SAR-GMTI Range Ambiguity Suppression Method Based on Non-Uniform Sub-Pulse Coding

Abstract

The present invention discloses a method for suppressing range ambiguity in SAR-GMTI based on non-uniform sub-pulse coding, including: acquiring multi-channel received data of a non-uniform sub-pulse coded synthetic aperture radar NSPC-SAR by using a receiving array; performing band-pass filtering and range pulse compression processing on the multi-channel received data to achieve primary range ambiguity suppression and sub-pulse separation, and obtaining a result of the first-stage processing of the echo; using digital beamforming technology to perform secondary range ambiguity suppression on the result of the first-stage processing of the echo to obtain an ambiguity-free echo; imaging the ambiguity-free echo, and performing moving target detection based on the imaging result to obtain NSPC-SAR ground moving target indication SAR-GMTI. The present invention can effectively suppress range ambiguity, thereby improving the detection performance of moving targets and enhancing robustness.

Description

Technical Field

[0001] The invention belongs to the field of signal technology, and in particular relates to a SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding. Background Art

[0002] With the improvement of SAR (Synthetic Aperture Radar) resolution, the demand for increasing the width of the mapping swath is becoming increasingly urgent. HRWS (High-Resolution and Wide Swath) has become one of the current research hotspots.

[0003] In SAR systems, the azimuth direction requires a high PRF (Pulse Repetition Frequency ， The HRWS is sampled at a pulse repetition frequency (PRF) to ensure a large Doppler bandwidth and high azimuth resolution. At the same time, a low PRF needs to be selected in the range direction to ensure that there is no range ambiguity within the surveying swath. Due to the limitation of the minimum antenna area, the increase in the width of the surveying swath comes at the expense of the azimuth resolution. The contradiction between the two makes it impossible for the superiority of HRWS to be apparent. As the width of the surveying swath increases, targets from different distance areas will not be able to be separated, resulting in range ambiguity. The aliasing of clutter in multiple range ambiguity areas will interfere with the desired signal, which is not conducive to subsequent target detection and imaging. In addition, moving targets in different range ambiguity areas will be defocused, resulting in a significant decrease in the signal-to-noise ratio. In particular, slow targets will be submerged in clutter, affecting the ground moving target indication performance. Therefore, it is crucial to solve the range ambiguity problem in SAR.

[0004] In order to solve the distance ambiguity problem, the existing technology is based on FDA-MIMO (Frequency Diversity array Multiple-Input Multiple-Output), which modulates the frequency difference, delay and phase relationship between the transmission channels to make the time-space coupling information difference of the ambiguous targets at different distances, and proposes a series of processing methods on this basis. However, the assumption of the MIMO system is to transmit an ideal orthogonal waveform, which is difficult to achieve in practical applications. In order to break through the limitation of the waveform, the existing technology also proposes an extended azimuth phase coding waveform to enable the ambiguous echo to be separated in the transmission space-frequency domain. However, continuous pitch beam switching will consume time resources.

[0005] It can be seen that the above method still cannot effectively deal with the mid-range ambiguity suppression of SAR-GMTI, and has high requirements on the transmission waveform and system resources, and its scope of application is limited. Summary of the invention

[0006] To solve the above problems existing in the prior art, the present invention provides a method for suppressing range ambiguity of SAR-GMTI based on non-uniform sub-pulse coding. The technical problems to be solved by the present invention are achieved through the following technical solutions:

[0007] The present invention provides a method for suppressing range ambiguity of SAR-GMTI based on non-uniform sub-pulse coding, including:

[0008] Obtaining multi-channel received data of a non-uniform sub-pulse coded synthetic aperture radar NSPC-SAR by using a receiving array;

[0009] Performing band-pass filtering and range pulse compression processing on the multi-channel received data to achieve primary range ambiguity suppression and sub-pulse separation, and obtaining a primary processing result of the echo;

[0010] Performing secondary range ambiguity suppression on the primary processing result of the echo by using digital beamforming technology to obtain an ambiguity-free echo;

[0011] Performing imaging on the ambiguity-free echo and performing moving target detection according to the imaging result to obtain NSPC-SAR ground moving target indication SAR-GMTI.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0013] 1. The method for suppressing range ambiguity of SAR-GMTI based on non-uniform sub-pulse coding provided by the present invention can enable the radar beam to automatically scan with non-uniform pointing in the elevation dimension through the joint coding of multi-frequency sub-pulses and spatial transmitting array elements. The specific design of parameters such as non-uniform modulation coefficients can direct the beam to the desired direction to obtain an imaging area with wide coverage. At the receiving end, by using a band-pass filter and digital beamforming (DBF) technology based on data reconstruction, the separation of echo signals and range ambiguity suppression are realized. This method effectively suppresses range ambiguity, improves the performance of moving target detection, and enhances the system robustness.

[0014] 2. The method for suppressing range ambiguity of SAR-GMTI based on non-uniform sub-pulse coding provided by the present invention does not require the transmitted waveform to satisfy orthogonality. By utilizing range-frequency domain resources, it is easy to realize the separation of sub-pulses, can effectively increase the imaging swath, can obtain an ambiguity-free imaging result, is easy to implement in engineering, has a good result for moving target detection, and is applicable to future multi-channel SAR-GMTI systems.

[0015] The following will further elaborate on the present invention in detail with reference to the accompanying drawings and embodiments. Description of the Drawings

[0016] Figure 1It is a flowchart of a SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding provided by an embodiment of the present invention;

[0017] Figure 2 It is a schematic diagram of the position of a point target in the first range ambiguity region provided by an embodiment of the present invention;

[0018] Figure 3 It is a schematic diagram of the result of multi-channel received data in the range frequency domain - azimuth time domain provided by an embodiment of the present invention;

[0019] Figure 4 It is a schematic diagram of the result of extracting the first sub-pulse after band-pass filtering provided by an embodiment of the present invention;

[0020] Figure 5 It is a schematic diagram of the range pulse compression result in the prior art;

[0021] Figure 6 It is a schematic diagram of the result of directly imaging multi-channel received data in the prior art;

[0022] Figure 7 It is a schematic diagram of the result of taking an azimuth slice after range pulse compression of the first sub-pulse provided by an embodiment of the present invention;

[0023] Figure 8 It is a schematic diagram of the result after secondary range ambiguity suppression of the first sub-pulse provided by an embodiment of the present invention;

[0024] Figure 9 It is a schematic diagram of the imaging result of the first range ambiguity region provided by an embodiment of the present invention;

[0025] Figure 10 It is a schematic diagram of the result before and after clutter suppression in the first range ambiguity region provided by an embodiment of the present invention;

[0026] Figure 11 It is a schematic diagram of the imaging result when the beam points to the second range ambiguity region in the prior art;

[0027] Figure 12 It is a schematic diagram of the imaging result of the first range ambiguity region and the results of moving target detection and repositioning provided by an embodiment of the present invention;

[0028] Figure 13 It is a schematic diagram of the imaging result of the second range ambiguity region and the results of moving target detection and repositioning provided by an embodiment of the present invention;

[0029] Figure 14 It is a schematic diagram of the imaging result of the third range ambiguity region and the results of moving target detection and repositioning provided by an embodiment of the present invention. Detailed implementation manners

[0030] The present invention will be further described in detail below in conjunction with specific embodiments, but the implementation manners of the present invention are not limited thereto.

[0031] Figure 1 It is a flowchart of a SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding provided by an embodiment of the present invention. As Figure 1 shown, an embodiment of the present invention provides a SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding, including:

[0032] S1. Using a receiving array to obtain multi-channel received data of a non-uniform sub-pulse coded synthetic aperture radar NSPC-SAR;

[0033] S2. Performing band-pass filtering and range pulse compression processing on the multi-channel received data to achieve primary range ambiguity suppression and sub-pulse separation, and obtaining a primary processing result of the echo;

[0034] S3. Using digital beamforming technology to perform secondary range ambiguity suppression on the primary processing result of the echo to obtain an unambiguous echo;

[0035] S4. Imaging the unambiguous echo and performing moving target detection according to the imaging result to obtain NSPC-SAR ground moving target indication SAR-GMTI.

[0036] Specifically, after obtaining the multi-channel received data of NSPC-SAR in this embodiment, primary range ambiguity suppression and sub-pulse separation are performed on the multi-channel received data through band-pass filtering and range pulse compression processing to obtain a primary processing result of the echo; then, based on DBF (Digital Beam Forming) technology, secondary range ambiguity suppression is performed on the primary processing result of the echo to obtain an unambiguous echo; finally, the unambiguous echo is imaged, and a robust principal component analysis algorithm is used to achieve moving target detection to obtain NSPC-SAR ground moving target indication SAR-GMTI.

[0037] Optionally, the multi-channel received data is:

[0038]

[0039] where t represents fast time, t k represents azimuth slow time, σ t,i represents the moving target scattering point coefficient in the i-th sub-pulse, w a (·) represents an azimuth window function, R0 represents the vertical distance from the moving target to the carrier platform track, v r represents v y projected onto the slant range plane of the moving target speed, v yis the velocity of the moving target perpendicular to the track of the carrier platform, v e represents the relative velocity between the NSPC-SAR and the moving target, x0 represents the initial azimuth coordinate of the moving target, v represents the velocity of the carrier platform, d represents the spacing between any adjacent transmitting channels and any adjacent receiving channels, and c is the speed of light. represents the instantaneous slant range between the m-th transmitting channel and the moving target, m = 1, …, M, Tr represents transmission. represents the instantaneous slant range between the receiving channel at the q-th row and the n-th column in the receiving array and the moving target, q = 1, …, M, n = 1, …, N, Re represents reception, s m,i (·) represents the i-th sub-pulse transmitted by the m-th transmitting channel, i = 1, …, P. represents the multi-channel received data of the moving target tar in the i-th sub-pulse received by the receiving channel at the q-th row and the n-th column.

[0040] Specifically, when the NSPC-SAR operates in the squint imaging mode, the X-axis is established based on the projection of the carrier platform's motion direction on the ground. The flight altitude of the carrier platform is H, the speed is v, and the swath width is W. g The receiving array is a uniform planar array with M rows and N columns and shared transmit and receive. The spacing between any two adjacent transmitting channels and any two adjacent receiving channels is d. At the transmitting end, each transmitting channel in each row transmits the same sub-pulse. After the sub-array synthesis of the transmitting channels in each row, the transmitting array can be equivalent to a uniform linear array with M channels. At the receiving end, all receiving channels jointly receive the multi-channel received data.

[0041] Since the transmitting array can be equivalent to a linear array with M channels, the instantaneous slant range between the m-th (m = 1, …, M) transmitting channel and the moving target can be expressed as:

[0042]

[0043] where t k represents the azimuth slow time. When t k = 0, the ground coordinates of the moving target are (x0, y0, 0), φ A represents the antenna tilt angle in the elevation dimension, v y represents the velocity of the moving target perpendicular to the carrier track, and T represents transmission.

[0044] According to the second-order Taylor coefficient expansion, we can obtain:

[0045]

[0046] In the above formula, at the moment t k = x0 / v, the perpendicular distance from the moving target to the carrier platform track can be expressed as R0 = ((y0 + vy ·x0 / v)+H 2 ) 1 / 2 , the relative velocity between the non-uniform sub-pulse coded synthetic aperture radar and the moving target The grazing angle η0 = acos((y0 + v y ·x0 / v) / R0), the elevation angle φ = asin[sin(φ A )·y0 / R0 - cos(φ A )·H / R0], the velocity v of the moving target projected onto the slant range plane r = v y cos(η0).

[0047] Since there are a total of M×N receiving channels in the receiving array, the instantaneous slant range between the receiving channel in the q-th row and the n-th column (q = 1, …, M, n = 1, …, N) and the moving target can be expressed as:

[0048]

[0049] Within each PRI (Pulse Repetition Interval), the transmitting channel will continuously transmit P chirp sub-pulses. Each sub-pulse has a different center frequency, and each sub-pulse will utilize non-overlapping frequency band resources. The basic waveform u of the i-th (i = 1, …, P) sub-pulse i can be expressed as:

[0050]

[0051] where t represents the fast time, μ represents the chirp rate, Δτ i represents the delay of the i-th sub-pulse, T sp represents the sub-pulse time width, and rect(x) is the rectangular window function, defined as follows:

[0052]

[0053] In this embodiment, the coding weights can be designed for different transmitting channels m and sub-pulses i. Define χ m (i) as the coding weight under the NSPC-SAR structure, and the expression is:

[0054]

[0055] where M γ represents the NSPC factor, γ i represents the non-uniform modulation coefficient of the i-th sub-pulse, and i0 is a fixed value used to change the direction of the first sub-pulse.

[0056] Further, by combining the basic waveform u of the i-th sub-pulse i and the coding weight χ m (i), the i-th sub-pulse s transmitted by the m-th transmitting channel can be obtained m,i and the expression is:

[0057] s m,i (t) = u i (t) exp[j2π(f c +Δf i )(t - Δτ i )]·χ m (i);

[0058] where, f c represents the carrier frequency, Δf i =(i - 1)Δf represents the frequency difference between the i-th sub-pulse and the first sub-pulse, and Δf is the frequency increment between any adjacent sub-pulses.

[0059] For the receiving channel at the q-th row and the n-th column in the receiving array, the multi-channel received data of the moving target in the i-th sub-pulse can be expressed as:

[0060]

[0061] where, σ t,i represents the moving target scattering point coefficient in the i-th sub-pulse, w a (·) represents the azimuth window function, tar represents the moving target, and c is the speed of light.

[0062] Optionally, before the steps of performing band-pass filtering and range pulse compression processing on the multi-channel received data to achieve first-time range ambiguity suppression and sub-pulse separation, it further includes:

[0063] Performing down-conversion processing on the multi-channel received data.

[0064] In this embodiment, the multi-channel received data after down-conversion processing is:

[0065]

[0066] where, u i (t) represents the basic waveform of the i-th sub-pulse, χ m (i) represents the preset coding weight of the i-th sub-pulse in NSPC-SAR, Δτ i represents the time delay of the i-th sub-pulse, f c represents the carrier frequency, Δf i represents the frequency difference between the i-th sub-pulse and the first sub-pulse, j is the imaginary unit, is the down-conversion processing result of

[0067] Specifically, to extract the \(i\)-th sub-pulse, first, the multi-channel received data needs to be down-converted. The down-conversion function corresponding to the \(i\)-th sub-pulse is:

[0068]

[0069] Multiply the multi-channel received data of the moving target tar in the \(i\)-th sub-pulse by the down-conversion function to obtain the down-conversion result of the multi-channel received data of the moving target in the \(i\)-th sub-pulse which is:

[0070]

[0071] Furthermore, using this down-conversion function, the down-conversion results of the multi-channel received data of the moving target in the remaining sub-pulses can be obtained and the expression is:

[0072]

[0073] where \(h\) (\(h = 1,\cdots,P, h\neq i\)) is the serial number of the remaining sub-pulses other than the \(i\)-th sub-pulse, \(\sigma\) t,h represents the moving target scattering point coefficient in the \(h\)-th sub-pulse, \(\chi\) m (h) represents the preset coding weight of the \(h\)-th sub-pulse in NSPC-SAR, \(u\) h represents the basic waveform of the \(h\)-th sub-pulse, \(\Delta f\) h represents the frequency difference between the \(h\)-th sub-pulse and the first sub-pulse, \(\Delta\tau\) h represents the time delay of the \(h\)-th sub-pulse, and \(j\) is the imaginary unit.

[0074] Therefore, the multi-channel received data corresponding to all sub-pulses after down-conversion can be expressed as:

[0075]

[0076] In the above step S2, first, perform range Fourier transforms on and respectively according to the following formula:

[0077]

[0078]

[0079] where \(f\) r \(\in[-B\) sp / 2, B\) sp / 2] represents the variation range of the range frequency, and \(B\) spIndicates the bandwidth of each sub-pulse.

[0080] Then, in order to separate sub-pulses in the range frequency domain, a band-pass filter function is constructed as:

[0081]

[0082] Indicates the band-pass filter function corresponding to the multi-channel received data of the i-th sub-pulse.

[0083] Next, in this embodiment, a corresponding matched filter is designed to perform range pulse compression processing on the multi-channel received data after band-pass filtering. The expression of the matched filter function is:

[0084]

[0085] Indicates the band-pass filter function corresponding to the multi-channel received data of the i-th sub-pulse.

[0086] Furthermore, the expression of the multi-channel received data in the range frequency domain is multiplied by the band-pass filter function and the matched filter function and then transformed into the time domain. The echo primary processing result of the multi-channel received data of the moving target in the i-th sub-pulse is:

[0087]

[0088] where, Indicates the amplitude of the multi-channel received data of the moving target in the i-th sub-pulse after range pulse compression processing, B sp Indicates the bandwidth of each sub-pulse.

[0089] In this embodiment, the above echo primary processing result can be simplified to:

[0090]

[0091]

[0092] where, Indicates the reference slant range echo expression, λ i Indicates the wavelength of the i-th sub-pulse,

[0093]

[0094]

[0095] Indicates the instantaneous slant range between the n-th receiving channel and the moving target. i0 is a fixed value used to change the direction of the first sub-pulse, Mγ Indicates the NSPC factor.

[0096] Since there are M channels in each column in the elevation dimension synthesis at the receiving end, the steering vector a of the i-th sub-pulse can be obtained i and the steering vectors a of the remaining sub-pulses h are respectively:

[0097]

[0098]

[0099] where f a,i (φ h ) = dsin(φ i ) / λ i represents the spatial frequency of the i-th sub-pulse, f a , h (φ h ) = dsin(φ h ) / λ h represents the spatial frequency of the h-th sub-pulse, λ h = c / (f c + Δf h ) represents the wavelength of the h-th sub-pulse, and the beam direction of the h-th sub-pulse

[0100] Stack the received echo data of the M channels in the n-th column, and respectively obtain the data vector of the i-th sub-pulse and the data vector

[0101]

[0102]

[0103] where represents the h-th sub-pulse after frequency domain separation, respectively represent the i-th sub-pulse received by the receiving channel in the n-th column of the m-th (m = 1, …, M) row, respectively represent the h-th sub-pulse received by the receiving channel in the n-th column of the m-th (m = 1, …, M) row.

[0104] Similarly, when the expression takes v y = 0, the clutter echo data of the corresponding sub-pulse can be obtained

[0105] Then, use the DBF technology to further suppress the interference from the remaining sub-pulses. Specifically, in this embodiment, the optimal weight vector is obtained by minimizing the interference signal power and increasing the desired signal power, which can be expressed as:

[0106]

[0107] where \(w\) i represents the weight vector of the \(i\)-th sub-pulse, and \((\cdot)^{H}\) H represents the conjugate transpose operation, represents the power calculated through the range gate corresponding to the sub-pulse with azimuth \(\varphi\) h and is obtained according to Capon spatial spectrum estimation:

[0108]

[0109] where represents the covariance matrix formed by the multi-channel received data of the \(h\)-th sub-pulse, and \(\mathbf{x}_{h}\) is the data vector of the moving target plus clutter stack in the \(h\)-th sub-pulse.

[0110] Based on the minimum variance distortionless response (MVDR) criterion, the weight vector of the \(i\)-th sub-pulse is calculated as:

[0111]

[0112] where \(\mathbf{F}_{1}\) is the constraint vector, \(\mathbf{F}_{1}=[1,0,0,\cdots,0]\) T and

[0113] According to the weight vectors of each sub-pulse, the unambiguous echo of the \(i\)-th sub-pulse in the \(n\)-th column of the receiving channel can be obtained as:

[0114]

[0115] where

[0116] Furthermore, the unambiguous echo \(y_{n,i}\) can be expressed as:

[0117]

[0118] where \(p\) r \((\cdot)=\text{sinc}[B(\cdot)]\). sp

[0119] Performing a two-dimensional frequency domain transformation on \(y_{n,i}\), we can obtain:

[0120]

[0121] where \(W\)​​​a (·) represents the frequency-domain form of the azimuth window function,

[0122] Next, construct the range migration correction function as:

[0123]

[0124] The azimuth compression filter function is:

[0125]

[0126] After performing range migration correction and azimuth compression on the non-ambiguous echo according to the following formula and then converting it back to the time domain, the imaging result can be obtained:

[0127]

[0128] Finally, decompose the sparse matrix containing moving targets and the low-rank matrix containing clutter background through the robust principal component analysis algorithm, and selectively use the GoDec algorithm for moving target detection.

[0129] Finally, the NSPC-SAR ground moving target indication SAR-GMTI is:

[0130]

[0131] where p r (·) = sinc[B sp (·)].

[0132] Next, the SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding provided by the present invention will be further described through simulation experiments.

[0133] Specifically, the hardware platform for the simulation experiment in this embodiment is: Intel(R) Core(TM) i5-8265U CPU @ 1.60 GHz, with a frequency of 1.8 GHz, Nvidia GeForce MX250, and the software used is matlab2016b.

[0134] In this embodiment, the simulation parameters of the NSPC-SAR system are shown in Table 1:

[0135] Table 1

[0136] Parameter Value Parameter Value Carrier frequency 18 GHz PRF 1200 Hz Platform speed 500 m / s Platform altitude 30 km Antenna tilt angle 50° Channel spacing 0.0083m Antenna aperture 2m Sub-pulse width 3 μs Sub-pulse bandwidth 37.5 MHz NSPC factor 32

[0137] Please refer to Table 1. In this embodiment, the number of sub-pulses is set to 3. The 3 sub-pulses respectively point to 3 range ambiguity regions, and the grazing angles corresponding to the range ambiguity regions are 5.9°, 10.4°, and 47° respectively. The non-uniform modulation coefficients of the sub-pulses are 3.71, 5.11, and 0.84 respectively. The transmitting end uses a uniform planar array of 32 rows and 6 columns, and the receiving end uses a sub-array receiving method. 4 receiving channels in the elevation dimension are used for residual range ambiguity suppression, and 3 receiving channels in the azimuth dimension are used for detecting moving targets.

[0138] Figure 2 It is a schematic diagram of the point target position set in the first range ambiguity region provided by the embodiment of the present invention. As Figure 2 shown, a total of eight stationary targets and one moving target are set in the first range ambiguity region. Similarly, eight stationary targets and one moving target are also set in the second range ambiguity region and the third range ambiguity region respectively. Exemplarily, taking the processing of the first range ambiguity region as an example. Figure 3 It is a schematic diagram of the result of multi-channel received data in the range frequency domain - azimuth time domain provided by the embodiment of the present invention. Among them, the sub-pulses occupy three different frequency bands and are obviously distinguishable. Figure 4 It is a schematic diagram of the result of extracting the first sub-pulse after band-pass filtering, completing the separation of the sub-pulses in the frequency domain and the first range ambiguity suppression. Figure 5 It is a schematic diagram of the range pulse compression result in the prior art, without performing range frequency domain separation on the multi-channel received data, that is Figure 5 it is the result of directly performing range pulse compression on Figure 3 Obviously, there is serious aliasing between the stationary targets and moving targets in the first range ambiguity region and the second range ambiguity region. All the targets in the second range ambiguity region are only about -2dB lower than those in the first range ambiguity region. Figure 6 It is a schematic diagram of the result of directly imaging the multi-channel received data in the prior art. As Figure 6 shown, all the targets in the first range ambiguity region are imaged, while all the targets in the second range ambiguity region have range ambiguity.

[0139] Figure 7 It is a schematic diagram of the result of taking an azimuth slice after range pulse compression of the first sub-pulse provided by the embodiment of the present invention. As Figure 7 shown, the nine targets (eight stationary targets and one moving target) located in the first range ambiguity region have completed range pulse compression. At the same time, it can also be seen that the point target in the second range ambiguity region enters from the sidelobe of the first sub-pulse, resulting in range ambiguity, which is about -20dB. Therefore, the DBF technology is used for secondary range ambiguity suppression. Figure 8 It is a schematic diagram of the result after secondary range ambiguity suppression of the first sub-pulse provided by the embodiment of the present invention. Please refer to Figure 7 、 8, only the point targets in the first range ambiguity region exist, which indicates that the remaining range ambiguities are well suppressed, and the interference from the other sub-pulses is completely removed. The NSPC scheme adopted by the present invention can effectively suppress range ambiguities through frequency band separation and DBF technology, which is beneficial to wide-swath unambiguous imaging and subsequent moving target detection.

[0140] Figure 9 is a schematic diagram of the imaging result of the first range ambiguity region provided by an embodiment of the present invention. Figure 10 is a schematic diagram of the results before and after clutter suppression in the first range ambiguity region provided by an embodiment of the present invention. As Figure 9 - 10 shown, only moving targets exist after two range ambiguity suppressions, and the point targets in the other regions and the stationary targets in the first range ambiguity region are well suppressed, and the clutter energy is suppressed to below -45 dB.

[0141] Next, the planar targets in three range ambiguity regions are simulated under the same parameters. Figure 11 is a schematic diagram of the imaging result of the beam pointing to the second range ambiguity region in the prior art. As Figure 11 shown, the first range ambiguity region is aliased with the imaging scene here, and the mutual interference of the stationary clutter will be very unfavorable for moving target detection. The processing flow of the present invention for planar targets is the same as that for point targets. First, the sub-pulses are separated in the range frequency domain, and then two range ambiguity suppressions are performed, and finally an imaging result without ambiguity is obtained. Figure 12 、 13 、14 are respectively schematic diagrams of the imaging results, moving target detection and repositioning results of the first range ambiguity region, the second range ambiguity region, and the third range ambiguity region provided by an embodiment of the present invention. Please refer to Figure 12 - 14 . After separating the moving targets and clutter using the GoDec algorithm, the triangles in the figure are the detected positions of the moving targets, and the squares are the repositioning of the moving targets. Through the simulation of planar targets, the present invention can specify the pointing of the scanning beam in the elevation dimension, further improve the imaging swath, can perform unambiguous moving target detection, and the method for removing range ambiguities is simple and feasible.

[0142] As can be seen from the above embodiments, the beneficial effects of the present invention are as follows:

[0143] 1. The SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding provided by the present invention can enable the radar beam to automatically scan with non-uniform pointing in the elevation dimension through the joint coding of multi-frequency sub-pulses and spatial transmitting array elements. The specific design of parameters such as the non-uniform modulation coefficient can direct the beam to the desired direction to obtain an imaging area with wide coverage. At the receiving end, a band-pass filter and digital beamforming (DBF) technology based on data reconstruction are used to separate the echo signals and suppress range ambiguities. This method effectively suppresses range ambiguities, improves the moving target detection performance, and enhances the system robustness.

[0144] 2. The SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding provided by the present invention does not require the transmitted waveform to satisfy orthogonality. By utilizing the range-frequency domain resources, it is easy to separate sub-pulses, can effectively increase the imaging swath width, can obtain an ambiguity-free imaging result, is easy to implement in engineering, has a good moving target detection result, and is applicable to future multi-channel SAR-GMTI systems.

[0145] The above content is a further detailed description of the present invention in combination with specific preferred embodiments. It cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions or substitutions can still be made, which should all be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for SAR-GMTI range ambiguity suppression based on non-uniform sub-pulse coding, characterized in that, Including: Obtaining multi-channel received data of a non-uniform sub-pulse coded synthetic aperture radar (NSPC-SAR) by using a receiving array; Performing band-pass filtering and range pulse compression processing on the multi-channel received data to achieve primary range ambiguity suppression and sub-pulse separation, and obtaining a primary echo processing result; Performing secondary range ambiguity suppression on the primary echo processing result by using digital beamforming technology to obtain an unambiguous echo; Performing imaging on the unambiguous echo and performing moving target detection based on the imaging result to obtain NSPC-SAR ground moving target indication (SAR-GMTI).

2. The SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding according to claim 1, wherein, The multi-channel received data is: where \(t\) represents the fast time, and \(t\) k represents the azimuth slow time, \(\sigma\) t,i represents the moving target scattering point coefficient in the \(i\)-th sub-pulse, \(w\) a (·) represents the azimuth window function, \(R_0\) represents the perpendicular distance from the moving target to the flight path of the carrier platform, \(v\) r represents \(v\) y projected onto the slant range plane, \(v\) y is the velocity of the moving target perpendicular to the flight path of the carrier platform, \(v\) e represents the relative velocity between the NSPC-SAR and the moving target, \(x_0\) represents the initial azimuth coordinate of the moving target, \(v\) represents the velocity of the carrier platform, \(d\) represents the spacing between any adjacent transmit channels and any adjacent receive channels, and \(c\) is the speed of light. represents the instantaneous slant range between the \(m\)-th transmit channel and the moving target, \(m = 1, \ldots, M\), \(Tr\) represents transmission. represents the instantaneous slant range between the receive channel in the \(q\)-th row and \(n\)-th column of the receive array and the moving target, \(q = 1, \ldots, M\), \(n = 1, \ldots, N\), \(Re\) represents reception, \(s\) m,i (·) represents the \(i\)-th sub-pulse transmitted by the \(m\)-th transmit channel, \(i = 1, \ldots, P\). represents the multi-channel received data of the moving target \(tar\) in the \(i\)-th sub-pulse received by the receive channel in the \(q\)-th row and \(n\)-th column.

3. The SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding according to claim 2, characterized in that, Before the step of performing band-pass filtering and range pulse compression processing on the multi-channel received data to achieve primary range ambiguity suppression and sub-pulse separation, it further includes: Performing down-conversion processing on the multi-channel received data.

4. The SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding according to claim 3, wherein The multi-channel received data after down-conversion processing is: Among them, u i represents the basic waveform of the i-th sub-pulse, and χ m (i) represents the preset coding weight of the i-th sub-pulse in NSPC-SAR, Δτ i represents the time delay of the i-th sub-pulse, f c represents the carrier frequency, Δf i represents the frequency difference between the i-th sub-pulse and the first sub-pulse, and j is the imaginary unit, is the down-conversion processing result of 5. The SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding according to claim 4, characterized in that, The primary echo processing result is: Among them, represents the amplitude after range pulse compression processing of the multi-channel received data of moving targets in the i-th sub-pulse, and B sp represents the bandwidth of each of the sub-pulses.

6. The SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding according to claim 5, wherein The non-blurred echo is as follows: where, w i denotes the weight vector of the i-th sub-pulse, (·) H denotes the conjugate transpose operation, y in denotes the data vector of the moving target plus clutter stack in the i-th sub-pulse, h = 1, …, P and h ≠ i, h is the sequence number of the remaining sub-pulses other than the i-th sub-pulse, y hn denotes the data vector of the moving target plus clutter stack in the h-th sub-pulse.

7. The SAR-GMTI range ambiguity suppression method based on non-uniform sub-pulse coding according to claim 6, wherein The NSPC-SAR ground moving target indication (SAR-GMTI) is: where p r (·) = sinc[B sp (·)], and sinc represents the sinc function.

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