Nonlinear radar high-precision ranging method and system based on single-frame zonal interference

Abstract

The application discloses a kind of based on single frame banding interference nonlinear radar high-precision ranging method and system, method includes constructing two-dimensional complex observation data;Obtain full-band observation data and multiple sub-band observation data;The full-band observation data and each sub-band observation data are respectively processed, corresponding peak complex response, peak phase and peak distance are obtained;Multiple sub-band observation data are pairwise interfered with processing, and the interference phase difference corresponding to different sub-band combinations is obtained;Multiple sub-band combinations corresponding distance estimation value is obtained;Multiple distance estimation values are fused, and single frame high-precision distance estimation result is obtained.This method can be without stable reference frame condition, utilize full-band rough measurement result and sub-band interference relationship complete ambiguity determination and fusion output, obtain single frame high-precision distance estimation result, and when there is reference distance or multiple time observation result, further obtain distance offset or displacement.

Description

Technical Field

[0001] This invention relates to the field of nonlinear radar signal processing and high-precision distance measurement technology, specifically to a high-precision ranging method and system for nonlinear radar based on single-frame segmented interferometry. Background Technology

[0002] Nonlinear radar detects targets with nonlinear scattering characteristics by transmitting a fundamental frequency signal and receiving harmonic echoes generated by the target. Since natural environments and ordinary building structures typically produce linear scattering, nonlinear radar can highlight nonlinear cooperative targets against a background of linear clutter such as vegetation, rocks, water bodies, and general buildings. Therefore, by placing nonlinear tags, harmonic transponders, or target units containing nonlinear devices on the object under test, cooperative measurement scenarios suitable for distance measurement, minute displacement measurement, or structural deformation monitoring can be formed.

[0003] In the above scenarios, target detection capability is not equivalent to high-precision range measurement capability. For single-frame nonlinear radar echoes, if peak localization or phase inversion is performed directly based on full-band data, the measurement results will still be affected by factors such as system range resolution, spectral peak extraction accuracy, noise, multipath propagation, amplitude-phase inhomogeneity within the frequency band, and local mismatch. When the distance to be measured is at the millimeter or sub-millimeter level, the robustness and accuracy of measurement relying solely on a single full-band observation result are still limited.

[0004] Among existing methods for improving the accuracy of distance or displacement measurements, one type utilizes full-band echoes for fine spectral peak estimation or phase estimation. This type of method has a relatively simple processing flow, but it typically lacks additional phase constraints or redundant observations, making it difficult to adequately suppress local errors. Another type of method selects a reference frame from multiple frames of observation data and performs interferometry between subsequent frames and the reference frame to extract fine displacement information. This type of method is dependent on inter-frame coherence, reference frame selection, and cross-time registration relationships, limiting its applicability in scenarios involving single observations, rapid measurements, or where reference frames are difficult to acquire stably.

[0005] Band splitting or spectral splitting can generate multiple sub-band observations with different equivalent center frequencies within the same observation bandwidth, with differential information related to target range contained between the phase responses of different sub-bands. Existing related ideas are mostly used in multi-temporal interferometry processing of conventional linear radars or synthetic aperture radars, primarily serving unambiguous range extension, phase unwrapping assistance, or error term estimation. However, for nonlinear radar harmonic echoes, especially under single-frame observation conditions, there is still a lack of targeted processing methods for constructing full-band observations and multiple sub-band observations within the same frame of data, and using the full-band coarse measurement results to constrain inter-sub-band interferometric range estimation.

[0006] Therefore, it is necessary to propose a high-precision distance measurement method for single-frame harmonic echo data from nonlinear radar. Summary of the Invention

[0007] The purpose of this invention is to address the problems existing in the prior art by providing a high-precision ranging method and system for nonlinear radar based on single-frame segmented interferometry. This method enables the system to complete ambiguity determination and fusion output using full-band coarse measurement results and inter-subband interference relationships without the need for a stable reference frame, thereby obtaining a single-frame high-precision range estimation result. Furthermore, when a reference distance or multi-time observation results are available, the range offset or displacement can be obtained.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: Firstly, a high-precision ranging method for nonlinear radar based on single-frame segmented interferometry is provided, comprising the following steps: Acquire single-frame nonlinear radar harmonic echo data and construct it into two-dimensional complex observation data for range dimension processing and slow time processing; Based on two-dimensional complex observation data, full-band observation data and multiple sub-band observation data are obtained; The full-band observation data and each of the sub-band observation data are processed to obtain the corresponding peak complex response, peak phase and peak distance; The peak distance corresponding to the full-band observation data is used as the coarse distance; pairwise interferometry is performed on multiple sub-band observation data to obtain the interferometric phase difference corresponding to different sub-band combinations; Based on the effective center frequency difference and the corresponding synthesis slope corresponding to different sub-band combinations, a distance estimation relationship is constructed, and the integer ambiguity is determined by combining the coarse distance measurement to obtain the distance estimation values ​​corresponding to multiple sub-band combinations. Multiple distance estimates are fused to obtain a single-frame high-precision distance estimation result; when a reference distance exists, the distance offset is obtained based on the single-frame high-precision distance estimation result and the reference distance; in the structural deformation monitoring scenario, the distance offset is used as the displacement.

[0009] In some implementations, the observation data of multiple sub-bands are obtained through time-domain zoning or frequency-domain zoning; in the time-domain zoning method, the intervals of each sub-band are separated from each other or partially overlap.

[0010] In some embodiments, the processing of the full-band observation data and each of the sub-band observation data includes range-dimensional processing and Doppler-dimensional processing; the range-dimensional processing employs a range focusing and peak extraction method; the Doppler-dimensional processing employs a Doppler-dimensional peak extraction or energy enhancement method.

[0011] In some implementations, the interferometric phase difference corresponding to the subband combination is constituted by the difference in peak phase of the observation data of the two subbands involved in the interferometry, and is limited to the principal value range.

[0012] In some implementations, the fusion is performed by weighting based on one or more of the following: peak (complex) response amplitude, signal-to-noise ratio, phase stability, coherence index, synthesis slope corresponding to sub-band frequency interval, and ranging sensitivity.

[0013] Furthermore, the weights for weighted fusion are determined by the geometric mean of the peak complex response amplitudes of the two subband observation data involved in the interferometry and the absolute value of the corresponding composite slope.

[0014] In some implementations, the distance offset is used as the displacement of the structure under test along the radar line of sight, for structural deformation monitoring or micro-displacement monitoring.

[0015] Secondly, a high-precision ranging system based on single-frame segmented interferometry of nonlinear radar is provided to realize the high-precision ranging method based on single-frame segmented interferometry of nonlinear radar as described above. The system includes a nonlinear radar and a cooperative target disposed on the surface of the structure to be measured. The cooperative target is a target with nonlinear scattering characteristics. The nonlinear radar transmits a fundamental frequency detection signal and receives the harmonic echo generated by the cooperative target.

[0016] In some embodiments, the cooperative target is in a stationary or near-stationary state; the cooperative target is a nonlinear tag fixedly mounted on the surface of the structure to be tested.

[0017] Furthermore, the system also includes the following modules: The first module is used to acquire single-frame nonlinear radar harmonic echo data and construct it into two-dimensional complex observation data for range dimension processing and slow time processing. The second module is used to acquire full-band observation data and multiple sub-band observation data; The third module is used to process the full-band observation data and each of the sub-band observation data respectively to obtain the corresponding peak complex response, peak phase and peak distance; The fourth module is used to perform pairwise interferometry on observation data from multiple sub-bands to obtain the interferometric phase difference corresponding to different sub-band combinations. The fifth module is used to calculate the distance estimate corresponding to multiple sub-band combinations; The sixth module is used to fuse multiple distance estimates to obtain a single-frame high-precision distance estimation result.

[0018] Compared with existing technologies, the advantages of this invention are as follows: 1. This nonlinear radar high-precision ranging method based on single-frame segmented interferometry simultaneously constructs full-band coarse measurement observations and multiple sub-band observations within a single frame echo data. Multiple distance estimation results are obtained through pairwise interferometry of sub-bands, and ambiguity determination and fusion output are completed by combining the full-band coarse measurement results, thereby obtaining more stable and refined single-frame high-precision distance estimation results. The processing flow is simple and easy to implement in engineering. 2. By constructing multiple independent distance estimates through pairwise interferometry of sub-bands, and using full-band coarse measurement distance to complete integer ambiguity determination, measurement errors caused by phase ambiguity can be effectively reduced. 3. The fusion method is not limited to a single weighting rule. Equal weighting fusion, response intensity weighting, signal-to-noise ratio weighting, or other fusion strategies can be adopted according to the application scenario, which has good implementation flexibility. 4. Nonlinear radar can effectively detect and measure the distance of stationary or near-stationary targets with high precision, and can be further applied to structural deformation monitoring (including structural health monitoring and deformation monitoring) and other micro-displacement observation scenarios. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the overall process of a nonlinear radar high-precision ranging method based on single-frame segmented interferometry according to the present invention; Figure 2 This is a schematic diagram comparing the actual distance and the estimated distance in the simulation experiment of this invention; Figure 3 This is a schematic diagram comparing the absolute errors of different methods in the simulation experiment of this invention; Figure 4 This is a schematic diagram of the engineering deployment of the nonlinear radar and nonlinear tag of the present invention; Figure 5 This is a schematic diagram of the distance offset or displacement measurement results in a real-world scenario according to the present invention. Detailed Implementation

[0020] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1: A high-precision ranging method for nonlinear radar based on single-frame segmented interferometry is provided, implemented based on the following nonlinear radar cooperative measurement system: The measurement system includes a nonlinear radar and nonlinear tags, harmonic transponders, target units containing nonlinear devices, or other targets with nonlinear scattering characteristics set on the target; the nonlinear radar transmits a fundamental frequency detection signal and receives harmonic echoes generated by the cooperative target; combined with... Figure 1As shown, the method includes the following steps: Step 1: Acquire single-frame nonlinear radar harmonic echo data and construct it into two-dimensional complex observation data for range dimension processing and slow time processing; Step 2: Based on the two-dimensional complex observation data, obtain full-band observation data and multiple sub-band observation data; Step 3: Process the full-band observation data and each of the sub-band observation data respectively to obtain the corresponding peak complex response, peak phase and peak distance; Step 4: Use the peak distance corresponding to the full-band observation data as the coarse distance; perform pairwise interferometry on multiple sub-band observation data to obtain the interferometric phase difference corresponding to different sub-band combinations; Step 5: Construct a distance estimation relationship based on the effective center frequency difference and the corresponding synthesis slope of different sub-band combinations, and combine it with the coarse distance measurement to complete the integer ambiguity determination, and obtain the distance estimation values ​​corresponding to multiple sub-band combinations; Step 6: Fuse multiple distance estimates to obtain a single-frame high-precision distance estimation result; when a reference distance exists, obtain the distance offset based on the single-frame high-precision distance estimation result and the reference distance; in the structural deformation monitoring scenario, the distance offset is used as the displacement.

[0022] This nonlinear radar high-precision ranging method based on single-frame segmented interferometry simultaneously constructs full-band coarse measurement observations and multiple sub-band observations within a single frame of echo data. Multiple distance estimation results are obtained through pairwise sub-band interferometry, and ambiguity determination and fusion output are completed by combining the full-band coarse measurement results, thereby obtaining more stable and refined single-frame high-precision distance estimation results. When there is a reference distance or multi-time observation results, the distance offset can be further obtained, and the distance offset can be used as a displacement in the structural deformation monitoring scenario.

[0023] In some implementations, the observation data of multiple sub-bands in step 2 are obtained by time-domain zoning or frequency-domain zoning; in time-domain zoning, the intervals of each sub-band are separated from each other, but may also partially overlap.

[0024] In step 3, the distance dimension processing can employ both distance dimension processing and Doppler dimension processing; the distance dimension processing can employ DFT, FFT, CZT, Zoom-FFT (refined fast Fourier transform) or other processing methods capable of achieving distance focusing and spectral peak extraction; the Doppler dimension processing can employ DFT, FFT, CZT or other processing methods capable of achieving Doppler spectral peak extraction or energy enhancement.

[0025] In some implementations, the interferometric phase difference corresponding to the sub-band combination is constituted by the peak phase difference of the observation data from the two sub-bands involved in the interferometry, and is limited to the principal value range. The fusion is performed by weighting the data based on one or more of the following: peak (complex) response amplitude, signal-to-noise ratio, phase stability, coherence index, the synthesis slope corresponding to the sub-band frequency interval, and ranging sensitivity. The weights for the weighted fusion are jointly determined based on the geometric mean of the peak complex response amplitudes of the two sub-band observation data involved in the interferometry and the absolute value of the corresponding synthesis slope.

[0026] The following section provides a further explanation of this method in conjunction with the frequency-modulated continuous wave (FMCV) system.

[0027] In one embodiment, the nonlinear radar employs a frequency-modulated continuous wave (FMCV) system, first performing descrambling mixing on the received signal and the reference signal, and then sampling the resulting intermediate frequency (IF) signal. For The target is the intermediate frequency signal after deskewing. It can be represented as: , in, For the first The echo amplitude of each target, For carrier frequency, For frequency modulation slope, To save time, For slow time, The speed of electromagnetic wave propagation. The initial radial distance to the target. For the target radial velocity, j It represents the imaginary unit.

[0028] In the time-domain band-segmented implementation, let the fast-time sampling sequence after de-scratching of a single pulse be represented as follows: ,in This represents the sequence number of the fast-time sampling point. Let the first... The fast-time cutoff interval corresponding to each sub-band is: Then the first Sub-band cutoff window function It can be represented as: , in, This indicates the number of sub-bands. Therefore, the [number]th... The sub-band time-domain signal can be represented as: .

[0029] For the time-domain band-division implementation, the first The center time corresponding to each sub-band It can be represented as: , in, This refers to the fast-time sampling frequency. For the frequency-modulated continuous wave implementation, if the starting frequency of the transmitted signal in the fast-time direction is... The frequency modulation slope is Then the first The effective center frequency of each sub-band It can be represented as: .

[0030] If partial overlap between adjacent sub-bands is allowed, then their fast-time truncation intervals satisfy: .

[0031] For the frequency domain segmentation implementation, the first The effective center frequency of each sub-band can also be determined by the spectral center or weighted average frequency of the corresponding sub-band. This zoning method facilitates obtaining observation results for multiple sub-bands with different equivalent center frequencies and provides a foundation for subsequent zonal interferometric ranging.

[0032] After performing range-dimensional processing and Doppler-dimensional processing on the full-band observation data or the observation data of each sub-band, the corresponding range-Doppler domain response can be obtained. Taking the two-dimensional Fourier transform as an example, its form can be expressed as: , The proportional term includes the target's envelope distribution in the range and Doppler dimensions, while the phase term in the exponential term contains target range information. At the target peak cell, the complex response phase mainly reflects the target range-related phase. After performing the corresponding range and Doppler processing on the full band or any subband, its range-Doppler domain response is denoted as... ,in Indicates full band or number Each sub-band. Extracting the target peak cell yields the peak complex response: , The corresponding peak phase is: , The corresponding peak distance is: , in, and They represent the first The distance-dimensional frequency and Doppler frequency at which the peak value of the target in each frequency band is located. When taking the whole belt, It can be used as a coarse distance for subsequent integer ambiguity determination; when When different sub-bands are selected, the extracted peak phase can be used for subsequent zonal interference distance estimation.

[0033] In a preferred embodiment, let the coarse measurement distance of the entire band be... , No. The and the first The peak phases of each sub-band are respectively and Then the interference phase difference corresponding to the sub-band interference can be expressed as: , in, This indicates that the phase is restricted to the principal value range.

[0034] Let the first The and the first The effective center frequencies of the sub-bands are respectively and The corresponding composite slope is: , in, The electromagnetic wave propagation speed is given by the combined slope, which is determined by the effective center frequency difference of the sub-bands and reflects the ranging sensitivity of the corresponding sub-band combination.

[0035] Integer fuzziness The option can be selected to make the sub-band interference distance estimate closest to the full-band coarse measurement distance. Integers, that is: .

[0036] In a preferred embodiment This can be further expressed as: , From this, we can obtain the distance estimate corresponding to the sub-band interference: , The range estimates of all sub-band interferometry are fused to obtain the final high-precision range estimate for a single frame. : , in, For the first , The weights of the subband interference results can be determined in one embodiment based on one or more of the following: peak response amplitude, signal-to-noise ratio, phase stability, coherence index, synthesis slope corresponding to the subband frequency interval, or ranging sensitivity; in a preferred embodiment, the weights can be determined jointly based on the geometric mean of the peak response amplitudes of the two subbands involved in the interference and the absolute value of the synthesis slope.

[0037] When the reference distance is When the target distance offset is, it can be expressed as: .

[0038] In structural deformation monitoring scenarios, the target distance offset can be used as the displacement of the structure under test along the radar line of sight.

[0039] The cooperative target can be stationary or near-stationary. In stationary or near-stationary target scenarios, because nonlinear radar can effectively suppress linear static background clutter, it can still maintain effective detection and high-precision range measurement of the cooperative target.

[0040] Example 2: This example provides a further detailed explanation of the algorithm flow and simulation verification process of the present invention.

[0041] This embodiment employs a second harmonic radar. The nonlinear radar transmits a fundamental frequency detection signal to a nonlinear tag deployed on the surface of the target and receives the second harmonic echo generated by the tag. The fundamental frequency transmission signal carrier frequency is 9.4 GHz with a full bandwidth of 300 MHz; the harmonic echo carrier frequency is 18.8 GHz with a full bandwidth of 600 MHz. Correspondingly, the harmonic echo wavelength is approximately 15.96 mm, and the conventional range resolution calculated based on the 600 MHz full bandwidth is approximately 0.25 m. It should be noted that the conventional range resolution characterizes the physical resolution capability of the system under full bandwidth conditions, while the subsequent fine spectral peak estimation through CZT and other methods, as well as band interferometry, improves the accuracy of parameter estimation; these are different concepts. The deskewed single-frame data is sampled to form a two-dimensional complex data matrix. In this embodiment, the data matrix used for processing has a size of 500. 512, where the number of fast-time sampling points is 500 and the number of slow-time pulses is 512.

[0042] Please continue reading Figure 1 The single-frame segmented interferometric high-precision distance measurement process used in this embodiment includes the following steps: Step 1: Obtain the deskewed single-frame harmonic echo data and sample it to form a 500 A two-dimensional complex data matrix of 512.

[0043] Step 2: Perform full-band and sub-band truncation on the single-frame two-dimensional complex data matrix. The full-band observation data is taken from fast time point 0 to 499. Three sub-band observation data points are taken, each with a bandwidth of 250 sampling points, and adjacent sub-bands overlap by 125 sampling points. The fast time sampling intervals corresponding to the three sub-bands are points 0 to 249, 125 to 374, and 250 to 499, respectively.

[0044] Step 3: Apply two-dimensional Hann windows to the full-band observation data and the three sub-band observation data respectively, and perform range dimension processing and Doppler dimension processing respectively. In this embodiment, CZT is used for range dimension processing, and FFT is used for Doppler dimension processing.

[0045] Step 4: Extract the range peak values ​​on the zero Doppler cells from the processing results of the full-band observation data and the observation data of each sub-band, and obtain the peak complex response, peak phase and peak distance. The peak distance corresponding to the full-band observation data is used as the coarse distance measurement.

[0046] Step 5: Combine the three subbands in pairs to form three subband combinations: subband 1-2, subband 1-3, and subband 2-3. For each subband combination, calculate the difference in peak phase between the two subbands to obtain the corresponding interference phase difference. The full-band coarse distance measurement is used for integer ambiguity determination in subband interference distance estimation, thereby obtaining the distance estimate for that subband.

[0047] Step 6: Weighted fusion of the distance estimates corresponding to the three sub-band combinations is performed to output a single-frame high-precision distance estimation result. In this embodiment, the fusion weights are jointly determined based on the ranging sensitivity reflected by the peak response amplitudes of the two sub-bands involved in the interferometry and the composite slope of the corresponding combination.

[0048] The effectiveness of this method can be verified through the following simulation experiments. Please see... Figure 2 and Figure 3 This embodiment uses a single-target simulation scenario. The target reference distance is set to 34.0m, and the actual distance offset varies linearly between 0mm and 50mm. A total of 100 test points are set, and the signal-to-noise ratio is 10dB.

[0049] The simulation calculated the actual distance, the full-band coarse measurement result, the sub-band interferometric distance estimate, and the sub-band weighted fusion result. Statistical analysis of the results file shows that the average absolute error of the full-band coarse measurement is 1.0000 mm, and the average absolute error of the sub-band weighted fusion is 0.0887 mm. In other words, under the conditions of a harmonic echo wavelength of approximately 15.96 mm and a conventional distance resolution of approximately 0.25 m corresponding to the full bandwidth, this algorithm achieves an average absolute error of 0.0887 mm through band-specific interferometry and sub-band weighted fusion, reaching sub-millimeter level parameter estimation accuracy, which is significantly better than the full-band coarse measurement result.

[0050] Figure 2 A comparison of distances is presented, including the true distance, the coarse measurement results of the entire band, the estimated sub-band interferometric distance, and the weighted fusion results of the sub-band. Figure 3 A comparison of the corresponding absolute errors is given. Figure 2 and Figure 3It can be seen that after subband interference and subband weighted fusion processing, the measurement results are significantly better than the full-band coarse measurement results, indicating that the present invention can improve the accuracy of distance parameter estimation under single-frame conditions without changing the full-band physical distance resolution.

[0051] Example 3: This example provides a real-world measurement scenario.

[0052] Please see Figure 4 In real-world scenarios, nonlinear radar is deployed at a safe observation location outside the area to be measured, and nonlinear tags are fixedly installed on the surface of the structure or slope to be measured. The nonlinear radar illuminates and receives signals from the nonlinear tags along the observation direction.

[0053] exist Figure 4 Under the shown deployment conditions, a set of actual collected stationary target measurement data was processed. The full-band observation data consisted of 500 sampling points, from fast time point 0 to 499. The sub-band setup was the same as step 2 of Example 2, i.e., three overlapping sub-bands were selected, each with a bandwidth of 250 sampling points, and adjacent sub-bands overlapping with each other by 125 sampling points. The fast time sampling intervals corresponding to the three sub-bands were points 0 to 249, 125 to 374, and 250 to 499, respectively. Range dimension processing and Doppler dimension processing were performed on the full-band and the three sub-bands, respectively. After extracting the corresponding peak responses, the interference results of three sub-band combinations (sub-band 1-2, sub-band 1-3, and sub-band 2-3) were calculated. Sub-band weighted fusion was then used to obtain the final range offset, which was output as the displacement measurement result in the structural deformation monitoring scenario.

[0054] Figure 5 Displacement measurement results varying with the number of scenarios in a real-world context are presented. Figure 5 It can be seen that the measurement results maintain good stability across multiple stable displacement stages and can reflect the displacement changes between adjacent stages. After segmenting and statistically analyzing the fused results, the mean displacements corresponding to the seven stable stages are 0.0561 mm, 0.9299 mm, 1.8060 mm, 2.6756 mm, 1.7701 mm, 0.9064 mm, and -0.0240 mm, respectively. The displacement step sizes corresponding to adjacent stable stages are 0.8739 mm, 0.8761 mm, 0.8696 mm, -0.9055 mm, -0.8637 mm, and -0.9303 mm, respectively.

[0055] Further statistical analysis revealed that the average intra-segment variance of the fusion results was 0.000793 mm. 2 The mean absolute error is 0.0629 mm. Combined with... Figure 5Based on the segmented statistical results, it can be seen that in actual scenarios, the single-frame segmented interferometric processing flow that combines full-band and overlapping sub-band can stably output high-precision distance offset, and can be used as displacement measurement results in structural deformation monitoring scenarios.

[0056] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A high-precision ranging method for nonlinear radar based on single-frame segmented interferometry, characterized in that, Includes the following steps: Acquire single-frame nonlinear radar harmonic echo data and construct it into two-dimensional complex observation data for range dimension processing and slow time processing; Based on two-dimensional complex observation data, full-band observation data and multiple sub-band observation data are obtained; The full-band observation data and each of the sub-band observation data are processed to obtain the corresponding peak complex response, peak phase and peak distance; The peak distance corresponding to the full-band observation data is used as the coarse distance; pairwise interferometry is performed on multiple sub-band observation data to obtain the interferometric phase difference corresponding to different sub-band combinations; Based on the effective center frequency difference and the corresponding synthesis slope corresponding to different sub-band combinations, a distance estimation relationship is constructed, and the integer ambiguity is determined by combining the coarse distance measurement to obtain the distance estimation values ​​corresponding to multiple sub-band combinations. Multiple distance estimates are fused to obtain a single-frame high-precision distance estimation result; when a reference distance exists, the distance offset is obtained based on the single-frame high-precision distance estimation result and the reference distance. In structural deformation monitoring scenarios, the distance offset is used as a displacement.

2. The high-precision ranging method for nonlinear radar based on single-frame segmented interferometry according to claim 1, characterized in that, Multiple sub-band observation data are obtained through time-domain zoning or frequency-domain zoning; in time-domain zoning, the intervals of each sub-band are separated from each other or partially overlap.

3. The high-precision ranging method for nonlinear radar based on single-frame segmented interferometry according to claim 1, characterized in that, The processing methods for the full-band observation data and the observation data of each sub-band include range dimension processing and Doppler dimension processing; the range dimension processing adopts the processing method of range focusing and spectral peak extraction; the Doppler dimension processing adopts the processing method of Doppler spectral peak extraction or energy enhancement.

4. The high-precision ranging method for nonlinear radar based on single-frame segmented interferometry according to claim 1, characterized in that, The interferometric phase difference corresponding to the sub-band combination is composed of the difference in peak phase of the observation data of the two sub-bands involved in the interferometry, and is limited to the principal value interval.

5. The high-precision ranging method for nonlinear radar based on single-frame segmented interferometry according to claim 1, characterized in that, The fusion is performed by determining weights based on one or more of the following: peak complex response amplitude, signal-to-noise ratio, phase stability, coherence index, synthesis slope corresponding to sub-band frequency interval, and ranging sensitivity.

6. The high-precision ranging method for nonlinear radar based on single-frame segmented interferometry according to claim 5, characterized in that, The weights for weighted fusion are determined by the geometric mean of the peak complex response amplitudes of the two subband observation data involved in the interferometry and the absolute value of the corresponding composite slope.

7. The high-precision ranging method for nonlinear radar based on single-frame segmented interferometry according to claim 1, characterized in that, The distance offset is the displacement of the structure under test along the radar line of sight, and is used for structural deformation monitoring or micro-displacement monitoring.

8. A high-precision ranging system for nonlinear radar based on single-frame segmented interferometry, used to implement the high-precision ranging method for nonlinear radar based on single-frame segmented interferometry as described in any one of claims 1 to 7, characterized in that, The system includes a nonlinear radar and a cooperative target set on the surface of the structure to be tested. The cooperative target is a target with nonlinear scattering characteristics. The nonlinear radar transmits a fundamental frequency detection signal and receives the harmonic echo generated by the cooperative target.

9. The high-precision ranging system for nonlinear radar based on single-frame segmented interferometry according to claim 8, characterized in that, The cooperative target is in a static or near-static state; the cooperative target is a nonlinear label fixedly set on the surface of the structure to be tested.

10. The high-precision ranging system for nonlinear radar based on single-frame segmented interferometry according to claim 8, characterized in that, The system also includes the following modules: The first module is used to acquire single-frame nonlinear radar harmonic echo data and construct it into two-dimensional complex observation data for range dimension processing and slow time processing. The second module is used to acquire full-band observation data and multiple sub-band observation data; The third module is used to process the full-band observation data and each of the sub-band observation data respectively to obtain the corresponding peak complex response, peak phase and peak distance; The fourth module is used to perform pairwise interferometry on observation data from multiple sub-bands to obtain the interferometric phase difference corresponding to different sub-band combinations. The fifth module is used to calculate the distance estimate corresponding to multiple sub-band combinations; The sixth module is used to fuse multiple distance estimates to obtain a single-frame high-precision distance estimation result.

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