Distributed synthetic aperture positioning method and system based on backward projection

Abstract

The invention discloses a distributed synthetic aperture positioning method and system based on backward projection, and belongs to the technical field of radio reconnaissance, and the method comprises the steps: arranging a plurality of unmanned aerial vehicles along the same flight path front and back, passively receiving a signal transmitted by a radiation source target, processing the received signal, and transmitting the processed signal to a server; a back projection positioning algorithm constructs a cost function of a target squint angle and a slope distance according to back projection of a Doppler history, and forms a back projection positioning image of a radiation source position in a region of interest. A nonlinear equation set of squint angles, target positions and residual frequency offsets obtained through back projection positioning search under different platforms is established, and a more accurate positioning result and a more accurate residual frequency offset estimation value can be further obtained through solving by a Newton method.

Description

Technical Field

[0001] The invention belongs to the technical field of radio reconnaissance, and in particular relates to a distributed synthetic aperture positioning method and system based on back projection. Background Art

[0002] Backprojection positioning technology is a high-precision passive emitter positioning algorithm that uses the Doppler history of the emitter to construct a cost function for processing. In non-cooperative reception such as radio spectrum monitoring, the signal obtained after down-conversion still contains residual frequency deviation, which is called residual frequency deviation. Residual frequency deviation will cause signal distortion and error accumulation, and affect the accuracy and reliability of the backprojection positioning algorithm. Effective frequency deviation estimation is the key to ensuring positioning accuracy. Summary of the invention

[0003] In order to solve the technical problems existing in the background technology, the present invention aims to provide a distributed synthetic aperture positioning method and system based on back projection, which can achieve high-precision positioning of high-value radiation sources and residual frequency offset estimation between transceivers under non-cooperative reception conditions.

[0004] In order to solve the technical problem, the technical solution of the present invention is:

[0005] A distributed synthetic aperture positioning method based on backprojection, the method comprising:

[0006] Multi-UAV configuration: Multiple UAVs are deployed along the same flight trajectory, with equal speed and equal distance. Each UAV passively receives the target signal through an omnidirectional antenna;

[0007] Signal processing: down-convert the received target signal into a baseband signal, de-modulate the baseband signal, extract the Doppler information of the target signal, and record the time variation of the Doppler frequency;

[0008] Back projection positioning: Grid division of the area of ​​interest, the target area is divided into multiple grid points; Calculate the echo Doppler signal, and predict the Doppler signal of each grid point based on the grid point position and the UAV trajectory; Coherent accumulation, the Doppler signal received by the UAV is coherently accumulated with the signal phase of each grid point to form a positioning cost function; Peak search, find the peak in the cost function to obtain a preliminary estimate of the target slant angle and slant range;

[0009] Nonlinear equation modeling: Based on the back-projection results of different drones and combined with the residual frequency deviation, a nonlinear equation of target position and oblique angle is established;

[0010] Nonlinear optimization solution: Newton's method is used to solve the nonlinear equations to obtain the precise position of the target and the residual frequency offset estimate.

[0011] Further, the multi-unmanned machine configuration and signal processing include:

[0012] Three UAVs are arranged in front and behind along the flight direction. Each UAV is distributed at equal speed and distance on the same flight trajectory and equipped with an omnidirectional antenna to passively receive the signal emitted by the radiation source target, down-convert the received signal to obtain the baseband signal; de-modulate the baseband signal to obtain the corresponding Doppler signal;

[0013] Assume that the instantaneous distances between the three UAV platform antennas and the radiation source targets are R 1 (t), R 2 (t) and R 3 (t), the Doppler signal r obtained after baseband demodulation 1 (t), r 2 (t) and r 3 (t) is expressed by formula (1)(2)(3):

[0014]

[0015] Among them, f c is the carrier frequency of the radiation source signal, c is the speed of light, f 1 is the fixed residual frequency offset.

[0016] Further, the back projection positioning includes:

[0017] The detection area of ​​interest is divided into m*n units according to the polar coordinate grid. k (t),y k (t),z k (t)], considering the influence of signal preprocessing on Doppler signal, calculate different grid points [x mn ,y mn ,z mn ], as shown in formula (4):

[0018]

[0019] Among them, k = 1, 2, 3 are the numbers of the drones, R mn Shows the instantaneous distance between the grid point and the platform;

[0020] The Doppler signal r obtained by each UAV 1 (t), r 2 (t) and r 3 (t) and Doppler signal r mn The phase of (t) is coherently accumulated and the obtained correlation value is used as the grid point [x mn ,y mn ,zmn ] is shown in formula (5)(6)(7):

[0021]

[0022] Where: I k (θ m ,R n ) is the result of coherent accumulation of the UAV numbered k at the grid point (m,n);

[0023] Search for the peak value of the positioning image and take the slant angle and slant distance corresponding to the peak position as the target position, as shown in formulas (8), (9), and (10):

[0024]

[0025] in, The slant angle and slant distance obtained by the backprojection positioning algorithm for the UAV numbered k.

[0026] Furthermore, the nonlinear optimization solution includes:

[0027] The nonlinear equations of the oblique angle, target position and residual frequency offset obtained by back-projection positioning of different UAVs are established, as shown in equation (11):

[0028]

[0029] Where: The radiation source position is expressed as [x 0 ,y 0 ,z 0 ], the position of the UAV numbered k is represented as [x ck ,y ck ,z ck ], The velocity vector of the UAV numbered k is expressed as [x ck ,y ck ,z ck ], is the current position vector of the UAV numbered k, expressed as

[0030] A distributed synthetic aperture positioning system based on backprojection, the system comprising:

[0031] Multi-UAV configuration module: multiple UAVs are deployed along the same flight trajectory, with equal speed and equal distance; each UAV passively receives target signals through an omnidirectional antenna;

[0032] Signal processing module: down-convert the received target signal into a baseband signal, de-modulate the baseband signal, extract the Doppler information of the target signal, and record the time variation of the Doppler frequency;

[0033] Back-projection positioning module: Grid division of the area of ​​interest, the target area is divided into multiple grid points; Calculate the echo Doppler signal, and predict the Doppler signal of each grid point based on the grid point position and the UAV trajectory; Coherent accumulation, the Doppler signal received by the UAV is coherently accumulated with the signal phase of each grid point to form a positioning cost function; Peak search, find the peak in the cost function to obtain a preliminary estimate of the target slant angle and slant range;

[0034] Nonlinear equation modeling module: Based on the back projection results of different drones and combined with the residual frequency deviation, a nonlinear equation group of target position and oblique angle is established;

[0035] Nonlinear optimization solution module: uses Newton's method to solve the nonlinear equations to obtain the precise position of the target and the residual frequency offset estimate.

[0036] Furthermore, the multi-unmanned machine configuration and signal processing module specifically include:

[0037] Three UAVs are arranged in front and behind along the flight direction. Each UAV is distributed at equal speed and distance on the same flight trajectory and equipped with an omnidirectional antenna to passively receive the signal emitted by the radiation source target, down-convert the received signal to obtain the baseband signal; de-modulate the baseband signal to obtain the corresponding Doppler signal;

[0038] Assume that the instantaneous distances between the three UAV platform antennas and the radiation source targets are R 1 (t), R 2 (t) and R 3 (t), the Doppler signal r obtained after baseband demodulation processing 1 (t), r 2 (t) and r 3 (t) can be expressed by formula (1), (2), (3):

[0039]

[0040] Among them, f c is the carrier frequency of the radiation source signal, c is the speed of light, f 1 is the fixed residual frequency offset.

[0041] Further, the back projection positioning module includes:

[0042] The detection area of ​​interest is divided into m*n units according to the polar coordinate grid. Based on the motion trajectory of each UAV platform [x k (t),y k (t),z k (t)], considering the influence of signal preprocessing on Doppler signal, calculate different grid points [x mn,y mn ,z mn ], as shown in formula (4):

[0043]

[0044] Among them, k = 1, 2, 3 are the numbers of the drones, R mn Shows the instantaneous distance between the grid point and the platform;

[0045] The Doppler signal r obtained by each UAV 1 (t), r 2 (t) and r 3 (t) and Doppler signal r mn The phase of (t) is coherently accumulated and the obtained correlation value is used as the grid point [x mn ,y mn ,z mn ] is shown in formula (5)(6)(7):

[0046]

[0047] Where: I k (θ m ,R n ) is the result of coherent accumulation of the UAV numbered k at the grid point (m,n);

[0048] Search for the peak value of the positioning image and take the slant angle and slant distance corresponding to the peak position as the target position, as shown in formulas (8), (9), and (10):

[0049]

[0050] in, The slant angle and slant distance obtained by the backprojection positioning algorithm for the UAV numbered k.

[0051] Furthermore, the nonlinear optimization solution module includes:

[0052] The nonlinear equations of the oblique angle, target position and residual frequency offset obtained by back-projection positioning of different UAVs are established, as shown in equation (11):

[0053]

[0054] Where: The radiation source position is expressed as [x 0 ,y 0 ,z 0 ], the position of the UAV numbered k is represented as [x ck ,y ck ,z ck ], The velocity vector of the UAV numbered k is expressed as [x ck ,y ck ,z ck ], is the current position vector of the UAV numbered k, expressed as

[0055] A computer device, characterized in that it includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any one of the above-mentioned distributed synthetic aperture positioning methods based on back projection is implemented.

[0056] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements any one of the above-mentioned distributed synthetic aperture positioning methods based on back projection.

[0057] Compared with the prior art, the advantages of the present invention are:

[0058] The invention discloses a distributed synthetic aperture positioning method and system based on back-projection, which can accurately locate high-value radiation sources in the case of non-cooperative reception. At the same time, the residual frequency deviation in the signal can be estimated, and compensation can be performed according to the estimation result, thereby reducing or eliminating the influence of the frequency deviation on the positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 , a flow chart of a distributed synthetic aperture positioning method based on back projection disclosed in the present invention;

[0060] Figure 2 , Geometric model diagram of distributed synthetic aperture positioning method based on back projection;

[0061] Figure 3 , GDOP diagram of positioning error of the positioning area based on the distributed synthetic aperture positioning method based on back projection. DETAILED DESCRIPTION

[0062] The specific implementation mode of the present invention is described below in conjunction with embodiments:

[0063] It should be noted that the structures, proportions, sizes, etc. shown in this specification are only used to match the contents disclosed in the specification so that people familiar with this technology can understand and read them, and are not used to limit the conditions under which the present invention can be implemented. Any structural modification, change in proportional relationship or adjustment of size should still fall within the scope of the technical content disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0064] At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" cited in this specification are only for the convenience of description and are not used to limit the scope of implementation of the present invention. Changes or adjustments to their relative relationships should be regarded as the scope of implementation of the present invention without substantially changing the technical content.

[0065] Embodiment 1:

[0066] A distributed synthetic aperture positioning method and system based on back-projection, multiple UAVs are arranged in front and behind along the same flight trajectory, passively receiving the signals emitted by the radiation source target and processing the received signals. The transceivers are in a non-cooperative working mode, and there is a fixed frequency offset, which is called residual frequency offset.

[0067] The backprojection positioning algorithm constructs the cost function of the target slant angle and slant range based on the backprojection of the Doppler process, and forms a backprojection positioning image of the radiation source position in the area of ​​interest. The positioning accuracy of the single-UAV backprojection positioning algorithm is easily affected by the residual frequency offset. A multi-UAV distributed configuration is proposed to establish a nonlinear equation group of the slant angle, target position and residual frequency offset obtained by the backprojection positioning search under different platforms. The Newton method can be used to solve it to further obtain more accurate positioning results and residual frequency offset estimates.

[0068] Specifically, the steps include:

[0069] Step 1: Taking the three-UAV platform along-track configuration as an example, three UAVs are arranged front and back along the flight direction. Each UAV is distributed at equal speed and distance on the same flight trajectory and equipped with an omnidirectional antenna to passively receive the signal emitted by the radiation source target, down-convert the received signal to obtain the baseband signal; de-modulate the baseband signal to obtain the corresponding Doppler signal;

[0070] Assume that the instantaneous distances between the three UAV platform antennas and the radiation source targets are R 1 (t), R 2 (t) and R 3 (t), the Doppler signal r obtained after baseband demodulation processing 1 (t), r 2 (t) and r 3 (t) can be expressed by formula (1)(2)(3):

[0071]

[0072] Where: f c is the carrier frequency of the radiation source signal, c is the speed of light, f 1 is the fixed residual frequency offset;

[0073] Step 2: Divide the detection area of ​​interest into m*n units according to the polar coordinate grid, based on the motion trajectory of each UAV platform [x k (t),y k (t),z k (t)], considering the influence of signal preprocessing on Doppler signal, calculate different grid points [x mn ,y mn ,z mn ], as shown in formula (4):

[0074]

[0075] Where: k = 1, 2, 3 are the numbers of the drones, R mn Shows the instantaneous distance between the grid point and the platform;

[0076] Step 3: The Doppler signal r obtained by each UAV 1 (t), r 2 (t) and r 3 (t) and Doppler signal r mn The phase of (t) is coherently accumulated and the obtained correlation value is used as the grid point [x mn ,y mn ,z mn ] is shown in formula (5)(6)(7):

[0077]

[0078] Where: I k (θ m ,R n ) is the result of the coherent accumulation of the numbered UAV k at the grid point (m,n)

[0079] Step 4: Search for the peak value of the positioning image, and use the slant angle and slant distance corresponding to the peak position as the target position, as shown in formulas (8), (9), and (10).

[0080]

[0081] in, The slant angle and slant distance obtained by the backprojection positioning algorithm for the UAV numbered k.

[0082] Step 5: Establish a nonlinear equation group of the oblique angle, target position and residual frequency offset obtained by back projection positioning of different UAVs, as shown in equation (11):

[0083]

[0084] Where: The radiation source position is expressed as [x 0 ,y0 ,z 0 ], the position of the UAV numbered k is represented as [x ck ,y ck ,z ck ], The velocity vector of the UAV numbered k is expressed as [x ck ,y ck ,z ck ], is the current position vector of the UAV numbered k, expressed as

[0085] Step 6: Solve the nonlinear equations using the Newton descent method to obtain the position estimation result of the radiation source target and the residual frequency offset estimation result.

[0086] Embodiment 2:

[0087] like Figure 1 As shown, the present embodiment discloses a distributed synthetic aperture positioning method based on back projection, and the specific implementation steps are as follows:

[0088] Assume that the drone flies in a straight line at a constant speed, the flight speed v is 30m / s, and the flight altitude is 500 meters. The carrier frequency of the radiation source f 0 The frequency is 2 GHz, the position and velocity errors are set to 0.1 m and 0.1 m / s Gaussian distribution standard deviations respectively, and the distance R from the radiation source to the UAV route 0 The distance between the two platforms is 10km, and the signal-to-noise ratio of the radiation source is set to 5dB. Taking the three-UAV platform along-track configuration as an example, three UAVs are arranged in front and behind along the flight direction. Each UAV is distributed at equal speed and distance on the same flight track and equipped with an omnidirectional antenna. The distance between each antenna is 1km. The signal synthesis time received by each platform is unified to 5s, and the residual frequency deviation is set to 105.2Hz. The geometric model is as follows: Figure 2 As shown in the figure, the positioning error GDOP diagram of the positioning area based on the distributed synthetic aperture positioning method based on back projection is as follows: Figure 3 shown.

[0089] Step 1: Assume that the instantaneous distances between the three UAV platform antennas and the radiation source target are R 1 (t), R 2 (t) and R 3 (t), the Doppler signal r obtained after baseband demodulation 1 (t), r 2 (t) and r 3 (t) can be expressed by formula (1)(2)(3):

[0090]

[0091] Where: f cis the carrier frequency of the radiation source signal, c is the speed of light, f 1 is the fixed residual frequency offset;

[0092] Step 2: Divide the detection area of ​​interest into 251*153 cells according to the polar coordinate grid, and calculate the detection area based on the trajectory of each UAV platform [x k (t),y k (t),z k (t)], considering the influence of signal preprocessing on Doppler signal, calculate different grid points [x mn ,y mn ,z mn ], as shown in formula (4):

[0093]

[0094] Where: k = 1, 2, 3 are the numbers of the drones, R mn Shows the instantaneous distance between the grid point and the platform;

[0095] Step 3: The Doppler signal r obtained by each UAV 1 (t), r 2 (t) and r 3 (t) and Doppler signal r mn The phase of (t) is coherently accumulated and the obtained correlation value is used as the grid point [x mn ,y mn ,z mn ] is shown in formula (5)(6)(7):

[0096]

[0097] Where: I k (θ m ,R n ) is the result of the coherent accumulation of the numbered UAV k at the grid point (m,n)

[0098] Step 4: Search for the peak value of the positioning image, and use the slant angle and slant distance corresponding to the peak position as the target position, as shown in formulas (8), (9), and (10).

[0099]

[0100] in, is the slant angle and slant distance obtained by the back projection positioning algorithm of the UAV numbered k. are -7.152, -1.434, 4.272, They are 10049.8721, 10001.1437, and 10052.7562.

[0101] Step 5: Establish a nonlinear equation group of the oblique angle, target position and residual frequency offset obtained by back projection positioning of different UAVs, as shown in equation (11):

[0102]

[0103] Where: The radiation source position is expressed as [x 0 ,y 0 ,z 0 ], in this case it is [7000,0,0], and the position of the drone numbered k is represented by [x ck ,y ck ,z ck ], The velocity vector of the UAV numbered k is expressed as [x ck ,y ck ,z ck ], is the current position vector of the UAV numbered k, expressed as

[0104] Step 6. Solve the nonlinear equations using the Newton descent method to obtain the position estimation result of the radiation source target as [7053.87, 34.58, 32.27], the positioning error is 71.69m, and the residual frequency offset estimation result is 104.97.

[0105] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0106] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0107] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0109] The preferred embodiments of the present invention are described in detail above, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

[0110] Many other changes and modifications may be made without departing from the concept and scope of the present invention.It should be understood that the present invention is not limited to the specific embodiments, and the scope of the present invention is defined by the appended claims.

Claims

1. A distributed synthetic aperture positioning method based on backprojection, characterized in that: The method comprises: Multi-UAV configuration: Multiple UAVs are deployed along the same flight trajectory, with equal speed and equal distance. Each UAV passively receives the target signal through an omnidirectional antenna; Signal processing: down-convert the received target signal into a baseband signal, de-modulate the baseband signal, extract the Doppler information of the target signal, and record the time variation of the Doppler frequency; Back projection positioning: Grid division of the area of ​​interest, the target area is divided into multiple grid points; Calculate the echo Doppler signal, and predict the Doppler signal of each grid point based on the grid point position and the UAV trajectory; Coherent accumulation, the Doppler signal received by the UAV is coherently accumulated with the signal phase of each grid point to form a positioning cost function; Peak search, find the peak in the cost function to obtain a preliminary estimate of the target slant angle and slant range; Nonlinear equation modeling: Based on the back-projection results of different drones and combined with the residual frequency deviation, a nonlinear equation of target position and oblique angle is established; Nonlinear optimization solution: Newton's method is used to solve the nonlinear equations to obtain the precise position of the target and the residual frequency offset estimate.

2. The distributed synthetic aperture positioning method based on backprojection according to claim 1, characterized in that: The multi-drone configuration and signal processing include: Three UAVs are arranged in front and behind along the flight direction. Each UAV is distributed at equal speed and distance on the same flight trajectory and equipped with an omnidirectional antenna to passively receive the signal emitted by the radiation source target, down-convert the received signal to obtain the baseband signal; de-modulate the baseband signal to obtain the corresponding Doppler signal; Assume that the instantaneous distances between the antennas of the three UAV platforms and the radiation source targets are R1(t), R2(t) and R3(t) respectively. The Doppler signals r1(t), r2(t) and r3(t) obtained after baseband demodulation processing are expressed by formulas (1)(2)(3): Among them, f c is the carrier frequency of the radiation source signal, c is the speed of light, and f1 is the fixed residual frequency deviation.

3. The distributed synthetic aperture positioning method based on backprojection according to claim 1, characterized in that: The back projection positioning comprises: The detection area of ​​interest is divided into m*n units according to the polar coordinate grid. k (t),y k (t),z k (t)], considering the influence of signal preprocessing on Doppler signal, calculate different grid points [x mn ,y mn ,z mn ], as shown in formula (4): Among them, k = 1, 2, 3 are the numbers of the drones, R mn Shows the instantaneous distance between the grid point and the platform; The Doppler signals r1(t), r2(t) and r3(t) obtained by each UAV are compared with the Doppler signal r mn The phase of (t) is coherently accumulated and the obtained correlation value is used as the grid point [x mn ,y mn ,z mn ] is shown in formula (5)(6)(7): Where: I k (θ m ,R n ) is the result of coherent accumulation of the UAV numbered k at the grid point (m,n); Search for the peak value of the positioning image and take the slant angle and slant distance corresponding to the peak position as the target position, as shown in formulas (8), (9), and (10): in, The slant angle and slant distance obtained by the backprojection positioning algorithm for the UAV numbered k.

4. The distributed synthetic aperture positioning method based on backprojection according to claim 1, characterized in that: The nonlinear optimization solution comprises: The nonlinear equations of the oblique angle, target position and residual frequency offset obtained by back-projection positioning of different UAVs are established, as shown in equation (11): Among them: the radiation source position is represented by [x0, y0, z0], and the position of the drone numbered k is represented by [x ck ,y ck ,z ck ], The velocity vector of the UAV numbered k is expressed as [x ck ,y ck ,z ck ], is the current position vector of the UAV numbered k, expressed as 5. A distributed synthetic aperture positioning system based on backprojection, characterized in that: The system comprises: Multi-UAV configuration module: multiple UAVs are deployed along the same flight trajectory, with equal speed and equal distance; each UAV passively receives target signals through an omnidirectional antenna; Signal processing module: down-convert the received target signal into a baseband signal, de-modulate the baseband signal, extract the Doppler information of the target signal, and record the time variation of the Doppler frequency; Back-projection positioning module: Grid division of the area of ​​interest, the target area is divided into multiple grid points; Calculate the echo Doppler signal, and predict the Doppler signal of each grid point based on the grid point position and the UAV trajectory; Coherent accumulation, the Doppler signal received by the UAV is coherently accumulated with the signal phase of each grid point to form a positioning cost function; Peak search, find the peak in the cost function to obtain a preliminary estimate of the target slant angle and slant range; Nonlinear equation modeling module: Based on the back projection results of different drones and combined with the residual frequency deviation, a nonlinear equation group of target position and oblique angle is established; Nonlinear optimization solution module: uses Newton's method to solve the nonlinear equations to obtain the precise position of the target and the residual frequency offset estimate.

6. A distributed synthetic aperture positioning system based on backprojection according to claim 5, characterized in that: The multi-unmanned machine configuration and signal processing module specifically include: Three UAVs are arranged in front and behind along the flight direction. Each UAV is distributed at equal speed and distance on the same flight trajectory and equipped with an omnidirectional antenna to passively receive the signal emitted by the radiation source target, down-convert the received signal to obtain the baseband signal; de-modulate the baseband signal to obtain the corresponding Doppler signal; Assume that the instantaneous distances between the antennas of the three UAV platforms and the radiation source targets are R1(t), R2(t) and R3(t) respectively. The Doppler signals r1(t), r2(t) and r3(t) obtained after baseband demodulation processing are expressed by formulas (1)(2)(3): Among them, f c is the carrier frequency of the radiation source signal, c is the speed of light, and f1 is the fixed residual frequency deviation.

7. The distributed synthetic aperture positioning system based on back projection according to claim 5, characterized in that: The back projection positioning module comprises: The detection area of ​​interest is divided into m*n units according to the polar coordinate grid. k (t),y k (t),z k (t)], considering the influence of signal preprocessing on Doppler signal, calculate different grid points [x mn ,y mn ,z mn ], as shown in formula (4): Among them, k = 1, 2, 3 are the numbers of the drones, R mn Shows the instantaneous distance between the grid point and the platform; The Doppler signals r1(t), r2(t) and r3(t) obtained by each UAV are compared with the Doppler signal r mn The phase of (t) is coherently accumulated and the obtained correlation value is used as the grid point [x mn ,y mn ,z mn ] is shown in formula (5)(6)(7): Where: I k (θ m ,R n ) is the result of coherent accumulation of the UAV numbered k at the grid point (m,n); Search for the peak value of the positioning image and take the slant angle and slant distance corresponding to the peak position as the target position, as shown in formulas (8), (9), and (10): in, The slant angle and slant distance obtained by the backprojection positioning algorithm for the UAV numbered k.

8. The distributed synthetic aperture positioning system based on back projection according to claim 5, characterized in that: The nonlinear optimization solution module comprises: The nonlinear equations of the oblique angle, target position and residual frequency offset obtained by back-projection positioning of different UAVs are established, as shown in equation (11): Among them: the radiation source position is represented by [x0, y0, z0], and the position of the drone numbered k is represented by [x ck ,y ck ,z ck ], The velocity vector of the UAV numbered k is expressed as [x ck ,y ck ,z ck ], is the current position vector of the UAV numbered k, expressed as 9. A computer device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a distributed synthetic aperture positioning method based on back projection as claimed in any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, implements a distributed synthetic aperture positioning method based on back-projection according to any one of claims 1 to 4.

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