ISAR distance envelope alignment method and system based on phase difference

Abstract

The invention discloses an ISAR (Inverse Synthetic Aperture Radar) range envelope alignment method and system based on phase difference, and belongs to the technical field of radars. The method comprises the following steps: sampling echo signals after pulse compression one by one, estimating and compensating adjacent sampling average phase change; partitioning azimuth signals in a distance frequency domain, respectively adding rectangular windows by taking zero frequency as a boundary, and sampling in each azimuth to generate an upper sideband signal and a lower sideband signal; performing three-time conjugate multiplication on four adjacent sampled signals to obtain a differential signal; obtaining an adjacent offset through maximum likelihood estimation by using the differential signal; aligning the adjacent envelopes according to an estimation result; and after the aligned envelopes are accumulated, the steps are repeated for recursion with the next sample, and finally, envelope alignment of all the samples is completed. According to the method, the sub-pixel-level distance envelope alignment precision can be realized without up-sampling and interpolation operations, and the problem of echo generation caused by amplitude modulation in a traditional amplitude dependent algorithm is effectively avoided.

Description

Technical Field

[0001] This invention belongs to the field of radar technology, specifically relating to an ISAR range envelope alignment method and system based on phase difference. Background Technology

[0002] Inverse Synthetic Aperture Radar (ISAR) is an effective means of imaging non-cooperative targets using microwaves. It is available in all weather conditions and is widely used in ground-based detection of air and space targets, space-based imaging of orbiting vehicles, and imaging of non-cooperative ships at sea.

[0003] ISAR systems typically transmit linear frequency modulated (LFM) signals, achieving high range resolution through pulse compression, and then imaging in the azimuth direction using the Doppler differences generated by target scattering points. Starting with the range-compressed signal, the ISAR imaging process consists of four steps: envelope alignment, initial phase correction, rotation compensation, and azimuth imaging. Among these, range envelope alignment is fundamental to subsequent processing; its purpose is to maintain the azimuth signals of all scattering points within the same range gate, preventing movement due to azimuth-time variations. The accuracy of envelope alignment has a decisive impact on the phase estimation of the azimuth signal and the final image quality.

[0004] Classical distance-envelope alignment algorithms primarily rely on envelope amplitude information. Representative methods include adjacent cross-correlation, cumulative cross-correlation, centroid method, prominent point method, and image quality optimization methods. Among these, the minimum entropy algorithm is currently a widely used method, which iteratively estimates the envelope offset by optimizing the entropy value of the average distance image. However, these amplitude-based algorithms have two inherent drawbacks: first, their accuracy is limited by the interpolation rate, requiring high-rate upsampling or interpolation operations to achieve sub-pixel-level alignment; second, their computational speed is slow, with high-rate interpolation and frequent Fourier transform operations resulting in a large computational load, making it difficult to meet real-time processing requirements. More importantly, inaccurate envelope alignment not only affects the phase but also introduces amplitude modulation, generating difficult-to-compensate echoes in the image domain.

[0005] To address the aforementioned issues, some improvements have emerged in existing technologies. For example, patent CN106154265B proposes an envelope alignment method for ISAR (Inductively Coupled Radar) systems based on frequency domain shifting. This method achieves precise range image shifting by constructing a frequency shift factor, breaking through the limitation of 0.5 range resolution cells. However, this method still requires coarse alignment followed by a fine search through exhaustive methods, essentially remaining dependent on search and interpolation, thus its computational efficiency needs improvement. Patent CN114488149A proposes a global envelope alignment method based on minimizing Tsallis entropy, iteratively estimating the offset by optimizing the Tsallis entropy of the average range image. However, this method is still an amplitude-dependent algorithm and fails to fundamentally resolve the contradiction between accuracy and speed.

[0006] In addition, although there are some envelope alignment methods based on phase difference, these methods usually rely on rapid phase changes and require complex phase unwinding operations to obtain the correct displacement. The algorithms have poor robustness and are difficult to promote and apply in practical engineering. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention provides an ISAR range envelope alignment method and system based on phase difference. It utilizes the signals after frequency domain segmentation of adjacent echo ranges to perform triple conjugate multiplication to construct a differential signal containing sub-pixel displacement information. Then, the envelope offset is directly extracted through amplitude-weighted maximum likelihood estimation, achieving high-precision and fast alignment without interpolation.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0009] A phase difference-based ISAR range envelope alignment method, the method comprising:

[0010] Step 1: Perform adjacent sample average phase compensation processing on the pulse-compressed echo signal to obtain the compensated signal;

[0011] Step 2: Divide the compensated signal into blocks in the range frequency domain, and sample each direction to generate an upper sideband signal and a lower sideband signal;

[0012] Step 3: Perform conjugate multiplication on the four signals from two adjacent samples to obtain the differential signal;

[0013] Step 4: Using the differential signal, obtain the estimated envelope offset of adjacent samples through maximum likelihood estimation;

[0014] Step 5: Align adjacent samples according to the estimated envelope offset to obtain the aligned signal;

[0015] Step 6: Accumulate the aligned signals and repeat steps 1-5 with the next sample to recursively align the accumulated results until the envelope alignment of all samples is completed.

[0016] Furthermore, in step 1: the average phase change factor of adjacent samples is estimated. The average phase change factor is equal to the sum of the conjugates of the adjacent subsequent sample and the preceding sample along the distance direction, and then divided by its magnitude. The conjugate of the average phase change factor is used to perform phase compensation on the adjacent subsequent sample to obtain the compensated signal.

[0017] Furthermore, in step 2: an upper sideband filter and a lower sideband filter are set, and both filters are windowed to the range spectrum of the compensated signal with zero frequency as the boundary; the filtered spectrum is then subjected to inverse Fourier transform to obtain the upper sideband time domain signal and the lower sideband time domain signal.

[0018] Furthermore, in step 3: the conjugate of the upper sideband signal and the lower sideband signal of the next adjacent sample is multiplied, and then multiplied by the conjugate of the upper sideband signal and the lower sideband signal of the previous adjacent sample to obtain the differential signal.

[0019] Furthermore, in step 4: the differential signal is subjected to amplitude-weighted phase averaging along the distance direction to obtain the average phase difference; an amplitude squared coefficient is introduced to weight the amplitude of the differential signal; based on the average phase difference, the center frequency difference between the upper and lower sidebands, and the speed of light, the estimated envelope offset of adjacent samples is calculated.

[0020] Furthermore, in step 5: the estimated envelope offset is converted into a linear phase factor in the range frequency domain; the range spectrum of the compensated signal is multiplied by the linear phase factor and then subjected to an inverse Fourier transform to achieve sub-pixel-level displacement in the time domain, thereby obtaining the aligned signal.

[0021] Furthermore, in step 6: the accumulated memory coefficient is introduced to weight the aligned signal and then added to the next sample to obtain a new accumulated signal; wherein, the value range of the accumulated memory coefficient is from zero to one, and it is used to control the degree of retention of historical envelope information.

[0022] On the other hand, the present invention provides an ISAR range envelope alignment system based on phase difference, comprising:

[0023] The compensation module is used to perform adjacent sampling average phase compensation processing on the pulse-compressed echo signal to obtain the compensated signal;

[0024] The generation module is used to divide the compensated signal into blocks in the range frequency domain, and to generate upper sideband and lower sideband signals for each azimuth sampling.

[0025] The differential module is used to perform conjugate multiplication on four signals from two adjacent samples to obtain a differential signal;

[0026] The estimation module is used to obtain the estimated envelope offset of adjacent samples by using the differential signal through maximum likelihood estimation;

[0027] The alignment module is used to align adjacent samples based on the envelope offset estimate to obtain the aligned signal.

[0028] The accumulation module is used to accumulate the aligned signals and recursively align the accumulated results with the average phase compensation of adjacent samples, distance frequency domain segmentation, conjugate multiplication, maximum likelihood estimation and adjacent alignment processing for the next sample until the envelope alignment of all samples is completed.

[0029] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned phase difference-based ISAR range envelope alignment method.

[0030] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned phase difference-based ISAR range envelope alignment method.

[0031] The beneficial effects of this invention are as follows:

[0032] First, this invention opens up a new path for envelope alignment based on phase difference, achieving sub-pixel accuracy without interpolation. Traditional amplitude-dependent algorithms (such as cross-correlation and minimum entropy methods) are limited in accuracy by the interpolation rate, requiring high-rate upsampling to improve alignment accuracy. This invention utilizes the conjugate multiplication of adjacent echo signals after they are divided into blocks in the distance frequency domain, and directly extracts the sub-pixel displacement information contained in the phase difference through maximum likelihood estimation. Without any upsampling or interpolation operations, it achieves the accuracy level that existing best methods require approximately 8 times upsampling to achieve.

[0033] Secondly, this invention avoids the echo artifact problem caused by amplitude modulation, thus improving image quality. Traditional methods introduce amplitude modulation due to inaccurate envelope alignment. This modulation period is related to the interpolation rate of the spectrum and the target translation scale, which can generate difficult-to-compensate echo artifacts in the image domain. This invention, through high-precision phase difference estimation, fundamentally eliminates the conditions for amplitude modulation, avoids the resulting image artifacts, and significantly improves the focusing quality of the final ISAR image.

[0034] Third, this invention boasts fast computation speed and strong engineering applicability. Traditional methods require frequent high-magnification interpolation, Fourier transforms, and cross-correlation searches, resulting in large computational loads and long processing times. This invention only requires simple conjugate multiplication and maximum likelihood estimation, avoiding complex search and iteration processes. Under actual measured data, the computation time is only about one-quarter of that of traditional methods, providing strong support for real-time imaging processing.

[0035] Fourth, this invention is robust and widely applicable. Compared to existing phase difference methods that rely on rapidly changing phases and require complex unwinding, this invention uses slowly changing phases for estimation, eliminating the need for unwinding when the relative displacement between adjacent envelopes does not exceed one distance cell. Furthermore, by introducing an amplitude squared coefficient β for weighted maximum likelihood estimation, it can adaptively adjust based on the presence or absence of prominent points in the scene, maintaining stable estimation performance under different signal-to-noise ratio conditions. Attached Figure Description

[0036] Figure 1 This is a flowchart of an ISAR range envelope alignment method based on phase difference according to the present invention;

[0037] Figure 2 This is a schematic diagram of the differential envelope signals of a single-scattering point echo, where (a) is the phase of the envelope signal; (b) is the amplitude of the differential signal; (c) is the amplitude of the envelope signal; and (d) is the phase of the differential signal.

[0038] Figure 3 This is a schematic diagram of a differential signal from a certain adjacent sample of measured data, where (a) is the phase curve and (b) is the amplitude curve.

[0039] Figure 4 Using different methods in this approach for simulation data Comparison of root mean square errors obtained by envelope alignment; where (a) represents echo signals without prominent points using different methods. After envelope alignment, the root mean square error (rMS) is shown in (b), which uses different methods for echo signals containing prominent points. Root mean square error after envelope alignment;

[0040] Figure 5 The method was used to perform envelope alignment on the measured data, and the final imaging results are shown. (a) is the echo signal after range compression; (b) is the result of envelope alignment using the method; and (c) is the result of imaging using the aligned envelope. Detailed Implementation

[0041] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0043] like Figure 1 As shown, this invention proposes an ISAR range envelope alignment method based on phase difference, comprising the following steps:

[0044] Step 1: For the pulse-compressed echo signal Estimate the average phase change of adjacent samples one by one according to the azimuth sampling order. And compensation is performed to obtain the compensated signal. For direction, slow time, For distance, the time is fast. This includes:

[0045] Estimating the average phase change between adjacent samples The expression is:

[0046] ,

[0047] in, express conjugate, This indicates the azimuth sampling interval.

[0048] The phase is compensated on a sample-by-sample basis, expressed as:

[0049] ,

[0050] The left side of the equation represents the compensated signal.

[0051] Step 2: Divide the compensated signal into blocks in the range frequency domain, using zero frequency as the boundary, and add rectangular windows to the upper and lower sidebands respectively, sampling in each azimuth. Two signals are generated, including:

[0052] Set up two frequency domain filters, namely:

[0053] ,

[0054] in, The center frequency of the lower sideband. The center frequency of the upper sideband. For distance bandwidth, This indicates a bottom-band filter. This indicates the top-sideband filter. Indicates the range frequency.

[0055] Each azimuth sample generates two signals, as shown in the formula:

[0056] ,

[0057] in, Indicates in Perform a Fourier transform on the dimension. Indicates in Perform an inverse Fourier transform on the dimension. and These are the upper sideband signal and the lower sideband signal, respectively.

[0058] Step 3: Sample adjacent samples and There are four signals in total. , , and Performing three conjugate multiplications yields the difference signal. ,include:

[0059] Using conjugate multiplication of adjacent sampled signals, the expression is as follows:

[0060] ,

[0061] like Figure 2 As shown, to more clearly illustrate the four adjacent samples and the differential signal... The phase and amplitude relationship between these signals is illustrated using the adjacent envelopes of the single-scattering point echoes. For clarity, the figure shows these four signals... , , and They are respectively denoted as , , and , Figure 2 In the diagram, (a) and (c) represent the phase and amplitude of the four signals, while (b) and (d) represent the differential signals. The amplitude and phase, the phase of which is unreliable in areas with small amplitude. Figure 3 The diagram uses the differential signals of adjacent samples of the measured data. (a) and (b) show the phase and amplitude of a differential signal of an adjacent sample of the measured data. It can be seen that the phase provides almost no useful information.

[0062] Step 4: Utilize differential signals The envelope offset of adjacent samples is obtained through maximum likelihood estimation. ,include:

[0063] Differential signal Observations Write in the following format:

[0064] ,

[0065] in Represents the observations of the differential signal The range, This indicates its phase, and j represents the imaginary unit.

[0066] according to Observations The offset is calculated using maximum likelihood estimation, as shown in the following expression:

[0067] ,

[0068] in, This represents the amplitude squared coefficient, and a value between 1 / 2 and 2 is reasonable. This value is affected by the interference effect of adjacent scattering points and the signal-to-noise ratio. If there are prominent points in the sampling, then... Taking a value close to 2 will yield better results. If there are no significant points in the sampling, taking 1 / 2 will likely yield better results.

[0069] Figure 4 Using different methods in this approach for simulation data Comparison of root mean square errors obtained by envelope alignment. Among them, (a) shows the echo signal without prominent points using different... After envelope alignment, the root mean square error (rMS) is shown in (b), which uses different methods for echo signals containing prominent points. The root mean square error after envelope alignment. Optimal results are achieved when there are prominent points. The value is larger than the value when there are no special points.

[0070] The offset estimate is obtained using phase estimation, expressed as follows:

[0071] ,

[0072] in, It is the speed of light.

[0073] Step 5: Based on the estimation results Align adjacent envelopes to obtain the aligned signal. ,include:

[0074] Use the estimation results Correction , Since it is much smaller than a distance gate, the time-domain shift needs to be achieved by multiplying the frequency domain by a linear phase, as shown in the following expression:

[0075] ,

[0076] in Indicates distance frequency.

[0077] Step 6: Accumulate the aligned envelopes, and record the accumulated signal as . Align the cumulative result with the next sample by repeating steps 1-5 above, including:

[0078] The already aligned echoes are added together, as shown in the following expression:

[0079] ,

[0080] After accumulation, the above steps are repeated with the next sample to align. The recursive expression is as follows:

[0081]

[0082] in, This represents the cumulative sum after the translation in step 6. This represents the accumulated memory coefficient, which can be adjusted between 0 and 1. A larger coefficient retains more historical envelope information, while a smaller coefficient is less affected by the incoherence of historical envelopes. After the recursion is complete, the signal indicating successful envelope alignment is obtained.

[0083] Figure 5 To illustrate the use of this method for envelope alignment of measured data and the final image, (a) shows the echo signal after range compression. The image shows that the original echo exhibits significant envelope movement, and the echoes from each scattering point fail to remain within the same range cell as the azimuth and time change. (b) shows the result of envelope alignment using this method. The image shows that after processing by the method of this invention, the envelope movement has been effectively corrected, and the echo energy of each scattering point is stabilized within the same range cell. (c) shows the result of imaging using the aligned envelope. The image shows that the target image is well focused and has a clear outline, verifying the effectiveness of the envelope alignment method of this invention and its effect on improving the final image quality.

[0084] On the other hand, the present invention provides an ISAR range envelope alignment system based on phase difference, which includes modules capable of implementing the steps of the aforementioned method, specifically including:

[0085] The compensation module is used to perform adjacent sampling average phase compensation processing on the pulse-compressed echo signal to obtain the compensated signal;

[0086] The generation module is used to divide the compensated signal into blocks in the range frequency domain, and to generate upper sideband and lower sideband signals for each azimuth sampling.

[0087] The differential module is used to perform conjugate multiplication on four signals from two adjacent samples to obtain a differential signal;

[0088] The estimation module is used to obtain the estimated envelope offset of adjacent samples by using the differential signal through maximum likelihood estimation;

[0089] The alignment module is used to align adjacent samples based on the envelope offset estimate to obtain the aligned signal.

[0090] The accumulation module is used to accumulate the aligned signals and recursively align the accumulated results with the average phase compensation of adjacent samples, distance frequency domain segmentation, conjugate multiplication, maximum likelihood estimation and adjacent alignment processing for the next sample until the envelope alignment of all samples is completed.

[0091] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned phase difference-based ISAR range envelope alignment method.

[0092] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned phase difference-based ISAR range envelope alignment method.

[0093] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A phase difference-based ISAR range envelope alignment method, characterized in that, The method includes: Step 1: Perform adjacent sample average phase compensation processing on the pulse-compressed echo signal to obtain the compensated signal; Step 2: Divide the compensated signal into blocks in the range frequency domain, and sample each direction to generate an upper sideband signal and a lower sideband signal; Step 3: Perform conjugate multiplication on the four signals from two adjacent samples to obtain the differential signal; Step 4: Using the differential signal, obtain the estimated envelope offset of adjacent samples through maximum likelihood estimation; Step 5: Align adjacent samples according to the estimated envelope offset to obtain the aligned signal; Step 6: Accumulate the aligned signals and repeat steps 1-5 with the next sample to recursively align the accumulated results until the envelope alignment of all samples is completed.

2. The ISAR range envelope alignment method based on phase difference according to claim 1, characterized in that, In step 1: the average phase change factor of adjacent samples is estimated. The average phase change factor is equal to the sum of the conjugate of the next adjacent sample and the previous sample along the distance direction, and then divided by its magnitude. The conjugate of the average phase change factor is used to perform phase compensation on the next adjacent sample to obtain the compensated signal.

3. The ISAR range envelope alignment method based on phase difference according to claim 1, characterized in that, In step 2: an upper sideband filter and a lower sideband filter are set. Both filters are windowed and filtered on the range spectrum of the compensated signal with zero frequency as the boundary. The filtered spectrum is then subjected to inverse Fourier transform to obtain the upper sideband time domain signal and the lower sideband time domain signal.

4. The ISAR range envelope alignment method based on phase difference according to claim 1, characterized in that, In step 3: the conjugate of the upper sideband signal and the lower sideband signal of the next adjacent sample is multiplied, and then multiplied by the conjugate of the upper sideband signal and the lower sideband signal of the previous adjacent sample to obtain the differential signal.

5. The ISAR range envelope alignment method based on phase difference according to claim 1, characterized in that, In step 4: the differential signal is amplitude-weighted and phase-averaged along the distance direction to obtain the average phase difference; an amplitude squared coefficient is introduced to weight the amplitude of the differential signal; based on the average phase difference, the center frequency difference between the upper and lower sidebands, and the speed of light, the estimated envelope offset of adjacent samples is calculated.

6. The ISAR range envelope alignment method based on phase difference according to claim 1, characterized in that, In step 5: the estimated envelope offset is converted into a linear phase factor in the range frequency domain; the range spectrum of the compensated signal is multiplied by the linear phase factor and then subjected to an inverse Fourier transform to achieve sub-pixel-level displacement in the time domain, thereby obtaining the aligned signal.

7. The ISAR range envelope alignment method based on phase difference according to claim 1, characterized in that, In step 6: the accumulated memory coefficient is introduced to weight the aligned signal and then added to the next sample to obtain a new accumulated signal; wherein, the value range of the accumulated memory coefficient is from zero to one, and it is used to control the degree of retention of historical envelope information.

8. A phase-difference-based ISAR range envelope alignment system, characterized in that, include: The compensation module is used to perform adjacent sampling average phase compensation processing on the pulse-compressed echo signal to obtain the compensated signal; The generation module is used to divide the compensated signal into blocks in the range frequency domain, and to generate upper sideband and lower sideband signals for each azimuth sampling. The differential module is used to perform conjugate multiplication on four signals from two adjacent samples to obtain a differential signal; The estimation module is used to obtain the estimated envelope offset of adjacent samples by using the differential signal through maximum likelihood estimation; The alignment module is used to align adjacent samples based on the envelope offset estimate to obtain the aligned signal. The accumulation module is used to accumulate the aligned signals and recursively align the accumulated results with the average phase compensation of adjacent samples, distance frequency domain segmentation, conjugate multiplication, maximum likelihood estimation and adjacent alignment processing for the next sample until the envelope alignment of all samples is completed.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by the one or more processors, the one or more processors implement the phase difference-based ISAR range envelope alignment method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, enable the processor to implement the phase difference-based ISAR range envelope alignment method as described in any one of claims 1-7.

Images