An effective SAR-BP motion compensation method for vehicle-mounted radar

Abstract

The application relates to the technical field of radar imaging, in particular to an effective vehicle-mounted SAR-BP motion compensation method, which comprises the following steps: obtaining echo signals, performing pulse compression on the echo signals based on transmission signals to obtain distance domain signals of SAR; selecting a reference strong point in the distance domain signals, performing upsampling processing on the reference strong point through interpolation to obtain a distance migration curve of the reference strong point; calculating a reference envelope offset correction factor, then estimating envelope offset correction factors of each distance gate, performing envelope offset correction on the distance domain signals to obtain signals compensated for slant range error; calculating a residual phase compensation factor, performing residual phase error correction on the signals compensated for slant range error to obtain signals compensated for residual phase; and performing imaging on the signals compensated for residual phase by using a BP algorithm to obtain a SAR image. The method reduces memory occupation, shortens calculation time consumption, has stronger universality and higher precision, and improves imaging quality.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of millimeter wave synthetic aperture radar imaging, and particularly relate to an effective vehicle-mounted SAR-BP motion compensation method. BACKGROUND

[0002] Millimeter wave frequency bands have significant advantages in short-range high-resolution radar imaging technology fields, such as FOD (Foreign Object Detection, vehicle-mounted road foreign object) detection, concealed target exploration, perimeter security, and the like, due to their large bandwidth characteristics and relatively short wavelengths. Compared with optical imaging, millimeter wave radar has all-weather and all-day working capabilities, and has certain penetration.

[0003] Vehicle-mounted millimeter wave SAR (Synthetic Aperture Radar) is one of effective means for realizing near-field high-resolution imaging, and can image targets at night and in foggy and rainy weather by synthesizing a large virtual aperture through the motion of the vehicle-mounted platform. The BP (Back Projection, back projection) imaging algorithm is a time-domain imaging algorithm that can accurately process arbitrary trajectory data, is very suitable for near-field imaging scenarios, and is a commonly used algorithm for vehicle-mounted millimeter wave SAR imaging. The technical key is to reversely project the pulse-compressed echo signal into the imaging grid, and the slant range measurement is strictly required.

[0004] A key challenge faced by vehicle-mounted millimeter wave SAR-BP systems in practical applications is that the inaccuracy of motion trajectory measurement leads to slant range error and phase error. In a complex vehicle-mounted environment, the vehicle-mounted platform inevitably has bumps and uneven speeds, which cause deviations between the real motion trajectory and the measured trajectory of the vehicle-mounted platform. At the same time, the millimeter wave wavelength is extremely short, which makes the radar echo signal extremely sensitive to small changes in platform position. If the slant range error and the phase error cannot be effectively corrected, they will seriously destroy the coherence of the echo signal in the BP imaging process, resulting in problems such as defocusing, geometric distortion, resolution degradation, and sidelobe level rise in the finally reconstructed image, which greatly reduces the imaging quality and target recognition ability.

[0005] In order to correct the slant range error and the phase error and improve the imaging focusing quality of the millimeter wave SAR, a self-focusing technology has been proposed by a research team, the core idea of which is to estimate and compensate the error directly from the echo data received by the radar itself without relying on external motion measurement equipment.

[0006] Ash et al. proposed an autofocus algorithm based on image sharpness maximization, which converts the phase correction problem into an ellipsoid optimization problem through geometric interpretation, projects the image sharpness maximization problem into a two-dimensional subspace spanned by auxiliary vectors, and converts it into a geometric problem of finding the farthest point on an ellipsoid from a fixed point. By eigenvalue decomposition, the optimization objective is converted into a quartic polynomial to derive a closed-form solution.

[0007] Evers et al. proposed a generalized phase gradient autofocus algorithm, which retains the four key steps of phase gradient sub-focusing (scatterer selection, phase compensation, low-pass filtering, and phase estimation), and relaxes the restriction that PGA needs to select only a single scatterer for each distance unit.

[0008] Ma et al. proposed a method that relies on a single strong scattering point to compensate for the overall echo signal, which corrects the error before imaging.

[0009] However, the inventors of the present application found that the method proposed by Ash et al. and the method proposed by Evers et al. need to store the pulse-by-pulse echo back-projection values of all pixels or calculate the matrix eigenvectors, which involves complex spectral analysis and multiple repeated imaging processes, resulting in high memory usage and long computation time. The method proposed by Ma et al. is suitable for long-range airborne scenarios, but in the near-range vehicle-mounted scenario, due to the large difference in range migration curves of points within the imaging range, using only a strong point to compensate for errors will result in good focusing effect for targets near the strong point, while targets far from the strong point appear to be out of focus, resulting in a decline in imaging quality. SUMMARY

[0010] To solve the above technical problems, the embodiments of the present application provide an effective vehicle-mounted SAR-BP motion compensation method, which can effectively compensate for signal errors in the time domain and correct errors before imaging, avoiding high memory usage and long computation time, while having stronger universality and higher precision, improving the quality of millimeter wave SAR imaging.

[0011] In a first aspect, the embodiments of the present application propose an effective vehicle-mounted SAR-BP motion compensation method, comprising: obtaining echo signals corresponding to a transmitted signal transmitted by SAR, performing pulse compression on the echo signals based on the transmitted signal to obtain a range domain signal of the SAR; selecting a reference strong point in the range domain signal, performing upsampling processing on data near the reference strong point through interpolation to obtain a range migration curve of the reference strong point; calculating a reference envelope shift correction factor of the range migration curve of the reference strong point, estimating an envelope shift correction factor of each range gate using the reference envelope shift correction factor to perform envelope shift correction on the range domain signal to obtain a signal after slant range error compensation; taking the farthest point and the nearest point of the signal after slant range error compensation as the reference strong point respectively, calculating a far-point residual phase compensation factor and a near-point residual phase compensation factor based on peak phases of range migration curves of the two reference strong points to perform residual phase error correction on the signal after slant range error compensation to obtain a signal after residual phase compensation; and performing imaging on the signal after residual phase compensation using a BP algorithm to obtain a SAR image.

[0012] The effective vehicle-mounted SAR-BP motion compensation method proposed in the present application compensates for errors in the time domain, that is, performs a time-domain autofocusing algorithm, and corrects the errors before imaging, avoiding the complex spectrum analysis and multiple repeated imaging process existing in the frequency-domain autofocusing algorithm, reducing the memory occupation and the complexity of the autofocusing algorithm, shortening the calculation time, and greatly improving the efficiency of the autofocusing algorithm. For the vehicle-mounted scene of the millimeter wave radar, the present application derives an interpolation method that does not produce phase aliasing, which can accurately obtain the range migration curve of the reference strong point. In the envelope shift correction process (i.e., slant range error compensation), the present application derives the range migration curve on each range gate based on the range migration curve of the reference strong point, generates a precise envelope shift correction factor matrix to correct the envelope shift on different range gates, and improves the accuracy of the envelope shift correction. In the residual phase compensation process, the present application selects reference strong points for the signal after envelope shift correction, thereby calculating the far-point residual phase compensation factor and the near-point residual phase compensation factor for residual phase error correction. Compared with the single-reference-point residual phase compensation method, the present application effectively improves the accuracy of residual phase compensation, achieves better focusing effect, has stronger universality and higher accuracy, and thus effectively improves the quality of millimeter wave SAR imaging.

[0013] In a second aspect, the embodiments of the present application provide an effective vehicle-mounted SAR-BP motion compensation system, comprising: a receiving processing module, a reference positioning module, a slant-range error compensation module, a residual phase compensation module and a BP imaging module; the receiving processing module is configured to obtain echo signals corresponding to transmitted signals transmitted by SAR, perform pulse compression on the echo signals based on the transmitted signals, and obtain range domain signals of the SAR; the reference positioning module is configured to select a reference strong point in the range domain signals, perform upsampling processing on data near the reference strong point through interpolation, and obtain a range migration curve of the reference strong point; the slant-range error compensation module is configured to calculate a reference envelope offset correction factor of the range migration curve of the reference strong point, estimate envelope offset correction factors of each range gate by using the reference envelope offset correction factor, perform envelope offset correction on the range domain signals, and obtain signals after slant-range error compensation; the residual phase compensation module is configured to take the farthest point and the nearest point of the signals after slant-range error compensation as reference strong points respectively, calculate a far-point residual phase compensation factor and a near-point residual phase compensation factor based on peak phases of range migration curves of the two reference strong points, perform residual phase error correction on the signals after slant-range error compensation, and obtain signals after residual phase compensation; and the BP imaging module is configured to perform imaging on the signals after residual phase compensation by using a BP algorithm, and obtain a SAR image.

[0014] In a third aspect, the embodiments of the present application provide an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the effective vehicle-mounted SAR-BP motion compensation method in the first aspect.

[0015] In a fourth aspect, the embodiments of the present application provide a computer-readable storage medium storing a computer program, and the computer program is executable by a processor to implement the effective vehicle-mounted SAR-BP motion compensation method in the first aspect.

[0016] It can be understood that the beneficial effects of the second aspect to the fourth aspect can be referred to the related description in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the following will briefly introduce the drawings required by the embodiments of the present application or the related art. Obviously, the following drawings are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained based on these drawings without creative labor. The drawings described herein are only used to explain the present application and should not be used to limit the present application.

[0018] Figure 1 is a flow chart of an effective vehicle-mounted SAR-BP motion compensation method provided in an embodiment of the present application;

[0019] Figure 2 is a model schematic diagram of a vehicle-mounted SAR platform provided in an embodiment of the present application;

[0020] Figure 3 is a schematic diagram of BP imaging results when no self-focusing is performed, provided in an embodiment of the present application;

[0021] Figure 4 is a schematic diagram of BP imaging results after envelope compensation and phase compensation using a single reference point, provided in an embodiment of the present application;

[0022] Figure 5 is a schematic diagram of BP imaging results after envelope compensation using envelope offset correction factors corresponding to each range gate and phase compensation using double reference points, provided in an embodiment of the present application;

[0023] Figure 6 is a structural schematic diagram of an effective vehicle-mounted SAR-BP motion compensation system provided in another embodiment of the present application;

[0024] Figure 7 is a structural schematic diagram of an electronic device provided in another embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the purposes, technical solutions and advantages of the embodiments of the present application more clear, the following will describe each embodiment of the present application in detail with reference to the drawings. In each embodiment of the present application, many technical details are proposed in order to make the readers better understand the present application. However, the technical solutions claimed by the present application can be realized even without these technical details and various changes and modifications based on each embodiment. The division of each embodiment is only for the convenience of description, and should not constitute any limitation on the specific implementation of the present application. Each embodiment can be combined and referenced with each other without contradiction.

[0026] One embodiment of the present application provides an effective vehicle-mounted SAR-BP motion compensation method, which is applied to an electronic device, wherein the electronic device can be a terminal or a server, and the electronic device in the embodiment and the following embodiments is taken as an example of a server. The implementation details of the effective vehicle-mounted SAR-BP motion compensation method provided in the embodiment are described in detail below, and the following details are provided for the convenience of understanding, and are not necessary for implementing the present solution.

[0027] The specific process of the effective vehicle-mounted SAR-BP motion compensation method provided in the embodiment can be as shown in Figure 1 .

[0028] Step 11: Obtain the echo signal corresponding to the transmitted signal of the SAR transmission, and perform pulse compression on the echo signal based on the transmitted signal to obtain the range domain signal of the SAR.

[0029] In a specific implementation, the server first needs to obtain the echo signal corresponding to the transmitted signal of the SAR transmission, and perform pulse compression on the echo signal based on the transmitted signal to obtain the range domain signal of the SAR. The range domain signal of the SAR is the basis for compensating the envelope deviation and the phase deviation.

[0030] In one example, the transmitted signal of the FMCW strip SAR transmission is a linear frequency modulation signal, which can be represented by the formula:

[0031] ;

[0032] ;

[0033] ;

[0034] wherein, represents the fast time, represents the slow time, represents the distance frequency modulation, represents the bandwidth of the transmitted signal, represents the pulse duration of the transmitted signal, represents a rectangular window function, represents the center frequency, represents the transmitted signal, the frequency of , .

[0035] For a point target , the echo signal corresponding to the transmitted signal is represented by the formula:

[0036] ;

[0037] wherein, denotes the speed of light, denotes the time delay, denotes the distance, denotes the echo signal corresponding to the transmitted signal for a point target .

[0038] with as the reference signal, the received signal is multiplied by the conjugate of the reference signal according to the Dechirp principle, i.e. the intermediate frequency signal, which is expressed by the formula:

[0039] .

[0040] wherein, denotes the carrier wavelength, , denotes the intermediate frequency signal.

[0041] The first two exponential terms in the intermediate frequency signal are the Doppler term and the distance term, respectively, which contain the information required for two-dimensional imaging, and the last exponential term is the RVP term introduced in the Dechirp processing, which is an error term not required for two-dimensional imaging processing and can be eliminated by filtering processing in the distance domain.

[0042] The RVP term is eliminated by filtering processing in the distance domain, i.e. the base frequency signal after elimination of the RVP term is obtained, which can be expressed by the formula:

[0043] .

[0044] wherein, and denote the Fourier transform and the inverse Fourier transform, respectively, denotes the distance frequency, , denotes the base frequency signal. The formula is the time domain echo signal model of FMCW strip SAR, which is the basis for signal analysis.

[0045] Finally, the is subjected to a fast Fourier transform along the fast time , i.e. the distance domain signal of FMCW strip SAR is obtained, which is expressed by the formula:

[0046] .

[0047] wherein, denotes the distance domain signal, the signal dimension of which is , denotes the number of distance dimension sampling points, denotes the number of azimuth dimension sampling points, This represents the Singer function.

[0048] Step 12: Select a reference strong point in the range domain signal, and perform upsampling on the data near the reference strong point through interpolation to obtain the range migration curve of the reference strong point.

[0049] In the specific implementation, after the server obtains the SAR range domain signal, it can select a reference strong point in the range domain signal, and perform upsampling processing on the data near the reference strong point through interpolation to obtain the range migration curve of the reference strong point.

[0050] In one example, let the original sampling interval be... Let the sampling interval after upsampling be... .

[0051] The first condition needs to be met. ,Right now .

[0052] based on , Based on the first condition, the upsampling factor can be derived. .

[0053] .

[0054] Select a reference strong point in the distance domain signal, based on the upsampling factor. By upsampling the data near the reference strength point through interpolation, the dimension of the reference strength point can be obtained. Distance migration curve .

[0055] Step 13: Calculate the reference envelope offset correction factor of the distance migration curve of the reference strong point, and use the reference envelope offset correction factor to estimate the envelope offset correction factor of each range gate in order to perform envelope offset correction on the range domain signal and obtain the signal after slant range error compensation.

[0056] In the specific implementation, after obtaining the distance migration curve of the reference strong point, the server needs to calculate the reference envelope offset correction factor of the distance migration curve of the reference strong point, and use the reference envelope offset correction factor to estimate the envelope offset correction factor of each range gate in order to perform envelope offset correction on the range domain signal and obtain the signal after slant range error compensation.

[0057] In one example, let The ideal distance migration curve of the reference strong point under ideal motion trajectory (ideal state) has the following dimension: The server can use the following formula to determine the distance migration curve based on the reference strong point. and The reference envelope offset correction factor of the distance migration curve of the reference strong point is calculated:

[0058] ;

[0059] in, Indicates the reference envelope offset correction factor. The dimension is , is used to represent the deviation between the actual distance migration curve and the ideal distance migration curve of the reference strong point at each azimuth point.

[0060] Next, the server uses the reference envelope offset correction factor Estimate the envelope offset correction factor for each range gate, generate the envelope offset correction factor matrix for the range migration curve, and then compensate the envelope offset of the range migration curve on the corresponding range gate based on the envelope offset correction factor matrix to obtain the signal after slant range error compensation.

[0061] In one example, considering the short radar range in a vehicle-mounted scenario, the envelope offset correction factors of the range migration curves at different range gates vary significantly. Therefore, it is unscientific to use only the range migration curve of the reference strong point to correct the envelope offset error of the range migration curves at all range gates. The server needs to use the envelope offset correction factor of the reference strong point's range migration curve to estimate the envelope offset correction factor of the range migration curve for each range gate, generate the envelope offset correction factor matrix of the range migration curves, and then compensate for the envelope offset of the range migration curves at the corresponding range gates. The server can establish the error model of the vehicle-mounted platform as follows: Figure 2 As shown.

[0062] set up Indicates the ideal location of the vehicle platform, located at On the axis, set This indicates the actual location of the vehicle platform, located at... In the plane, let Let the position of the nearby target be the closest point. The location of a distant target, i.e., the farthest point, is where both the nearest and farthest points are located. On the axis, the coordinates of the nearest point are The coordinates of the farthest point are , The coordinates are .

[0063] The vibration of the vehicle platform originates from speed instability and vehicle body bumps. Speed ​​instability causes... Error on the shaft The bumps of the car body produce Error on the shaft ,but The coordinates compared to In terms of There is a slight offset on the plane. The coordinates are .

[0064] If the server chooses the farthest point as the reference strong point, then the actual slope distance at the farthest point can be expressed as: The actual slope distance at the nearest point can be expressed as .

[0065] and It can be represented as:

[0066] ;

[0067] ;

[0068] Based on this, we obtain and The relationship between them is:

[0069] .

[0070] Similarly, it can be deduced that the first... The actual slope distance of the gate is .

[0071] .

[0072] Next, following the order of the distance gates, and based on the actual slope distance of each distance gate, the dimension is formed as follows: Actual slant range matrix , .

[0073] Let the first The ideal slope distance of the gate is , It can be represented as:

[0074] .

[0075] Based on the ideal slant distance of each distance gate, and following the order of the distance gates, the dimensions are formed as follows: Ideal slant distance matrix , .

[0076] based on and The envelope offset correction factor matrix of the distance migration curve can then be calculated. , .

[0077] Finally, the envelope offset of the range migration curve on the corresponding range gate can be compensated based on the envelope offset correction factor matrix, to obtain the slant range error compensated signal by the following formula:

[0078] ;

[0079] wherein, represents the slant range error compensated signal, at this time, the maximum error between the estimated slant range and the ideal slant range is .

[0080] Step 14, respectively, the farthest point and the nearest point of the slant range error compensated signal are taken as reference strong points, and the far point residual phase compensation factor and the near point residual phase compensation factor are calculated based on the peak value phase of the distance migration curve of the two reference strong points, to correct the residual phase error of the slant range error compensated signal, to obtain the residual phase compensated signal.

[0081] In a specific implementation, after completing the slant range error compensation (envelope offset correction), the server needs to respectively take the farthest point and the nearest point of the slant range error compensated signal as reference strong points, and calculate the far point residual phase compensation factor and the near point residual phase compensation factor based on the peak value phase of the distance migration curve of the two reference strong points, to correct the residual phase error of the slant range error compensated signal, to obtain the residual phase compensated signal.

[0082] It can be understood that the slant range error compensated signal is at the correct projection position, but the phase does not meet the consistency, and cannot be coherently integrated (coherent superposition), so the remaining phase error caused by the motion error needs to be corrected to ensure that the signal achieves the same direction superposition when coherently integrated.

[0083] In one example, the server first takes the farthest point of the slant range error compensated signal as the reference strong point, to obtain the peak value phase of the distance migration curve when the farthest point is taken as the reference strong point ;

[0084] ;

[0085] wherein, represents the phase angle.

[0086] Suppose that the ideal peak value phase of the ideal distance migration curve when the farthest point is taken as the reference strong point in the ideal state is , which is expressed by the formula as:

[0087] .

[0088] Based on and , the far point residual phase compensation factor , the far point residual phase compensation factor is expressed by the formula:

[0089] .

[0090] The residual phase error is related to the distance, so the segmented residual phase error correction is performed on the envelope offset corrected signal, instead of using only the farthest point as the reference strong point to compensate for all signals.

[0091] After calculating the far point residual phase compensation factor , the server takes the nearest point of the slant range error compensated signal as the reference strong point, and obtains the peak phase of the distance migration curve when the nearest point is taken as the reference strong point , is expressed by the formula:

[0092] .

[0093] Suppose that the ideal peak phase of the ideal distance migration curve when the nearest point is taken as the reference strong point in the ideal state is , is expressed by the formula:

[0094] .

[0095] Based on and , the near point residual phase compensation factor , the near point residual phase compensation factor , .

[0096] Finally, the server performs residual phase error correction on the slant range error compensated signal based on and by the following formula, to obtain the residual phase compensated signal:

[0097] ;

[0098] wherein, represents the residual phase compensated signal.

[0099] Step 15, imaging the residual phase compensated signal by using the BP algorithm to obtain a SAR image.

[0100] In a specific implementation, after the envelope offset correction and the residual phase error correction are completed, the server can use the BP algorithm to image the signal compensated for the residual phase, thereby obtaining the SAR image of the FMCW strip.

[0101] In one example, the BP algorithm is pixel-by-pixel imaging, and therefore the observed scene needs to be divided into a plurality of grid cells, and the distance direction interval and the azimuth direction interval of the divided grid cells are respectively less than the distance direction resolution and the azimuth direction resolution.

[0102] The server calculates the instantaneous slant range of all the grid cells at the time t , , , , projects the instantaneous slant range at the time t into the imaging network, then performs azimuth direction phase compensation to obtain the sub-image at the time t ,

[0103] , , , .

[0104] Finally, the server coherently superimposes the sub-images at all azimuth times, thereby obtaining the SAR image of the FMCW strip , .

[0105] The effective vehicle-mounted SAR-BP motion compensation method proposed in this embodiment compensates the error of the signal in the time domain, that is, performs the time-domain self-focusing algorithm, and the error correction is completed before imaging, avoiding the complex spectrum analysis and the process of multiple repeated imaging existing in the frequency-domain self-focusing algorithm, reducing the memory occupation and the complexity of the self-focusing algorithm, shortening the time consumption of calculation, and greatly improving the efficiency of the self-focusing algorithm. In the vehicle-mounted scene of the millimeter wave radar, the interpolation method which does not produce phase aliasing is derived in this embodiment, and the distance migration curve of the reference strong point can be accurately obtained. In the process of envelope offset correction (i.e. slant range error compensation), the distance migration curve of each distance gate is derived based on the distance migration curve of the reference strong point in this embodiment, and a precise envelope offset correction factor matrix is generated to correct the envelope offset of different distance gates, thereby improving the accuracy of the envelope offset correction. In the process of residual phase compensation, the reference strong point is selected by segmenting the signal after envelope offset correction, and the far point residual phase compensation factor and the near point residual phase compensation factor are calculated to perform residual phase error correction. Compared with the single reference strong point residual phase compensation method, the accuracy of residual phase compensation is effectively improved, a better focusing effect is achieved, and the method has stronger universality and higher accuracy, thereby effectively improving the quality of millimeter wave SAR imaging.

[0106] Millimeter wave radars are increasingly used in vehicle-mounted SAR scenes, but the envelope deviation and phase deviation caused by uneven speed, jolting and other problems of the vehicle-mounted platform cannot be ignored. In the imaging process, these deviations will cause the SAR image to be seriously out of focus, so it is necessary to correct the envelope deviation and phase deviation of the echo signal. This embodiment simulates the error model in the vehicle-mounted foreign object monitoring scene, and derives accurate envelope offset compensation and distance dimension segmented residual error compensation in the millimeter wave band, thereby improving the accuracy of envelope deviation and phase deviation compensation and the quality of SAR imaging results.

[0107] The effective vehicle-mounted SAR-BP motion compensation method proposed in this embodiment is suitable for airport foreign object monitoring, border patrol, road and bridge safety monitoring and other scenes. The high precision and all-weather characteristics of the vehicle-mounted SAR make it one of the key technologies for target detection and identification. In order to more accurately detect and identify targets, it is necessary to compensate the envelope deviation and phase deviation of the echo signal. The technical solution proposed in this embodiment can effectively correct the errors caused by uneven speed, jolting and other problems of the vehicle-mounted platform, has the advantages of low complexity and good effect, and has practical application value and wide application scenarios.

[0108] The step division of the above various methods is only for the purpose of clear description, and in implementation, one step can be combined or some steps can be divided into multiple steps, as long as the same logical relationship is included, and the application is within the protection scope. Irrelevant modifications or irrelevant designs are added to the algorithm or flow, but the core design of the algorithm and flow is within the protection scope of the application.

[0109] In one embodiment, in order to verify the effectiveness of the effective vehicle-mounted SAR-BP motion compensation method proposed in the application, we carried out relevant simulation experiments, and compared the BP imaging results without self-focusing, the BP imaging results after envelope compensation and phase compensation using a single reference point, and the BP imaging results obtained by the application. The BP imaging results without self-focusing can be as shown in Figure 3 , the BP imaging results after envelope compensation and phase compensation using a single reference point can be as shown in Figure 4 , and the BP imaging results after envelope compensation using the envelope offset correction factor corresponding to each range gate for correction and phase compensation using double reference points (i.e. the BP imaging results obtained by the application) can be as shown in Figure 5 . The envelope compensation and phase compensation using a single reference point and the focusing result analysis of the application are shown in Table 1.

[0110] Table 1: Envelope compensation and phase compensation using a single reference point and focusing result analysis of the application

[0111]

[0112] Based on Figure 3 , Figure 4 , Figure 5 and Table 1, it can be seen that the compensation method proposed in the application obtains the best focusing effect and can greatly improve the quality of SAR imaging.

[0113] Correspondingly, another embodiment of the application proposes an effective vehicle-mounted SAR-BP motion compensation system. The implementation details of the effective vehicle-mounted SAR-BP motion compensation system proposed in this embodiment are specifically described below. The following details are provided for the convenience of understanding, and are not necessary for implementing this embodiment. Figure 6 is a structural schematic diagram of an effective vehicle-mounted SAR-BP motion compensation system proposed in this embodiment. The system includes a receiving processing module 21, a reference positioning module 22, a slant range error compensation module 23, a residual phase compensation module 24, and a BP imaging module 25.

[0114] The receiving processing module 21 is configured to acquire echo signals corresponding to the transmitted signals transmitted by the SAR, and perform pulse compression on the echo signals based on the transmitted signals to obtain distance domain signals of the SAR.

[0115] The reference positioning module 22 is configured to select a reference strong point in the distance domain signals, and perform upsampling processing on data near the reference strong point by interpolation to obtain a range migration curve of the reference strong point.

[0116] The slant-range error compensation module 23 is configured to calculate a reference envelope offset correction factor of the range migration curve of the reference strong point, and estimate envelope offset correction factors of each range gate by using the reference envelope offset correction factor to perform envelope offset correction on the distance domain signals to obtain signals after slant-range error compensation.

[0117] The residual phase compensation module 24 is configured to take the farthest point and the nearest point of the signals after slant-range error compensation as reference strong points respectively, calculate a far-point residual phase compensation factor and a near-point residual phase compensation factor based on peak phases of range migration curves of the two reference strong points, and perform residual phase error correction on the signals after slant-range error compensation to obtain signals after residual phase compensation.

[0118] The BP imaging module 25 is configured to perform imaging on the signals after residual phase compensation by using a BP algorithm to obtain a SAR image.

[0119] It is worth mentioning that each module involved in the embodiment is a logical module, and in actual application, one logical unit can be one physical unit, or a part of one physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the present application, units not closely related to solving the technical problems proposed in the present application are not introduced in the embodiment, but this does not mean that there are no other units in the embodiment.

[0120] It can be found that the embodiment is a system embodiment corresponding to the above-mentioned method embodiment, and the embodiment can be implemented in cooperation with the above-mentioned method embodiment. The related technical details and technical effects mentioned in the above-mentioned method embodiment are still valid in the embodiment. In order to reduce repetition, they will not be described here again. The related technical details mentioned in the embodiment can also be applied to the above-mentioned method embodiment.

[0121] Another embodiment of the present application provides an electronic device, and a specific structure of the electronic device is as follows. Figure 7As shown, it comprises: at least one processor 31; and a memory 32 connected in communication with the at least one processor 31; wherein the memory 32 stores instructions executable by the at least one processor 31, and the instructions are executed by the at least one processor 31 to enable the at least one processor 31 to perform an effective vehicle-mounted SAR-BP motion compensation method as described in the above method embodiments.

[0122] The bus can include any number of interconnecting buses and bridges, and the bus links various circuits of the processor and the memory together. The bus can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, and therefore, not described further. The bus interface is responsible for providing an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as a plurality of receivers and transmitters, which provides a means for communicating with various other apparatus over a transmission medium.

[0123] The processor is responsible for managing the bus and general processing, and can also provide various functions including timing, peripheral interface, voltage regulation, power management, and other control functions. The memory can be used for storing data used by the processor when executing operations.

[0124] Another embodiment of the present application provides a computer readable storage medium storing a computer program, which, when executed by a processor, can implement an effective vehicle-mounted SAR-BP motion compensation method as described in the above method embodiments.

[0125] That is, those skilled in the art can understand that all or part of the steps in the above method embodiments can be instructed by a program to be completed by relevant hardware, and the program is stored in a storage medium, including a plurality of instructions for causing a device (such as a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps in the above method embodiments. The storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various storage medium capable of storing program codes.

[0126] Those skilled in the art can understand that the above embodiments are specific embodiments for implementing the present application, and in actual applications, various changes can be made in form and details without departing from the spirit and scope of the present application.

Claims

1. An effective vehicle-mounted SAR-BP motion compensation method, characterized in that, include: The echo signal corresponding to the transmitted signal of the SAR is obtained, and the echo signal is pulse compressed based on the transmitted signal to obtain the range domain signal of the SAR. In the range domain signal, a reference strong point is selected, and the data near the reference strong point is upsampled by interpolation to obtain the range migration curve of the reference strong point. Calculate the reference envelope offset correction factor of the range migration curve of the reference strong point, and use the reference envelope offset correction factor to estimate the envelope offset correction factor of each range gate in order to perform envelope offset correction on the range domain signal and obtain the signal after slant range error compensation. The farthest and nearest points of the slant range error-compensated signal are taken as reference strong points respectively. Based on the peak phase of the distance migration curves of the two reference strong points, the residual phase compensation factor at the far point and the residual phase compensation factor at the near point are calculated to correct the residual phase error of the slant range error-compensated signal and obtain the signal after residual phase compensation. The BP algorithm is used to image the signal after residual phase compensation to obtain a SAR image; The BP algorithm is used to image the residual phase-compensated signal to obtain a SAR image, including: The observation scene is divided into several grid cells, and the range interval and azimuth interval of the divided grid cells are smaller than the range resolution and azimuth resolution, respectively. Calculate all grid cells in Instantaneous slant distance at time and will signal after residual phase compensation at time 1 according to The image is projected onto an imaging network, followed by azimuth phase compensation, to obtain... Sub-image of time, Indicates slow time. Indicates distance frequency, The azimuth phase compensation function at time is , ; The SAR image is obtained by coherently overlaying the sub-images at all azimuth times. ; , This indicates the number of sampling points in the azimuth dimension.

2. The effective vehicle-mounted SAR-BP motion compensation method according to claim 1, characterized in that, Obtain the echo signal corresponding to the transmitted signal from the SAR, and perform pulse compression on the echo signal based on the transmitted signal to obtain the range domain signal of the SAR, including: The transmitted signal from a SAR is a linear frequency modulated signal, which can be expressed by the formula: ； ； in, Indicates a fast time. Indicates slow time. Indicates the distance-directed frequency modulation. Indicates the bandwidth of the transmitted signal. Indicates the pulse duration of the transmitted signal. Represents a rectangular window function. Indicates the center frequency. Indicates the transmission of a signal; For point targets In other words, the echo signal corresponding to the transmitted signal can be expressed by the formula: ； in, Represents the speed of light. Indicates time delay. Indicates distance, Indicates a point target In other words, the echo signal corresponding to the transmitted signal; by As a reference signal, according to the Decirp principle, the received signal is multiplied by the conjugate of the reference signal to obtain the intermediate frequency (IF) signal, which is expressed by the formula: ； in, Indicates the carrier wavelength. , Indicates intermediate frequency signal; right Filtering is performed in the range domain to eliminate the RVP term, resulting in the fundamental frequency signal after RVP term elimination. The fundamental frequency signal is expressed by the formula: ； in, and These represent the Fourier transform and the inverse Fourier transform, respectively. Indicates distance frequency, , Indicates the baseband signal; Will Along fast time Performing a Fast Fourier Transform (FFT) yields the SAR range domain signal, which can be expressed by the formula: ； in, This represents a distance-domain signal with a signal dimension of . , Indicates the number of sampling points in the distance dimension. This indicates the number of sampling points in the azimuth dimension. This represents the Singer function.

3. An effective vehicle-mounted SAR-BP motion compensation method according to claim 2, characterized in that, A reference strong point is selected in the range domain signal. Data near the reference strong point is upsampled using interpolation to obtain the range migration curve of the reference strong point, including: Let the original sampling interval be Let the sampling interval after upsampling be... ; The first condition needs to be met. ,Right now ; based on , Based on the first condition, the upsampling factor is derived. ; Select a reference strong point in the distance domain signal, based on the upsampling factor. By upsampling the data near the reference strong point through interpolation, the dimension of the reference strong point is obtained. Distance migration curve .

4. An effective vehicle-mounted SAR-BP motion compensation method according to claim 3, characterized in that, Calculate the reference envelope offset correction factor of the range migration curve of the reference strong point, and use the reference envelope offset correction factor to estimate the envelope offset correction factor of each range gate to perform envelope offset correction on the range domain signal, obtaining the signal after slant range error compensation, including: The distance migration curve based on the reference strong point is obtained using the following formula. The ideal distance migration curve of the reference strong point under ideal conditions The reference envelope offset correction factor of the distance migration curve of the reference strong point is calculated: ； in, Indicates the reference envelope offset correction factor; The envelope offset correction factor for each range gate is estimated using the reference envelope offset correction factor, and the envelope offset correction factor matrix of the range migration curve is generated. Based on the envelope offset correction factor matrix, the envelope offset of the range migration curve on the corresponding range gate is compensated to obtain the signal after slant range error compensation.

5. An effective vehicle-mounted SAR-BP motion compensation method according to claim 4, characterized in that, The envelope offset correction factor for each range gate is estimated using the reference envelope offset correction factor, generating the envelope offset correction factor matrix for the range migration curve, including: set up Indicates the ideal location of the vehicle platform, located at On the axis, set This indicates the actual location of the vehicle platform, located at... In the plane, let Let the location of the nearby target be the closest point. The location of a distant target, i.e., the farthest point, is where both the nearest and farthest points are located. On the axis, the coordinates of the nearest point are The coordinates of the farthest point are , The coordinates are ; The vibration of the vehicle platform originates from speed instability and vehicle body bumps. Speed ​​instability causes... Error on the shaft The bumps of the car body produce Error on the shaft ,but The coordinates compared to In terms of There is a slight offset on the plane. The coordinates are ; If the farthest point is selected as the reference strong point, then the actual slope distance at the farthest point is... The actual slope distance at the nearest point is ; ； ； Based on this, we obtain and The relationship between them is: ； Similarly, we obtain the first... The actual slope distance of the gate is ; ； Based on the actual slant distance of each distance gate, and following the order of the gates, the dimensions are: Actual slant range matrix , ; Let the first The ideal slope distance of the gate is : ； Based on the ideal slant distance of each distance gate, and following the order of the distance gates, the dimensions are formed as follows: Ideal slant distance matrix , ; based on and The envelope offset correction factor matrix of the distance migration curve is calculated. , ; The envelope offset of the range migration curve on the corresponding range gate is compensated using the following formula based on the envelope offset correction factor matrix, resulting in the signal after slant range error compensation: ； in, This represents the signal after slant distance error compensation.

6. An effective vehicle-mounted SAR-BP motion compensation method according to claim 5, characterized in that, Using the farthest and nearest points of the range-error-compensated signal as reference strong points, and based on the peak phases of the distance migration curves of the two reference strong points, residual phase compensation factors for the far point and the near point are calculated to correct the residual phase error of the range-error-compensated signal, resulting in the residual phase-compensated signal, including: Using the farthest point of the signal after slant range error compensation as the reference strong point, the peak phase of the range migration curve when the farthest point is used as the reference strong point is obtained. ; ； in, This indicates the calculation of the phase angle; Let the ideal peak phase of the ideal distance migration curve be, under ideal conditions, when the farthest point is used as the reference strong point. ; ； based on and The residual phase compensation factor at the far point is obtained. ; ； Using the nearest point of the range error-compensated signal as the reference strong point, the peak phase of the range migration curve when the nearest point is used as the reference strong point is obtained. ; ； Let the ideal peak phase of the ideal distance migration curve be, under ideal conditions, when the nearest point is used as the reference strong point. ; ； based on and The near-point residual phase compensation factor is obtained. ; ； Based on the following formula, and The residual phase error is corrected after the slant range error is compensated to obtain the signal with residual phase compensation: ； in, This represents the signal after residual phase compensation.

7. An effective vehicle-mounted SAR-BP motion compensation system, characterized in that, include: The receiving and processing module is used to acquire the echo signal corresponding to the transmitted signal of the SAR, and to perform pulse compression on the echo signal based on the transmitted signal to obtain the range domain signal of the SAR. The reference positioning module is used to select a reference strong point in the range domain signal, and to upsample the data near the reference strong point through interpolation to obtain the distance migration curve of the reference strong point. The slant range error compensation module is used to calculate the reference envelope offset correction factor of the distance migration curve of the reference strong point, and to estimate the envelope offset correction factor of each range gate using the reference envelope offset correction factor in order to perform envelope offset correction on the range domain signal and obtain the signal after slant range error compensation. The residual phase compensation module is used to take the farthest point and the nearest point of the signal after slant range error compensation as reference strong points, respectively. Based on the peak phase of the distance migration curve of the two reference strong points, the module calculates the residual phase compensation factor at the far point and the residual phase compensation factor at the near point to correct the residual phase error of the signal after slant range error compensation, and obtains the signal after residual phase compensation. The BP imaging module is used to image the signal after residual phase compensation using the BP algorithm to obtain SAR images; The BP algorithm is used to image the residual phase-compensated signal to obtain a SAR image, including: The observation scene is divided into several grid cells, and the range interval and azimuth interval of the divided grid cells are smaller than the range resolution and azimuth resolution, respectively. Calculate all grid cells in Instantaneous slant distance at time and will signal after residual phase compensation at time 1 according to The image is projected onto an imaging network, followed by azimuth phase compensation, to obtain... Sub-image of time, Indicates slow time. Indicates distance frequency, The azimuth phase compensation function at time is , ; The SAR image is obtained by coherently overlaying the sub-images at all azimuth times. ; , This indicates the number of sampling points in the azimuth dimension.

8. An electronic device, characterized in that, include: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform an effective vehicle-mounted SAR-BP motion compensation method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it can implement an effective vehicle-mounted SAR-BP motion compensation method as described in any one of claims 1 to 6.

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