A single satellite moving target passive positioning method based on ADS-B signal

Abstract

The present invention discloses a single-satellite moving target passive positioning method based on ADS-B signals, which belongs to the field of aviation technology. The method comprises the following steps: firstly, determining the basic parameters of positioning, including the sampling period of positioning, the search processing window length N required for single positioning, and the total positioning time; obtaining the observation value of the kth observation, including two azimuth direction finding results and frequency measurement results for direction finding-frequency measurement combined passive positioning, as well as the position, speed, attitude angle, and orbit of the satellite itself at that moment; judging whether the current number of sampling points k is less than the search processing window length N required for single positioning; sliding window processing measurement results according to the most recent N observation values, and positioning search for the target to obtain the rough positioning result of the kth observation; performing Kalman filtering on the positioning result, and outputting the filtered positioning result. The method of the present invention solves the problem that the positioning accuracy is low and the positioning result is updated slowly when a single satellite performs passive positioning on a moving target such as an airplane.

Description

Technical Field

[0001] The invention belongs to the field of aviation technology, and in particular relates to a single-satellite moving target passive positioning method based on ADS-B signals. Background Art

[0002] The ADS-B system is the abbreviation of the Automatic Dependent Surveillance-Broadcast system. It consists of multiple ground stations and airborne stations, and completes two-way data communication in a meshed, multi-point to multi-point manner. The ADS-B currently used is mainly a land-based ADS-B system, but it is limited by terrain changes and cannot monitor aircraft in the airspace of distant sea areas. In order to achieve wide-area coverage of the world, ADS-B monitoring stations are set up on low-orbit satellites, which can effectively get rid of terrain restrictions and increase the coverage area. Compared with land-based ADS-B, satellite-based ADS-B only requires a very small number of monitoring stations to achieve global monitoring coverage.

[0003] However, since the ADS-B system adopts an open and shared automatic monitoring architecture, and its technical standards and data encoding formats are open to the outside world, the ADS-B system is susceptible to human interference, resulting in erroneous information, which seriously affects the reliability of airspace control. In order to conduct aviation surveillance of aircraft in the far sea and far area, it is necessary to load the ADS-B message anti-spoofing system on the low-orbit satellite. It is crucial for the system to verify the source of the message. The passive positioning system can compare the message with the positioning result, thereby solving this problem to a certain extent. Low-orbit satellite passive positioning is divided into single-star passive positioning and multi-star passive positioning. Multi-star passive positioning technology refers to multiple satellites observing the emission signal of the radiation source at the same time, transmitting the observation signal to the master satellite or ground data center, establishing a positioning model and solving the radiation source position. It has high positioning accuracy, good real-time performance, and a wider positioning range, but the multi-star networking is complex and difficult to achieve. Single-star passive positioning refers to the same satellite observing the emission signal of the radiation source multiple times, using the observation quantity to establish a positioning model and solve the radiation source position. The positioning principle is simple and easy to implement, but its positioning accuracy is low.

[0004] In order to save costs, some systems still use single-satellite passive positioning methods. Since the system has only one receiving station, the amount of observations per unit time is limited, the set of simultaneous equations is complex, and it is not easy to obtain solutions to the nonlinear set of equations. In many studies, considering the large scale of the current satellite observation positioning model, the movement speed of the radiation source is ignored during the observation time, and it is regarded as a stationary point. However, the movement speed of many aircraft is relatively fast, which will obviously introduce errors to the positioning results, thereby reducing the positioning accuracy. In addition, since the data update speed of the ADS-B system is once per second, in the scenario of single-satellite passive positioning, the method of using multiple observations of simultaneous equations to solve the target position will cause the problem of slow positioning update time, which is not conducive to real-time tracking of the target. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a passive positioning method for moving targets based on ADS-B signals and a single satellite platform, which solves the problems of low positioning accuracy and slow updating of positioning results when a single satellite performs passive positioning on moving targets such as aircraft. Its accuracy is better than that of traditional positioning methods that regard moving targets as stationary.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides a single-satellite moving target passive positioning method based on ADS-B signals, comprising the following steps:

[0008] S1, determine the basic parameters of positioning, including the sampling period of positioning, the search processing window length N required for a single positioning, and the total positioning time;

[0009] S2, obtain the observation value of the kth observation, including two azimuth direction finding results and frequency measurement results used for direction finding-frequency measurement joint passive positioning, as well as the satellite's own position, speed, attitude angle, and orbit at that moment;

[0010] S3, determine whether the current number of sampling points k is less than the search processing window length N required for a single positioning. If so, return to step S2 for the next observation; if k is greater than or equal to N, proceed to step S4;

[0011] S4, based on the latest N observation values, the target is located and searched to obtain the rough positioning result of the kth observation;

[0012] S5, performing Kalman filtering on the positioning result and outputting the filtered positioning result.

[0013] Further, step S4 specifically includes:

[0014] S41, determining the parameter value of the search range according to the initial position of the satellite;

[0015] S42, calculating the direction finding and frequency measurement cost functions of each search point;

[0016] S43, weighting the cost function and calculating a joint cost function for each search point;

[0017] S44, searching for the minimum value of the joint cost function to obtain the positioning result.

[0018] Further, in step S41, the coordinates of the target in the current measurement coordinate system are set to (x T ,y T ,z T ), the satellite coordinates are (x i ,y i ,z i), the satellite motion speed in the current measurement coordinate system is v i =[v xi ,v yi ,v zi ] T , the distance between the satellite and the target is r i , the radial velocity is v ri ; The signal direction angle measurement value α measured by the on-board antenna and receiver for the i-th measurement i and β i , and the frequency measurement value f i as follows:

[0019]

[0020] Among them, i=1,2,..,N,ε i , i are the measurement errors of the two direction angles, ζ i is the measurement error of the instantaneous frequency of the signal.

[0021] Further, in step S42, the azimuth angle measurement steps are as follows: Combined with the search algorithm, the cost function is calculated for each search point (x, y, z) according to the azimuth angle measurement conditions at N moments:

[0022]

[0023] in, and are the estimated values ​​of the two azimuths at the search point, namely:

[0024]

[0025]

[0026] For frequency measurement, the measured frequencies at N moments are expressed in matrix form as: ψ = f 0 ·F+ζ, where

[0027] ψ=[f 1 ,f 2 ,...,f N ] T

[0028] F=[F 1 (x T ,y T ,z T ),F 2 (x T ,y T ,z T ),...,F N (x T,y T ,z T )] T

[0029] ζ=[ζ 1 ,ζ 2 ,...,ζ N ] T ;

[0030] The center frequency f in the formula 0 As the quantity to be estimated, its least squares estimate at the search point (x, y, z) can be expressed as:

[0031]

[0032] F x,y,z =[F 1 (x,y,z),F 2 (x,y,z),...,F N (x,y,z)] T ;

[0033] Select all search points in the 0 The coordinates of the position point where the mean square error of the least squares estimate is the smallest, and the search point is the optimal solution for the target position:

[0034]

[0035] Where J 3 This is the cost function of the search point in frequency measurement and positioning.

[0036] Further, in step S43, the three cost functions are normalized to obtain a joint cost function of the single-satellite direction finding and frequency measurement joint positioning method:

[0037] J=c 1 J 1 +c 2 J 2 +c 3 J 3

[0038] The coefficients of the three cost functions are c 1 、c 2 and c 3 , which is calculated as follows: divide the search range into small grids, and calculate the average value of the cost function of each grid point in the search range, and take the inverse of the average value as the coefficient.

[0039] The beneficial effects of the present invention are:

[0040] The present invention discloses a single-satellite moving target passive positioning method based on ADS-B signals, which can realize the positioning and tracking of a moving target by a single satellite without decoding the ADS-B message, and solves the problem of low positioning accuracy and slow updating of positioning results when a single satellite performs passive positioning on a moving target such as an aircraft. By combining sliding processing and direction finding-frequency measurement joint positioning with Kalman filtering, a more accurate positioning result after filtering is obtained while shortening the positioning time.

[0041] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or those skilled in the art may be taught from the practice of the present invention. The objectives and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration:

[0043] Figure 1 It is the algorithm flow chart of the present invention;

[0044] Figure 2 It is a schematic diagram of the flow of the positioning method in step 4 of the present invention;

[0045] Figure 3 It is a schematic diagram of the simulation structure of the method of the present invention. DETAILED DESCRIPTION

[0046] Traditional passive positioning methods mainly locate targets based on three observation quantities: time difference of arrival, azimuth of arrival, and Doppler frequency of the measured signal. Aiming at the problem of treating moving targets as stationary and thus having poor positioning accuracy, the present invention provides a single-satellite moving target passive positioning method based on ADS-B signals, selects a direction finding-frequency measurement combined passive positioning method, and combines Kalman filtering to reduce the positioning error of moving targets.

[0047] The present invention uses an ADS-B receiver mounted on a satellite to continuously receive signals from the target aircraft over a period of time, obtains measurement information such as the angle and frequency of the incoming wave based on the signal, calculates the estimated value of the target position, and combines the estimated value of the target position at the previous moment to obtain a more accurate positioning result after filtering. The basic scenario of single-star positioning adopted by the present invention is: a low-orbit satellite flies around the earth in a predetermined orbit, and can receive the ADS-B signal radiated by the satellite when it flies over a certain range above the target. In the limited positioning time, the movement of the satellite and the aircraft are regarded as uniform linear motion, and a mathematical model is established.

[0048] Select N moments t 1,t 2 ,...,t N The signal is directionally and frequency-measured, and the target positioning result is obtained by combining the satellite's own position, speed, attitude angle, orbit and other information at each moment. Since the positioning time selected by the model is short, in a single positioning, since the satellite speed is much greater than the flight speed of the aircraft, it can be assumed that the aircraft position is approximately fixed, that is, the aircraft speed is zero. The algorithm flow chart is as follows Figure 1 As shown, the technical solution adopted by the present invention is as follows:

[0049] S1, determine the basic positioning parameters, including: positioning sampling period, search processing window length N required for a single positioning, and total positioning time.

[0050] S2, obtain the observation value of this sampling (i.e., the kth observation), including the two azimuth direction finding results, frequency measurement results, etc. used for direction finding-frequency measurement combined passive positioning, as well as the satellite's own position, speed, attitude angle, orbit and other information at this moment.

[0051] S3, determine whether the current number of sampling points k is less than the search processing window length N required for a single positioning. If it is less than, it means that the current number of sampling points is not enough to solve a positioning result, so it is necessary to return to step S2 for the next observation.

[0052] If k is greater than or equal to N, it means that the positioning solution result can be obtained currently, and the process goes to step S4.

[0053] S4: Based on the latest N observation values, the target is located and searched to obtain the rough positioning result of the kth observation.

[0054] In order to reduce the amount of calculation and improve the positioning speed, the present invention uses the latest N observations to locate the target and obtain the rough positioning result of the kth observation. Comprehensively considering the single-satellite positioning scenario, the positioning method selects the passive positioning method of direction finding and frequency measurement. This method can combine the error geometric distribution of the two passive positioning methods of direction finding and frequency measurement to reduce the positioning error.

[0055] The specific process is as follows Figure 2 As shown, the specific steps are:

[0056] S41, determining the parameter value of the search range according to the initial position of the satellite.

[0057] For the i-th measurement, assume that the coordinates of the target in the current measurement coordinate system are (x T ,y T ,z T ), the satellite coordinates are (x i ,y i ,z i). Assume that the satellite motion speed is v in the current measurement coordinate system. i =[v xi ,v yi ,v zi ] T , the distance between the satellite and the target is r i , and the radial velocity v is obtained by taking its derivative in the distance direction ri Taking the measurement error into account, the signal direction angle measurement value α measured by the onboard antenna and receiver for the i-th measurement can be obtained: i and β i , and the frequency measurement value f i as follows:

[0058]

[0059] Among them, i=1,2,..,N,ε i , i are the measurement errors of the two direction angles, ζ i is the measurement error of the instantaneous frequency of the signal.

[0060] The direction-frequency positioning equations obtained above are nonlinear, and the equations obtained from multiple measurements are also contradictory, making it difficult to obtain closed-form solutions. Therefore, a grid search algorithm is used as a positioning solution method to divide the airspace within a certain range under the satellite into grids according to the initial position of the satellite, so as to facilitate the subsequent search for positioning points.

[0061] S42, calculating the direction finding and frequency measurement cost functions of each search point.

[0062] For azimuth measurement, combined with the search algorithm, the cost function is calculated for each search point (x, y, z) based on the azimuth measurement at N moments:

[0063]

[0064]

[0065] in, and are the estimated values ​​of the two azimuths at the search point, namely:

[0066]

[0067]

[0068] For frequency measurement, the measured frequencies at N moments are expressed in matrix form as:

[0069] ψ=f 0 ·F+ζ

[0070] Where ψ=[f 1 ,f 2 ,...,f N ] T , F=[F 1 (x T ,y T ,z T ),F 2 (x T ,y T ,z T ),...,F N (x T ,y T ,z T )] T , ζ=[ζ 1 ,ζ 2 ,...,ζ N ] T .

[0071] The center frequency f in the formula 0 As the quantity to be estimated, its least squares estimate at the search point (x, y, z) can be expressed as:

[0072]

[0073] Among them, F x,y,z =[F 1 (x,y,z),F 2 (x,y,z),...,F N (x,y,z)] T .

[0074] At each search point, an estimated value of the signal transmission frequency can be obtained according to the above formula, and only when it meets the following conditions, the search point is the optimal solution for the target location:

[0075]

[0076] That is, select all search points for f 0 The coordinates of the point where the mean square error of the least squares estimate is the smallest. 3 This is the cost function of the search point in frequency measurement and positioning.

[0077] S43, weighting the cost function, and calculating the joint cost function of each search point. The physical quantities represented by the cost functions for azimuth and frequency are different, and the magnitude of the measurement error will directly affect the mean value of each cost function. Therefore, it is necessary to normalize the three cost functions to obtain the joint cost function of the single-star direction finding and frequency measurement joint positioning method:

[0078] J=c 1 J1 +c 2 J 2 +c 3 J 3

[0079] The coefficients of the three cost functions are c 1 、c 2 and c 3 , which is calculated as follows: divide the search range into small grids, and calculate the average value of the cost function of each grid point in the search range, and take the inverse of the average value as the coefficient.

[0080] S44, searching for the minimum value of the joint cost function to obtain a positioning result. After calculating the joint cost function value of each search point, the coordinate position corresponding to the minimum value point is regarded as the result of this rough positioning.

[0081] S5, perform Kalman filtering on the positioning result and output the filtered positioning result. The positioning result calculated based on only a small number of observations often has a large error. In order to further reduce the positioning error, each rough positioning result is subjected to Kalman filtering. The moving target motion model is a two-dimensional uniform linear motion model. The process noise is a zero-mean Gaussian white noise, which is independent of the measurement noise, and its variance is determined according to the positioning error. Therefore, based on the previous filtering results, a more accurate positioning result is obtained at each moment recursively.

[0082] The present invention designs a passive positioning method for moving targets based on ADS-B signals and a single satellite platform. It adopts a direction finding-frequency measurement combined passive positioning method suitable for satellite-based ADS-B systems. For a limited number of positioning observations, the sliding window processing measurement results are used to solve the target position estimation value, and the positioning results are subjected to Kalman filtering. More accurate positioning results can be obtained in a limited number of positioning observations. The present invention solves the problem of low positioning accuracy and slow updating of positioning results when a single satellite performs passive positioning on moving targets such as aircraft. Its accuracy is better than the traditional positioning method that regards moving targets as stationary. The simulation structure is as follows: Figure 3 As shown, it is shown that the filtered positioning result can reduce the positioning error by more than 25%, that is, the positioning accuracy of the present invention is better than the traditional positioning method that regards the moving target as a stationary target.

[0083] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A single-satellite moving target passive positioning method based on ADS-B signals, characterized in that: The following steps are involved: S1, determine the basic parameters of positioning, including the sampling period of positioning, the search processing window length N required for a single positioning, and the total positioning time; S2, obtain the observation value of the kth observation, including two azimuths and signal frequencies used for direction-frequency joint passive positioning, as well as the position, speed, attitude angle, and orbit of the satellite at the time of this observation; S3, determine whether the current number of sampling points k is less than the search processing window length N required for a single positioning. If so, return to step S2 for the next observation; if k is greater than or equal to N, proceed to step S4; S4, based on the latest N observation values, the target is located and searched to obtain the rough positioning result of the kth observation; S5, performing Kalman filtering on the positioning result and outputting the filtered positioning result; Step S4 specifically includes: S41, determining the parameter value of the search range according to the initial position of the satellite; S42, calculating the direction finding and frequency measurement cost functions of each search point; S43, weighting the cost function and calculating a joint cost function for each search point; S44, searching for the minimum value of the joint cost function to obtain the positioning result.

2. The single-satellite moving target passive positioning method based on ADS-B signal according to claim 1, characterized in that: In step S41, the coordinates of the target in the current measurement coordinate system are set to , the satellite coordinates are , the satellite motion speed is , the distance between the satellite and the target is , the radial velocity is ;No. i The signal direction angle measurement value measured by the on-board antenna and receiver and , and frequency measurement value as follows: in, , , are the measurement errors of the two direction angles, is the measurement error of the instantaneous frequency of the signal, is the center frequency of the radiation source, c The speed of light.

3. The single-satellite moving target passive positioning method based on ADS-B signal according to claim 2 is characterized in that: In step S42, the azimuth measurement steps are as follows: Combined with the search algorithm, for each search point Calculate the cost function based on the azimuth measurement at N moments: in, and are the estimated values ​​of the two azimuths at the search point, is the coordinate value of the search point in the geodetic coordinate system, that is: For frequency measurement, the measured frequencies at N moments are expressed in matrix form as: ,in, ； In the formula, fi For the i The frequency measurement value of the measurement, , the center frequency in the formula As the quantity to be estimated, then its search point The least squares estimate at can be expressed as: ； Select all search points The coordinates of the position point where the mean square error of the least squares estimate is the smallest, and the search point is the optimal solution for the target position: In the formula This is the cost function of the search point in frequency measurement and positioning.

4. The single-satellite moving target passive positioning method based on ADS-B signals according to claim 3 is characterized in that: In step S43, the three cost functions are normalized to obtain a joint cost function of the single-satellite direction finding and frequency measurement joint positioning method: The coefficients of the three cost functions are , and , which is calculated as follows: divide the search range into small grids, and calculate the average value of the cost function of each grid point in the search range, and take the inverse of the average value as the coefficient.

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