mv(13) are obtained: (43), (44) and (45) below.

[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 Using FDOA, mv(13) bar, information v about the components of each direction of the velocity vector of target A is obtained according to the following equations (46), (47), and (48). ２ Ｎ Bar, V ２ Ｅ Bar and v ２ Ｕ Calculate the bar.

[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 ＥBar 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.

[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 p of the position vector of target A is calculated. １２ Bar, p ２３ Bar and p １３ The position information of target A is estimated from the bar. Then, the target classification unit 3 classifies target A based on the estimated speed information of target A and the position information of 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.

[0052] The target classification unit 3 calculates the absolute value (speed) v of the velocity of the target A using the following equation (51): ｅｓｔ The target classification unit 3 calculates the speed v ｅｓｔ The example shows a case where the speed estimation device 2 calculates the speed v ｅｓｔ In this case, the target velocity component calculation unit 16 may calculate the information v ２ Ｎ Bar, V ２ Ｅ Bar and v ２ Ｕ The speed of target A is estimated from the bar.

[0053] 1 shows the speed estimation device 2 including a positioning processing unit, the positioning processing unit may be included in a positioning device provided separately from the speed estimation device 2. That is, the speed estimation device 2 is required to be able to acquire control point information from the positioning device, and to include 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 value calculation unit 15, and a target speed component calculation unit 16.

[0054] Next, a target classification method using the target classification device 1 will be described. FIG. 8 is a flowchart showing the target classification method according to the first embodiment. ０ , v １ , v ２ and v ３ , v ０ <v １ <v ２ <v ３ The target classifier 3 calculates the estimated position p of target A according to the above formula (50) and formula (51). ｅｓｔ Absolute value (speed) of the speed of the bar and target A v ｅｓｔ The bar is estimated (step ST1).

[0055] Next, the target classification unit 3 calculates the target speed v ｅｓｔ bar and constant v １ By comparing with v ｅｓｔ Bar < v １ It is determined whether or not (step ST2). ｅｓｔ Bar < v １ If so (step ST2; YES), the target classifying unit 3 determines the estimated position p ｅｓｔ It is determined whether the bar is present on land (step ST3). ｅｓｔ If the bar does not exist on land (step ST3; NO), the target classification unit 3 classifies target A as a ship (step ST4).

[0056] Estimated position p of target A ｅｓｔ If the bar is on land (step ST3; YES), the target classification unit 3 calculates the speed of the target v ｅｓｔ bar and constant v ０ By comparing with vｅｓｔ Bar < v ０ It is determined whether or not v ｅｓｔ Bar < v ０ If so (step ST5; YES), the target classification unit 3 classifies the target A as a fixed station or a stationary vehicle (step ST6). ｅｓｔ Bar < v １ and v ｅｓｔ Bar ≧ v ０ That is, v ０ ≦v ｅｓｔ Bar < v １ If so (step ST5; NO), the target classification unit 3 classifies the target A as a vehicle (step ST7).

[0057] On the other hand, v ｅｓｔ Bar ≧ v １ If so (step ST2; NO), the target classification unit 3 １ <v ｅｓｔ Bar < v ２ It is determined whether or not (step ST8). １ <v ｅｓｔ Bar < v ２ If so (step ST8; YES), the target classification unit 3 classifies target A as an unmanned aircraft or a rotary-wing aircraft (step ST9).

[0058] v １ <v ｅｓｔ Bar < v ２ If not (step ST8; YES), the target classifying unit 3 ２ <v ｅｓｔ Bar < v ３ It is determined whether or not (step ST10). ２ <v ｅｓｔ Bar < v ３ If so (step ST10; YES), the target classification unit 3 classifies target A as a civil aircraft (step ST11). ２ <v ｅｓｔ Bar < v ３ If not (step ST10; NO), the target classification unit 3 classifies target A as a military aircraft (step ST12).

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

[0060] Next, the reception SNR estimators 10-1, 10-2, and 10-3 estimate the SNRs of the received signals acquired by the signal receivers 4-1, 4-2, and 4-3 (step ST2A). For example, the reception SNR estimators 10-1, 10-2, and 10-3 Fourier transform 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 difference between the peak value 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 the error ellipse axis length theoretical value calculator 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 orientation point calculation units 6-1, 6-2 and 6-3 calculate orientation 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 a correlation processing between complex signal vectors. The orientation point calculation units 6-1, 6-2 and 6-3 use the TDOA and FDOA information to calculate orientation points based on the TDOA and FDOA, respectively, by solving the simultaneous equations of the above formulas (1) to (7).

[0062] The accumulation time determination unit 8 accumulates the information on the orientation points calculated by the orientation 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, respectively, in the orientation 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 orientation points and the SNRs held in the orientation point accumulation unit 7 to the coordinate conversion unit 9. The coordinate conversion unit 9 converts the three-dimensional vector information of each orientation point output from the orientation point accumulation unit 7 into latitude and longitude information. The information on the orientation 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 point based on the information of the latitude φ and longitude θ of the control point that has been coordinate-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 set 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 dispersion value calculation unit 15.

[0067] The FDOA moving variance calculation unit 15 calculates the variance 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 target A in each direction based on the variance of the FDOA calculated by the FDOA moving variance calculation unit 15 (step ST10A). The target classification unit 3 classifies target A based on the average value of the orientation points calculated in step ST6A and the speed information of target A calculated using the velocity components of target A calculated 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, 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, theoretical error ellipse axis length calculation unit 14, FDOA moving variance 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, an input interface 100 is an interface that relays signals that the speed estimation device 2 acquires from ground station antennas #1A, #2A, and #3A. An 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 classifier 3.

[0070] When the processing circuit is the dedicated hardware processing circuit 102 shown in FIG. 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, correlation processing units 5-1, 5-2 and 5-3, orientation point calculation units 6-1, 6-2 and 6-3, orientation point storage unit 7, storage 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 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, 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, 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, orientation point calculation units 6-1, 6-2, and 6-3, orientation point storage unit 7, storage 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. The memory 104 may be a computer-readable storage medium that stores a program 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] The memory 104 may be, for example, a non-volatile or volatile semiconductor memory such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Only Memory), or an EEPROM (Electrically-EPROM) (registered trademark), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, or a DVD.

[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, orientation point calculation units 6-1, 6-2, and 6-3, orientation point storage unit 7, storage 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 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, 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, and reception SNR estimation units 10-1, 10-2, and 10-3 is realized by a processing circuit 102 which is dedicated hardware, and each function of the 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 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 thereof.

[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 control points included in an area where the frequency is maximum from the frequency distribution, an error ellipse calculation unit 13 that calculates, for each pair of satellites, an error ellipse which is an area in which the control point extracted from the frequency distribution may exist, an error ellipse axis length theoretical value calculation unit 14 that calculates a theoretical value of the axis length of the error ellipse in which the control point exists based on the SNR of the received signal, an FDOA moving variance value calculation unit 15 that calculates a variance value 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 control point extracted from the frequency distribution exists, and a target velocity component calculation unit 16 that calculates a velocity 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 orientation point exists, estimated based on the SNR of the received signal, and the axis length of the error ellipse in which the orientation point exists, extracted from the frequency distribution of the orientation point, the variance value of the FDOA 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. In this way, the speed estimation device 2 can 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 the speed information of target A estimated from the speed component of target A calculated by a target speed component calculation unit 16 and the 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: step ST5A in which the frequency distribution calculation unit 11 calculates the frequency distribution; step ST6A in which the control point extraction unit 12 extracts, from the frequency distribution, a control point included in an area with the maximum frequency; step ST7A in which the error ellipse calculation unit 13 calculates, for each pair of satellites, an error ellipse which is an area in which the control point extracted from the frequency distribution may exist; step ST8A in which the error ellipse axis length theoretical value calculation unit 14 calculates, based on the signal-to-noise ratio of the received signal, a theoretical value of the axis length of the error ellipse in which the control point exists; step ST9A in which the FDOA moving variance value 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 the target velocity component calculation unit 16 calculates a velocity component of the target A based on the variance value of the FDOA. By executing this method, the speed estimation device 2 can estimate the speed information of the target A to be used for categorizing 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 component 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 component 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 classifying device 1A according to embodiment 2. In Fig. 11, the target classifying 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 classifying device 1. In addition to the target classifying 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 Fig. 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. Ground station antennas #1A, #2A, and #3A receive radio waves that arrive 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 that is composed of 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, 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 the ground station antennas #1A, #2A, and #3A. The operation of the positioning processing unit is the same as in embodiment 1.

[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, a theoretical error ellipse axis length 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 theoretical error ellipse axis length 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 velocity component calculation unit 16 determines the velocity components of target A in each direction, and then the target classification unit 3 calculates the speed of target A. This has the advantage of being able to obtain three-dimensional motion information of target A. 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 velocity 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 enables 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).

[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).

[0089] By independently using the above equations (55), (56), and (57), the speed v of the target A can be calculated. ｅｓｔ 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 the target A can be calculated according to the following equations (58), (59) and (60). ｅｓｔ Bars are calculated in triplicate.

[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 bar is the final target speed of A, v ｅｓｔ Calculated as bars.

[0091] By calculating 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 target A and the satellite, making the inverse matrix calculation difficult. This allows the speed estimation device 2A to calculate the speed of target A more robustly.

[0092] Next, a speed estimation method according to embodiment 2 will be described. Fig. 12 is a flowchart showing the speed estimation method according to embodiment 2, illustrating a series of operations performed by speed estimation device 2A. The processes from step ST1B to step ST9B in Fig. 12 are the same as the processes from step ST1A to step ST9A in Fig. 9.

[0093] The target speed calculation unit 17 calculates a plurality of speeds of the target A based on the FDOA variance calculated by the FDOA moving variance calculation unit 15, and calculates the arithmetic mean of the plurality of 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 ｅｓｔ bar, and the velocity information v of the 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, 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 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 control points included in the region where the frequency is maximum 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 point extracted from the frequency distribution may exist, an error ellipse axis length theoretical value calculation unit 14 that calculates a theoretical value of the axis length of the error ellipse in which the control point exists based on the SNR of the received signal, an FDOA moving variance calculation unit 15 that calculates a variance value 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 control point extracted from the frequency distribution exists, and a target speed calculation unit 17 that calculates a plurality of speeds of target A based on the variance value and calculates the arithmetic average of the plurality of velocities of target A as the speed of target A. The speed estimation device 2A calculates a variance value 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 in which the orientation point exists, estimated based on the SNR of the received signal, and the axis length of the error ellipse in which the orientation point exists, extracted from the frequency distribution of the orientation 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 classification results for target A.

[0098] The speed estimation method according to the second embodiment includes step ST5B in which the frequency distribution calculation unit 11 calculates the frequency distribution, step ST6B in which the control point extraction unit 12 extracts control points included in an area with the maximum frequency from the frequency distribution, step ST7B in which the error ellipse calculation unit 13 calculates an error ellipse, which is an area where the control point extracted from the frequency distribution may exist, for each pair of satellites, and step ST7B in which the error ellipse theoretical axis length calculation unit 14 calculates an area where the control point may exist based on the signal-to-noise ratio of the received signal. The method includes step ST8B in which the FDOA moving variance calculation unit 15 calculates a theoretical value of the axis length of the error ellipse in which the orientation point extracted from the frequency distribution exists, step ST9B in which the 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 orientation point extracted from the frequency distribution exists, and 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 mean of the plurality of velocities 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 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, because the speed estimation device 2A can calculate the speed of target A more robustly, the target classification device 1A can ultimately stably output classification results for target A.

[0100] Embodiment 3. Fig. 13 is a block diagram showing an example of the configuration of a target classifying device 1B according to embodiment 3. In Fig. 11, like the target classifying device 1, the target classifying device 1B 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 classifying device 1B, Fig. 13 also shows target A, the source of the radio waves, as the target to be classified.

[0101] The number of ground station antennas provided corresponds to the number of satellites. In Fig. 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. Ground station antennas #1A, #2A, and #3A receive radio waves that arrive 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 that is composed 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 the ground station antennas #1A, #2A, and #3A. The operation of the positioning processing unit is the same as in embodiment 1.

[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, a theoretical error ellipse axis length 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 theoretical error ellipse axis length 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 a velocity component in the direction of the earth's surface plane, and for example, the velocity component v in the north direction is 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, the 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 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 have three relationships shown in the following equations (62), (63), and (64).

[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 by 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.

[0107] Depending on the positional relationship between the satellite and target A, the denominator terms in the above equations (55), (56), and (57) become extremely small. In other words, when the conditions shown in the following equations (67), (68), and (69) are satisfied for a certain minute constant ε, the term is omitted and the calculation averaging process is performed. 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 calculate 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.

[0108] Next, a speed estimation method according to embodiment 3 will be described. Fig. 14 is a flowchart showing the speed estimation method according to embodiment 3, illustrating a series of operations performed by speed estimation device 2B. The processes from step ST1C to step ST9C in Fig. 14 are similar to the processes from step ST1A to step ST9A in Fig. 9.

[0109] The target planar direction velocity component calculation unit 18 calculates the planar direction velocity component of the target A based on the FDOA variance calculated by the FDOA moving variance value calculation unit 15 (step ST10C). ｅｓｔ and the north direction velocity component v, which is the velocity component in the planar direction of target A obtained in step ST10C. Ｎ and the eastward velocity component v Ｅ For example, the target classification unit 3B executes 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, 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, theoretical error ellipse axis length calculation unit 14, FDOA moving variance calculation unit 15, and target plane direction velocity component calculation unit 18, which are provided 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 may be 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 control points included in an area where the frequency is maximum from the frequency distribution, an error ellipse calculation unit 13 that calculates, for each pair of satellites, an error ellipse which is an area in which the control point extracted from the frequency distribution may exist, an error ellipse axis length theoretical value calculation unit 14 that calculates a theoretical value of the axis length of the error ellipse in which the control point exists based on the SNR of the received signal, an FDOA movement variance value calculation unit 15 that calculates a variance value of the FDOA between 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 point extracted from the frequency distribution exists, and a target planar direction velocity component calculation unit 18 that calculates a velocity component in the planar direction of the target A based on the variance value. The speed estimation device 2B calculates a variance value 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 in which the control point exists, estimated based on the SNR of the received signals, and the axis length of the error ellipse in which the control point exists, extracted from the frequency distribution of the control points, and calculates the velocity component of target A in the planar direction 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, the speed estimation device 2B can robustly calculate the magnitude of the velocity component 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, the speed estimation device 2B can estimate the speed of target A more robustly than the speed estimation device 2, and can obtain more information regarding the movement of target A than the 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. This allows the target classification device 1B 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 2B can calculate the speed of target A more robustly, the target classification device 1B can consequently stably output the classification result of target A.

[0114] The speed estimation method according to the third embodiment includes step ST5C in which the frequency distribution calculation unit 11 calculates the frequency distribution, step ST6C in which the control point extraction unit 12 extracts, from the frequency distribution, a control point included in an area with the maximum frequency, step ST6C in which the error ellipse calculation unit 13 calculates, for each pair of satellites, an error ellipse which is an area in which the control point extracted from the frequency distribution may exist, step ST7C in which the error ellipse axis length theoretical value calculation unit 14 calculates, based on the signal-to-noise ratio of the received signal, a theoretical value of the axis length of the error ellipse in which the control point exists, step ST8C in which the FDOA moving variance value 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 ST10C in which the target planar direction velocity component calculation unit 18 calculates a 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, because the speed estimation device 2B can calculate the speed of the target A more robustly, the target classification device 1B can consequently stably output the classification result of the target A.

[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.

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

[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 Reception 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 moving 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, which is a radio wave source, and arrives via a plurality of satellites, and sequentially acquires orientation points, which 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, comprising: a frequency distribution calculation unit that calculates a frequency distribution of orientation points converted into latitude and longitude coordinates; an orientation point extraction unit that extracts orientation points existing in an area with the maximum frequency from the frequency distribution; an error ellipse calculation unit that calculates an error ellipse, which is an area in which 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 the error ellipse in which the orientation point exists, based on the signal-to-noise ratio of the received signal; and a variance calculation unit that calculates a variance value of the arrival frequency difference between the received signals associated with 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 orientation point extracted from the frequency distribution exists. a target speed component calculation unit that calculates a speed component of the target based on the variance value.

2. A speed estimation device that receives radio waves transmitted from a target, which is a radio wave source, and arrives via a plurality of satellites, and sequentially acquires orientation points, which 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, comprising: a frequency distribution calculation unit that calculates a frequency distribution of orientation points converted into latitude and longitude coordinates; an orientation point extraction unit that extracts orientation points existing in an area with the maximum frequency from the frequency distribution; an error ellipse calculation unit that calculates an error ellipse, which is an area in which 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 the error ellipse in which the orientation point exists, based on the signal-to-noise ratio of the received signal; and a variance calculation unit that calculates a variance value of the arrival frequency difference between the received signals associated with 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 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, which is a radio wave source, and arrives via a plurality of satellites, and sequentially acquires orientation points, which 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, comprising: a frequency distribution calculation unit that calculates a frequency distribution of orientation points converted into latitude and longitude coordinates; an orientation point extraction unit that extracts orientation points existing in an area with the maximum frequency from the frequency distribution; an error ellipse calculation unit that calculates an error ellipse, which is an area in which 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 the error ellipse in which the orientation point exists, based on the signal-to-noise ratio of the received signal; and a variance calculation unit that calculates a variance value of the arrival frequency difference between the received signals associated with 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 orientation point extracted from the frequency distribution exists. a target planar direction velocity component calculation unit that calculates a velocity component of the target in a planar direction based on the variance value.

4. A target classification device comprising: a speed estimation device as claimed in claim 1; and a target classification unit which classifies the target based on speed information of the target estimated from the speed component of the target calculated by the target speed component calculation unit and position information of the target.

5. A target classification device comprising: a speed estimation device as claimed in claim 2; and a target classification unit which classifies the target based on the target speed information calculated by the target speed calculation unit and position information of the target.

6. A target classification device comprising: a speed estimation device as claimed in claim 3; and a target classification unit which classifies the target based on the target's planar direction velocity component information calculated by the target planar direction velocity component calculation unit and the target's position information.

7. A speed estimation method executed by the speed estimation device according to claim 1, comprising the steps of: said frequency distribution calculation unit calculating said frequency distribution; said control point extraction unit extracting control points existing in an area with the maximum frequency from said frequency distribution; said error ellipse calculation unit calculating, for each pair of satellites, an error ellipse which is an area in which the control point extracted from said frequency distribution may exist; said theoretical value calculation unit calculating 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; said variance value calculation unit calculating said 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 control point extracted from said frequency distribution exists; and said target speed component calculation unit calculating the speed 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 the steps of: said frequency distribution calculation unit calculating said frequency distribution; said control point extraction unit extracting control points existing in an area with the maximum frequency from said frequency distribution; said error ellipse calculation unit calculating, for each pair of satellites, an error ellipse which is an area in which the control point extracted from said frequency distribution may exist; said theoretical value calculation unit calculating a theoretical value of an axis length of an error ellipse in which a control point exists based on a signal-to-noise ratio of said received signal; said variance calculation unit calculating said variance based on the difference between the theoretical value of the axis length of an error ellipse and the axis length of an error ellipse in which a control point extracted from said frequency distribution exists; and said target speed calculation unit calculating a plurality of speeds of the target based on said variance, and calculating 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 the steps of: said frequency distribution calculation unit calculating said frequency distribution; said control point extraction unit extracting control points existing in an area with the maximum frequency from said frequency distribution; said error ellipse calculation unit calculating, for each pair of satellites, an error ellipse which is an area in which the control points extracted from said frequency distribution may exist; said theoretical value calculation unit calculating a theoretical value of the axis length of the error ellipse in which the control points exist based on the signal-to-noise ratio of the received signal; said variance value calculation unit calculating said 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 control points extracted from said frequency distribution exist; and said target planar direction velocity component calculation unit calculating a velocity component in the planar direction of the target based on said variance value.

10. A target classification method executed by the target classification device described in claim 4, comprising: a step in which the speed estimation device described in claim 1 calculates the speed components of the target; and a step in which the target classification unit classifies the target based on speed information of the target estimated from the speed components of the target and position information of the target.

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

12. A target classification method executed by the target classification device described in claim 6, comprising: a step in which the speed estimation device described in claim 3 calculates speed component information of the target in a planar direction; and a step in which the target classification unit classifies the target based on the speed component information of the target in the planar direction and position information of the target.

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