Radar jamming effect evaluation method and device combining imaging quality and application performance

Abstract

The application discloses a radar jamming effect evaluation method and device combining imaging quality and application performance, and belongs to the field of synthetic aperture radar image processing. The method comprises the following steps: acquiring a reference complex SAR interferometric pair and a disturbed complex SAR interferometric pair, and extracting reference index values and disturbed index values of multiple evaluation indexes; calculating the normalized degradation degrees of the multiple evaluation indexes based on the reference index values and the disturbed index values; constructing an F-ANP network model to obtain basic weights of the multiple evaluation indexes; constructing a dynamic correction factor according to the normalized degradation degrees, correcting the basic weights to obtain adaptive weights of the multiple evaluation indexes; and calculating the contribution items of the multiple evaluation indexes according to the adaptive weights and the normalized degradation degrees, and summing the contribution items to obtain a comprehensive score. The application improves the adaptability of the evaluation result to different interference styles, different degradation modes and different interference intensities.

Description

Technical Field

[0001] This invention relates to the field of synthetic aperture radar image processing technology, and in particular to a method and apparatus for evaluating radar interference effects that combines imaging quality and application performance. Background Technology

[0002] Synthetic Aperture Radar (SAR) possesses all-weather, all-time, long-range, and high-resolution imaging capabilities. Interferometric Synthetic Aperture Radar (InSAR) refers to SAR that employs interferometric measurement techniques. It obtains terrain elevation, surface deformation, or other interferometric measurement results by registering, conjugate multiplication, coherence estimation, and phase processing two complex SAR images with spatial or temporal baselines. In complex electromagnetic environments, interference not only causes sidelobe lift, decreased contrast, and abnormal information content in images (SAR or InSAR images), but may also disrupt the complex correlation between the primary and secondary images, reducing the average coherence coefficient, deteriorating the continuity and directional consistency of interference fringes, and consequently causing difficulties in phase unwrapping or decreased measurement accuracy.

[0003] SAR interference effect assessment reflects the degree of interference's impact on images, thereby guiding the adjustment of radar anti-jamming parameters. Traditional SAR interference effect assessment mainly includes schemes based on single or a few SAR image quality indicators and schemes based on multi-indicator normalization and static weighting. Schemes based on single or a few SAR image quality indicators typically use image-level indicators such as integral sidelobe ratio, peak sidelobe ratio, image contrast, image entropy, structural similarity, or correlation coefficient, and judge the strength of interference based on changes in a single or a few indicators. These indicators are simple to implement and can describe imaging quality, but cannot fully describe the damage to InSAR coherence links and interferometric phase information. Schemes based on multi-indicator normalization and static weighting normalize and normalize multiple image quality indicators, determine weights, and obtain a comprehensive score through weighted summation. This type of scheme can integrate multiple indicators, but the resulting weights are usually fixed, making it difficult to distinguish between different damage modes such as "significantly deteriorated point targets with acceptable InSAR performance" and "small changes in amplitude map but severe decrease in coherence." Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a radar jamming effect evaluation method and apparatus that combines imaging quality and application performance, thereby improving the adaptability of evaluation results to different jamming patterns, degradation modes, and jamming intensities.

[0005] The technical solution provided by this invention is as follows:

[0006] A method for evaluating radar jamming effects that combines imaging quality and application performance, the method comprising:

[0007] S1: Obtain the reference complex SAR interferometric pair and the disturbed complex SAR interferometric pair to be evaluated in the same area, and determine the point target area, the distributed target area and the interferometric performance evaluation area;

[0008] S2: Extract the baseline index value and the disturbed index value of multiple evaluation indicators based on the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair;

[0009] The evaluation indicators include point target quality indicators, distributed target quality indicators, and InSAR application performance indicators. These indicators are extracted from the point target region, distributed target region, and interferometric performance evaluation region, respectively. The point target quality indicators include azimuth integral sidelobe ratio and range integral sidelobe ratio. The distributed target quality indicators include contrast and image entropy. The InSAR application performance indicators include average coherence coefficient and interferometric fringe sharpness.

[0010] S3: Calculate the positive degradation amount of each evaluation indicator based on the baseline and disturbed indicator values ​​and normalize it to obtain the normalized degradation degree of each evaluation indicator; wherein, the larger the value of the positive degradation amount of the evaluation indicator, the more severe the disturbance damage.

[0011] S4: Divide the various evaluation indicators into point target quality indicator set, distributed target quality indicator set and InSAR application performance indicator set according to their types, and construct the F-ANP network model to obtain the basic weights of each evaluation indicator.

[0012] S5: Construct a dynamic correction factor based on the normalized degradation degree of each evaluation indicator, and correct the basic weights to obtain the adaptive weights of each evaluation indicator.

[0013] S6: Calculate the contribution of each evaluation indicator based on the adaptive weight and normalized degradation degree of each evaluation indicator, and sum the contribution of all evaluation indicators to obtain a comprehensive score representing the interference effect.

[0014] Furthermore, the method also includes: S7: summing the contribution terms of the point target quality index, the distributed target quality index, and the InSAR application performance index respectively to obtain the point target quality degradation score, the distributed target quality degradation score, and the application performance degradation score, and determining the main degradation source based on the point target quality degradation score, the distributed target quality degradation score, and the application performance degradation score.

[0015] Further, S2 includes: S201: Determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the reference complex SAR interferometric pair, calculate the integral side lobe ratio along the azimuth and range directions respectively, and obtain the reference index values ​​of the azimuth integral side lobe ratio and the range integral side lobe ratio.

[0016] S202: Determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the disturbed complex SAR interferometer pair, and calculate the integral side lobe ratio along the azimuth and range directions respectively to obtain the disturbed index values ​​of the azimuth integral side lobe ratio and the range integral side lobe ratio.

[0017] S211: Calculate the baseline index value and the disturbed index value of the contrast based on the standard deviation and mean of the distribution target area of ​​the baseline complex SAR interferometer pair and the disturbed complex SAR interferometer pair;

[0018] S212: Calculate the baseline index value and the disturbed index value of the image entropy based on the gray-level histogram or amplitude histogram of the target region of the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair.

[0019] S221: Set a local window within the interferometric performance evaluation area, calculate the local coherence coefficient based on the cross-correlation and energy of the two complex SAR channels of the reference complex SAR interferometer pair within the local window, and average the local coherence coefficients of each local window to obtain the reference index value of the average coherence coefficient.

[0020] S222: Calculate the local coherence coefficient based on the cross-correlation and energy of the two complex SAR channels of the disturbed complex SAR interferometer pair within the local window, and average the local coherence coefficients of each local window to obtain the disturbed index value of the average coherence coefficient.

[0021] S223: Calculate the phase consistency term based on the average magnitude of the complex phase vector within the local window of the reference complex SAR interferometer pair, calculate the phase gradient stability term based on the variance of the interferometric phase gradient within the local window of the reference complex SAR interferometer pair, and calculate the reference index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the reference complex SAR interferometer pair.

[0022] S224: Calculate the phase consistency term based on the average magnitude of the complex phase vector within the local window of the disturbed complex SAR interferometer pair, calculate the phase gradient stability term based on the variance of the interferometric phase gradient within the local window of the disturbed complex SAR interferometer pair, and calculate the disturbance index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the disturbed complex SAR interferometer pair.

[0023] Furthermore, S3 includes: S31: calculating the positive degradation of the contrast, average coherence coefficient, and interference fringe sharpness based on the decrease in the reference index values ​​of the contrast, average coherence coefficient, and interference fringe sharpness relative to the disturbed index values;

[0024] S32: Calculate the positive degradation of the azimuth integral sidelobe ratio and the range integral sidelobe ratio based on the increment of the disturbed index values ​​of the azimuth integral sidelobe ratio and the range integral sidelobe ratio relative to the reference index values;

[0025] S33: Calculate the positive degradation of the image entropy based on the deviation of the disturbed index value of the image entropy from the reference index value;

[0026] S34: Set upper and lower cutoff thresholds to cut off and normalize the positive degradation of each evaluation indicator to obtain the normalized degradation degree of each evaluation indicator.

[0027] Furthermore, S4 includes: S41: Dividing the various evaluation indicators into a set of point target quality indicators, a set of distributed target quality indicators, and a set of InSAR application performance indicators according to their categories, and constructing an F-ANP network model;

[0028] S42: Construct a fuzzy judgment matrix that reflects the internal dependencies of each evaluation index and the dependencies between the point target quality index set, the distributed target quality index set, and the InSAR application performance index set;

[0029] S43: Calculate the local weights based on the fuzzy judgment matrix and construct an unweighted hypermatrix;

[0030] S44: Based on the component weights of the point target quality index set, the distributed target quality index set, and the InSAR application performance index set, the unweighted hypermatrix is ​​block-weighted to obtain a column-randomized weighted hypermatrix.

[0031] S45: Perform limit sorting on the weighted supermatrix to obtain the basic weights of each evaluation index.

[0032] Furthermore, S5 includes: S51: Constructing a dynamic correction factor based on the normalized degradation degree of each evaluation index;

[0033] ,in, and These are the normalized degradation degree and dynamic correction factor of the i-th evaluation index, respectively. , To adaptively adjust parameters, The function used to construct the dynamic correction factor. Satisfy The requirement of monotony without reduction;

[0034] S52: Adjust the basic weights according to the dynamic correction factor to obtain the adaptive weights of each evaluation index;

[0035] ,in, and These are the basic weight and adaptive weight of the i-th evaluation indicator, respectively.

[0036] Furthermore, S6 includes: S61: Calculating the contribution of each evaluation indicator based on the adaptive weight and normalized degradation degree of each evaluation indicator;

[0037] ,in, The contribution of the i-th evaluation indicator;

[0038] S62: Sum the contribution items of all evaluation indicators to obtain a comprehensive score representing the interference effect. ;

[0039]

[0040] A radar jamming effect evaluation device that combines imaging quality and application performance, the device comprising:

[0041] The complex SAR data acquisition module is used to acquire the reference complex SAR interferometric pairs and the disturbed complex SAR interferometric pairs to be evaluated in the same area, and to determine the point target area, the distributed target area and the interferometric performance evaluation area.

[0042] The index value extraction module is used to extract the baseline index value and the disturbed index value of multiple evaluation indicators based on the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair.

[0043] The evaluation indicators include point target quality indicators, distributed target quality indicators, and InSAR application performance indicators. These indicators are extracted from the point target region, distributed target region, and interferometric performance evaluation region, respectively. The point target quality indicators include azimuth integral sidelobe ratio and range integral sidelobe ratio. The distributed target quality indicators include contrast and image entropy. The InSAR application performance indicators include average coherence coefficient and interferometric fringe sharpness.

[0044] The degradation degree calculation module is used to calculate the positive degradation amount of each evaluation indicator based on the baseline indicator value and the disturbed indicator value of each evaluation indicator and normalize it to obtain the normalized degradation degree of each evaluation indicator; wherein, the larger the value of the positive degradation amount of the evaluation indicator, the more severe the disturbance damage.

[0045] The basic weight determination module divides the various evaluation indicators into point target quality indicator set, distributed target quality indicator set and InSAR application performance indicator set according to their types, and constructs an F-ANP network model to obtain the basic weights of each evaluation indicator.

[0046] The dynamic weight correction module is used to construct a dynamic correction factor based on the normalized degradation degree of each evaluation indicator, and correct the basic weight to obtain the adaptive weight of each evaluation indicator.

[0047] The comprehensive scoring module is used to calculate the contribution of each evaluation indicator based on the adaptive weights and normalized degradation degree of each evaluation indicator, and to sum the contribution of all evaluation indicators to obtain a comprehensive score representing the interference effect.

[0048] Furthermore, the device also includes a degradation source discrimination module, which is used to sum the contribution terms of point target quality index, distributed target quality index and InSAR application performance index respectively to obtain point target quality degradation score, distributed target quality degradation score and application performance degradation score, and to determine the main degradation source based on the point target quality degradation score, distributed target quality degradation score and application performance degradation score.

[0049] Furthermore, the index value extraction module includes: a first calculation unit, used to determine the main lobe region and the side lobe region in the two-dimensional impulse response corresponding to the point target region of the reference complex SAR interferometric pair, calculate the integral side lobe ratio along the azimuth and range directions respectively, and obtain the reference index values ​​of the azimuth integral side lobe ratio and the range integral side lobe ratio.

[0050] The second calculation unit is used to determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the disturbed complex SAR interferometer pair, and calculate the integral side lobe ratio along the azimuth and range directions respectively to obtain the disturbed index values ​​of the azimuth integral side lobe ratio and the range integral side lobe ratio.

[0051] The third calculation unit is used to calculate the baseline index value and the disturbed index value of the contrast based on the standard deviation and mean of the distribution target area of ​​the baseline complex SAR interferometer pair and the disturbed complex SAR interferometer pair.

[0052] The fourth calculation unit is used to calculate the baseline index value and the disturbed index value of the image entropy based on the gray-level histogram or amplitude histogram of the distribution target area of ​​the baseline complex SAR interferometer pair and the disturbed complex SAR interferometer pair.

[0053] The fifth calculation unit is used to set a local window in the interferometric performance evaluation area, calculate the local coherence coefficient based on the cross-correlation and energy of the two complex SAR channels of the reference complex SAR interferometer pair in the local window, and average the local coherence coefficients of each local window to obtain the reference index value of the average coherence coefficient.

[0054] The sixth calculation unit is used to calculate the local coherence coefficient based on the cross-correlation and energy of the two complex SAR channels of the disturbed complex SAR interferometer pair within the local window, and to average the local coherence coefficients of each local window to obtain the disturbed index value of the average coherence coefficient.

[0055] The seventh calculation unit calculates a phase consistency term based on the average magnitude of the complex phase vector within a local window of the reference complex SAR interferometer pair, calculates a phase gradient stability term based on the variance of the interferometric phase gradient within a local window of the reference complex SAR interferometer pair, and calculates a reference index value for the sharpness of the interferometric fringes based on the phase consistency term and the phase gradient stability term of the reference complex SAR interferometer pair.

[0056] The eighth calculation unit calculates a phase consistency term based on the average magnitude of the complex phase vector within a local window of the disturbed complex SAR interferometer pair, calculates a phase gradient stability term based on the variance of the interferometric phase gradient within a local window of the disturbed complex SAR interferometer pair, and calculates the disturbance index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the disturbed complex SAR interferometer pair.

[0057] Furthermore, the degradation calculation module includes: a degradation calculation unit, used to calculate the positive degradation of the contrast, average coherence coefficient and interference fringe sharpness based on the degradation of the baseline index values ​​of the contrast, average coherence coefficient and interference fringe sharpness relative to the disturbed index values.

[0058] An incremental calculation unit is used to calculate the positive degradation of the azimuth integral sidelobe ratio and the range integral sidelobe ratio based on the increment of the disturbed index values ​​of the azimuth integral sidelobe ratio and the range integral sidelobe ratio relative to the reference index values.

[0059] The deviation calculation unit is used to calculate the positive degradation of the image entropy based on the deviation of the disturbed index value of the image entropy from the reference index value.

[0060] The normalization module is used to set the upper and lower cutoff thresholds, and to truncate and normalize the positive degradation of each evaluation indicator to obtain the normalized degradation degree of each evaluation indicator.

[0061] Furthermore, the basic weight determination module includes: a model building unit, used to divide the various evaluation indicators into a set of point target quality indicators, a set of distributed target quality indicators, and a set of InSAR application performance indicators according to their categories, and to build an F-ANP network model;

[0062] The fuzzy judgment matrix construction unit is used to construct a fuzzy judgment matrix that reflects the internal dependencies of various evaluation indicators and the dependencies between the point target quality indicator set, the distributed target quality indicator set, and the InSAR application performance indicator set.

[0063] An unweighted hypermatrix construction unit is used to calculate local weights and construct an unweighted hypermatrix based on the fuzzy judgment matrix.

[0064] The weighted hypermatrix generation unit is used to perform block weighting on the unweighted hypermatrix according to the component weights of the point target quality index set, the distributed target quality index set, and the InSAR application performance index set to obtain a column-random weighted hypermatrix.

[0065] The sorting unit is used to perform limit sorting on the weighted supermatrix to obtain the basic weights of each evaluation index.

[0066] Furthermore, the dynamic weight correction module includes: a dynamic correction factor construction unit, used to construct dynamic correction factors based on the normalized degradation degree of each evaluation index;

[0067] ,in, and These are the normalized degradation degree and dynamic correction factor of the i-th evaluation index, respectively. , To adaptively adjust parameters, The function used to construct the dynamic correction factor. Satisfy The requirement of monotony without reduction;

[0068] The correction unit is used to correct the basic weights according to the dynamic correction factor to obtain the adaptive weights of each evaluation index.

[0069] ,in, and These are the basic weight and adaptive weight of the i-th evaluation indicator, respectively.

[0070] Furthermore, the comprehensive scoring module includes:

[0071] The contribution calculation unit is used to calculate the contribution of each evaluation indicator based on the adaptive weight and normalized degradation degree of each evaluation indicator.

[0072] ,in, The contribution term for the i-th evaluation indicator;

[0073] The comprehensive scoring calculation unit is used to sum the contribution items of all evaluation indicators to obtain a comprehensive score representing the interference effect. ;

[0074]

[0075] The present invention has the following beneficial effects:

[0076] This invention jointly evaluates the point target quality, distributed target quality, and InSAR application performance of benchmark complex SAR interferometric pairs and disturbed complex SAR interferometric pairs. It utilizes the F-ANP basic weights and a dynamic correction mechanism for sample degradation to output a comprehensive interference effect score and the main sources of degradation. This invention integrates point target quality, distributed target quality, and InSAR application performance into the unified evaluation process, enabling simultaneous and unified evaluation of complex interferometric data, point target quality, distributed target quality, and InSAR application performance. This ensures that the comprehensive score reflects both SAR imaging quality and interferometric mission performance. This invention takes complex primary and secondary image pairs as input and forms a three-category, six-index degradation vector based on unified registration and quality control. It obtains basic weights through F-ANP, avoiding simple equal weighting or isolated index weighting. The basic weights are adjusted according to the six degradation degrees of the current sample, enabling the index weights to adaptively change according to the actual degradation mode of the current sample, allowing the score to respond to different interference-to-signal ratios and different degradation structures. The invention outputs a comprehensive score and the main sources of degradation, forming a recalcible and interpretable comprehensive score and degradation source discrimination result, thereby improving the adaptability of the evaluation results to different interference patterns, degradation modes, and interference intensities. Attached Figure Description

[0077] Figure 1 This is a flowchart illustrating the radar jamming effect evaluation method combining imaging quality and application performance according to the present invention.

[0078] Figure 2 The amplitude diagram of the complex SAR interferometer pair under interference-free conditions;

[0079] Figure 3 Amplitude plot of complex SAR interferometric pairs under a signal-to-interference ratio of -10 dB;

[0080] Figure 4 Amplitude plot of complex SAR interferometric pairs under a signal-to-interference ratio of -5 dB;

[0081] Figure 5 Amplitude plot of complex SAR interferometric pairs under a 0dB interference-to-signal ratio condition;

[0082] Figure 6Amplitude plot of complex SAR interferometric pairs under a 5dB interference-to-signal ratio condition;

[0083] Figure 7 Amplitude plot of complex SAR interferometric pairs under a 10dB interference-to-signal ratio condition;

[0084] Figure 8 A schematic diagram of the point target region, the distributed target region, and the interferometric performance evaluation region;

[0085] Figure 9 This is a schematic diagram of the radar jamming effect evaluation device that combines imaging quality and application performance according to the present invention. Detailed Implementation

[0086] To make the technical problems, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. The components of the embodiments of this invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0087] This invention provides a method for evaluating radar interference effects that combines imaging quality and application performance, such as... Figure 1 As shown, the method includes:

[0088] S1: Obtain the reference complex SAR interferometric pair and the disturbed complex SAR interferometric pair to be evaluated in the same area, and determine the point target area, the distributed target area and the interferometric performance evaluation area.

[0089] Among them, the reference complex SAR interferometric pair is a complex SAR interferometric pair under no interference or weak interference conditions. Both the reference complex SAR interferometric pair and the disturbed complex SAR interferometric pair to be evaluated include two complex SAR channels. At the same time, this step can also obtain the interferometric processing results of the two complex SAR channels, which can be used to calculate subsequent evaluation indicators.

[0090] A point target region refers to a region in a SAR image dominated by a single strong scatterer. Echo energy within this region is concentrated in a single resolution cell, exhibiting stable scattering characteristics and low phase noise. In this invention, the point target region is used to calculate the azimuth integral sidelobe ratio and the range integral sidelobe ratio. A distributed target region refers to a planar region composed of numerous spatially distributed sub-scatterers. Echo energy is dispersed across multiple adjacent resolution cells, exhibiting statistically uniform overall scattering characteristics. In this invention, the distributed target region is used to calculate contrast and image entropy. An interferometric performance evaluation region refers to a reference region specifically designated in the interferometric processing flow for quantitatively verifying the quality of interferometric data and the accuracy of inversion results. In this invention, the interferometric performance evaluation region is used to calculate the average coherence coefficient and the sharpness of interferometric fringes.

[0091] S2: Extract the baseline and disturbed index values ​​of multiple evaluation indicators based on the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair.

[0092] The evaluation metrics include point target quality metrics, distributed target quality metrics, and InSAR application performance metrics. These metrics are extracted from the point target region, distributed target region, and interferometric performance evaluation region, respectively. Point target quality metrics include azimuth integral sidelobe ratio and range integral sidelobe ratio; distributed target quality metrics include contrast and image entropy; and InSAR application performance metrics include average coherence coefficient and interferometric fringe sharpness.

[0093] This invention adopts a three-category, six-indicator structure, and the specific meanings of each indicator are shown in Table 1 below:

[0094] Table 1: InSAR Three Categories and Six Indicators System

[0095]

[0096] The focus of this invention is not on redefining individual indicators, but on organizing the aforementioned indicators into a joint indicator system suitable for SAR interference effect assessment, and combining it with the F-ANP basic weights and dynamic degradation correction mechanism. Regarding the specific calculation process and formulas for each indicator, mature calculation methods from published literature can be used, or calculations can be performed using the detailed examples provided in this invention below:

[0097] S201: Determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the reference complex SAR interferometric pair, and calculate the integral side lobe ratio along the azimuth and range directions respectively to obtain the reference index values ​​of the azimuth integral side lobe ratio and the range integral side lobe ratio.

[0098] S202: Determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the disturbed complex SAR interferometer pair, and calculate the integrated side lobe ratio along the azimuth and range directions respectively to obtain the disturbed index values ​​of the azimuth integrated side lobe ratio and the range integrated side lobe ratio.

[0099] The formula for calculating the integral sidelobe ratio is as follows:

[0100] ,in, For the integral sidelobe ratio, Main lobe energy, The main lobe and outer sidelobe energy are used. An increase in the integral sidelobe ratio or a decrease in its absolute value usually indicates an increase in sidelobe energy and a decrease in the focusing quality of point targets. Using the above formula, the azimuth integral sidelobe ratio ISLRaz and the range integral sidelobe ratio ISLRrg are calculated for the azimuth and range slices, respectively. For the reference index value, it is calculated based on the reference complex SAR interferometric pair; for the disturbed index value, it is calculated based on the disturbed complex SAR interferometric pair.

[0101] S211: Calculate the baseline and disturbed contrast index values ​​based on the standard deviation and mean of the target area distribution of the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair. The specific calculation formula is as follows:

[0102] ,in, For contrast, and These represent the standard deviation and mean of the target distribution area, respectively. This is a constant greater than zero. Using the above formulas, the baseline and disturbed contrast index values ​​are calculated based on the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair, respectively.

[0103] S212: Calculate the baseline and disturbed index values ​​of image entropy based on the gray-level histograms or amplitude histograms of the target regions of the baseline and disturbed complex SAR interferometric pairs. The specific calculation formulas are as follows:

[0104] ,in, Image entropy, grayscale or amplitude value The probability of a pixel appearing in the target distribution area. B represents the total number of gray levels or amplitudes. Using the above formulas, the baseline and disturbed index values ​​of image entropy are calculated based on the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair, respectively.

[0105] S221: Set up local windows within the interferometric performance evaluation area. Calculate the local coherence coefficients based on the cross-correlation and energy of the two complex SAR channels of the reference complex SAR interferometer pair within the local windows. Then, average the local coherence coefficients of each local window to obtain the benchmark index value of the average coherence coefficient.

[0106] S222: Calculate the local coherence coefficient based on the cross-correlation and individual energy of the two complex SAR channels within a local window of the disturbed complex SAR interferometer pair. Then, average the local coherence coefficients of each local window to obtain the disturbed index value of the average coherence coefficient. The specific calculation formula is as follows:

[0107] ,in, Let be the local coherence coefficient. and For the first in the local window Two complex SAR channel values ​​for each pixel L is the total number of pixels in the local window. for The complex conjugate of the coherence coefficients is used. The average coherence coefficient is obtained by averaging the local coherence coefficients within the preset interferometric performance evaluation region. For the baseline index value, it is calculated based on the baseline complex SAR interferometric pair; for the disturbed index value, it is calculated based on the disturbed complex SAR interferometric pair.

[0108] S223: Calculate the phase consistency term based on the average magnitude of the complex phase vector within the local window of the reference complex SAR interferometer pair, calculate the phase gradient stability term based on the variance of the interferometric phase gradient within the local window of the reference complex SAR interferometer pair, and calculate the benchmark index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the reference complex SAR interferometer pair.

[0109] S224: Calculate the phase consistency term based on the average magnitude of the complex phase vector within the local window of the disturbed complex SAR interferometer pair; calculate the phase gradient stability term based on the variance of the interferometric phase gradient within the local window of the disturbed complex SAR interferometer pair; and calculate the disturbance index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the disturbed complex SAR interferometer pair. The specific calculation formula is as follows:

[0110]

[0111]

[0112]

[0113] in, For the clarity of interference fringes, and These are the phase consistency term and the phase gradient stability term, respectively. A larger value indicates more consistent phase within the window. A larger value indicates a more stable phase gradient. For pixels Interference phase, For local windows, For local windows The total number of pixels, where j is the imaginary unit. For gradient operators, This represents the standard deviation of the interference phase gradient magnitude within the local window.

[0114] S3: Calculate the positive degradation of each evaluation indicator based on the benchmark and disturbed indicator values ​​and normalize it to obtain the normalized degradation degree of each evaluation indicator.

[0115] Among them, the positive degradation of the evaluation index represents the degree of degradation of the disturbed index value relative to the benchmark index value. The larger the positive degradation value, the more severe the damage caused by the disturbance. Let the benchmark index value of the i-th evaluation index be... The disturbance index value is The specific calculation methods for the positive degradation of the aforementioned six evaluation indicators are as follows:

[0116] S31: Calculate the positive degradation of contrast, average coherence coefficient, and interference fringe sharpness based on the decrease in the baseline index values ​​of contrast, average coherence coefficient, and interference fringe sharpness relative to the disturbed index values.

[0117] In this invention, contrast ratio, average coherence coefficient, and interference fringe sharpness are performance retention indicators, and their specific calculation formulas for the decrease are as follows:

[0118] ,in, Let i be the positive degradation amount of the i-th evaluation index. Let i be the decrease in the i-th evaluation indicator. These are contrast ratio, average coherence coefficient, and interference fringe sharpness.

[0119] S32: Calculate the positive degradation of the azimuth integral sidelobe ratio and the range integral sidelobe ratio based on the increments of the disturbed index values ​​of the azimuth integral sidelobe ratio and the range integral sidelobe ratio relative to the reference index values.

[0120] In this invention, the azimuth integral sidelobe ratio and the range integral sidelobe ratio are indicators of degradation increase, and the specific calculation formulas for their increments are as follows:

[0121] ,in, For the increment of the i-th evaluation indicator, That is, the azimuth integral sidelobe ratio and the range integral sidelobe ratio.

[0122] S33: Calculate the positive degradation of image entropy based on the deviation of the disturbed index value of image entropy from the baseline index value.

[0123] In this invention, the deviation can be an absolute deviation, a relative deviation, or a monotonic mapping calibrated by the scene. Taking the relative deviation as an example, the calculation formula is as follows:

[0124] ,in, This is the relative deviation. That is, image entropy.

[0125] S34: Set upper and lower cutoff thresholds to cut off and normalize the positive degradation of each evaluation indicator to obtain the normalized degradation degree of each evaluation indicator.

[0126] , Let i be the normalized degradation degree of the i-th evaluation index. and These are the lower cutoff threshold (zero score reference) and the upper cutoff threshold (full score reference), respectively. Using the above formula, the positive degradation is normalized to [0,1] using the threshold truncation method, thus obtaining the normalized degradation degree.

[0127] S4: The evaluation indicators are categorized into point target quality indicator set, distributed target quality indicator set, and InSAR application performance indicator set, and an F-ANP network model is constructed to obtain the basic weights of each evaluation indicator. A specific implementation example of this step includes:

[0128] S41: Divide the various evaluation indicators into point target quality indicator set, distributed target quality indicator set and InSAR application performance indicator set according to type, and construct the F-ANP network model.

[0129] This invention uses point target quality, distributed target quality, and InSAR application performance as three factor sets. Each factor set contains two indicators and allows dependencies and feedback relationships within and between factor sets to construct an F-ANP network model.

[0130] S42: Construct a fuzzy judgment matrix that reflects the internal dependencies of various evaluation indicators and the dependencies between the point target quality indicator set, the distributed target quality indicator set, and the InSAR application performance indicator set.

[0131] S43: Calculate the local weights based on the fuzzy judgment matrix and construct the unweighted hypermatrix.

[0132] S44: Based on the component weights of the point target quality index set, the distributed target quality index set, and the InSAR application performance index set, the unweighted hypermatrix is ​​block-weighted to obtain a column-randomized weighted hypermatrix.

[0133] S45: Perform limit sorting on the weighted hypermatrix to obtain the basic weights of each evaluation indicator. The basic weights of each evaluation indicator are as follows: and the vectors formed as follows:

[0134]

[0135] S5: Construct a dynamic correction factor based on the normalized degradation degree of each evaluation indicator, correct the basic weights, and obtain the adaptive weights of each evaluation indicator.

[0136] To avoid the basic weights becoming completely fixed across different disturbed samples, this invention performs a secondary correction on the basic weights based on the normalized degradation degree of the current sample. The specific implementation method is as follows:

[0137] S51: Construct dynamic correction factors based on the normalized degradation degree of each evaluation indicator.

[0138] ,in, and These are the normalized degradation degree and dynamic correction factor of the i-th evaluation index, respectively. , To adaptively adjust parameters, The function used to construct the dynamic correction factor. Satisfy The requirement of monotony without reduction.

[0139] S52: Adjust the basic weights according to the dynamic adjustment factor to obtain the adaptive weights of each evaluation index.

[0140] .in, and These are the basic weight and adaptive weight of the i-th evaluation index, respectively.

[0141] Preferably, the dynamic correction factor is in linear form. The corrected adaptive weights are When a certain indicator degrades significantly in the current sample, its correction factor increases, and its weight increases accordingly; conversely, when an indicator degrades only slightly, its relative weight decreases. This preserves the expert prior and indicator dependency information in the F-ANP base weights while ensuring that the scoring responds to the actual degradation characteristics of the current sample. As an alternative implementation, the dynamic correction factor can also be exponential. Power function type Alternatively, a piecewise enhancement function. All of the above functions should satisfy the following condition: The requirement of monotonicity is to ensure that indicators with greater degradation receive relative enhancement in adaptive weights.

[0142] S6: Calculate the contribution of each evaluation indicator based on its adaptive weights and normalized degradation degree, and sum the contributions of all evaluation indicators to obtain a comprehensive score representing the interference effect. Specific calculation methods include:

[0143] S61: Calculate the contribution of each evaluation indicator based on the adaptive weight and normalized degradation degree of each evaluation indicator.

[0144] ,in, This is the contribution item for the i-th evaluation indicator.

[0145] S62: Sum the contributions of all evaluation indicators to obtain a comprehensive score representing the interference effect.

[0146] ,in, For comprehensive scoring, due to , and Therefore, the range of values ​​for R is The larger the value, the stronger the interference effect.

[0147] To determine the main source of interference, the method of this invention further includes: S7: summing the contribution terms of the point target quality index, the distributed target quality index, and the InSAR application performance index respectively to obtain the point target quality degradation score. Distribution target quality degradation score Application performance degradation score The main sources of degradation are determined based on the point target quality degradation score, the distributed target quality degradation score, and the application performance degradation score.

[0148] Among them, if If the value is maximum, then the current interference is determined to primarily affect the quality of the point target; if... If the value is the largest, it is determined to be the primary factor affecting the quality of the distributed target; if If the contribution is the largest, it is determined to have a major impact on application performance. The result of this contribution assessment can be used as an interpretable output of the overall score.

[0149] This invention jointly evaluates the point target quality, distributed target quality, and InSAR application performance of benchmark complex SAR interferometric pairs and disturbed complex SAR interferometric pairs. It utilizes the F-ANP basic weights and a dynamic correction mechanism for sample degradation to output a comprehensive interference effect score and the main sources of degradation. This invention integrates point target quality, distributed target quality, and InSAR application performance into the unified evaluation process, enabling simultaneous and unified evaluation of complex interferometric data, point target quality, distributed target quality, and InSAR application performance. This ensures that the comprehensive score reflects both SAR imaging quality and interferometric mission performance. This invention takes complex primary and secondary image pairs as input and forms a three-category, six-index degradation vector based on unified registration and quality control. It obtains basic weights through F-ANP, avoiding simple equal weighting or isolated index weighting. The basic weights are adjusted according to the six degradation degrees of the current sample, enabling the index weights to adaptively change according to the actual degradation mode of the current sample, allowing the score to respond to different interference-to-signal ratios and different degradation structures. The invention outputs a comprehensive score and the main sources of degradation, forming a recalcible and interpretable comprehensive score and degradation source discrimination result, thereby improving the adaptability of the evaluation results to different interference patterns, degradation modes, and interference intensities.

[0150] The following uses InSAR mode as an example. After evaluating individual indicators for images with different interference-to-signal ratios, the method of this invention is used for comprehensive weighted evaluation.

[0151] Figure 2-7 The image presents a set of interferometric pairs of images from an airborne array interferometric SAR. Figures 2-7 These are amplitude diagrams for interference-free conditions, -10dB interference-to-signal ratio (sample_1), -5dB interference-to-signal ratio (sample_2), 0dB interference-to-signal ratio (sample_3), 5dB interference-to-signal ratio (sample_4), and 10dB interference-to-signal ratio (sample_5), respectively. T1R1 and T1R2 are the two channels of the interferometer pair, respectively. Point target evaluation is performed using... Figure 8 The points within the red box are used to extract the integral sidelobe ratio in the azimuth and range directions. The area within the yellow box is used for target distribution evaluation (to extract contrast and grayscale entropy). The area within the blue box is used for InSAR performance evaluation (to extract the average coherence coefficient and interferometric fringe discernibility).

[0152] The table below shows the results of extracting individual indicators, including six sets of indicators: azimuth integral sidelobe ratio (ISLR), range integral sidelobe ratio (ISLR), contrast, image entropy, mean coherence, and fringe visibility. sample_1 to sample_6 represent images with signal-to-interference ratios of -10dB, -5dB, 0dB, 5dB, and 10dB, respectively.

[0153] Table 2: Results of Individual Indicator Extraction

[0154]

[0155] The normalized degradation degree of each evaluation indicator is calculated using the following formula, as shown in Table 3 below.

[0156] Table 3: Calculation method of normalized degradation degree for each evaluation indicator

[0157]

[0158] This embodiment uses the following F-ANP basic weight vector:

[0159] Dynamically corrected parameters and in accordance with and Calculate the adaptive weights x for each evaluation index i The overall score R is shown in Table 4 below.

[0160] Table 4: Normalized Degradation and Overall Score of Each Evaluation Indicator

[0161]

[0162] The adaptive weights of each evaluation indicator are shown in Table 5 below.

[0163] Table 5: Adaptive weights of each evaluation indicator

[0164]

[0165] The contributing factors of the three categories of indicators and the main sources of degradation are shown in Table 6 below.

[0166] Table 6: Contributions of the Three Types of Indicators and Major Sources of Degradation

[0167]

[0168] From the perspective of verifying the rationality of the comprehensive score, it can be seen that the comprehensive score exhibits both trend consistency and application performance consistency. As the interference-to-signal ratio increases, the comprehensive score should rise overall, consistent with the application degradation trend. Overall, the comprehensive score results can objectively reflect the degree of impact of interference on image quality and image application, demonstrating reasonable judgment. Compared to single indicators, the comprehensive index can compensate for the potential limitations of single indicators, such as their one-sidedness and susceptibility to random factors. It can systematically depict the comprehensive state of the evaluation object and is more suitable for the judgment needs in complex scenarios.

[0169] To comprehensively evaluate the consistency between the overall score and the interference-to-information ratio (JSR), this invention employs Pearson correlation coefficient, Spearman rank correlation coefficient, and Kendall rank correlation coefficient to analyze and compare the correlation coefficients between the scoring results and the JSR (dB). Specifically, the Pearson correlation coefficient reflects the linear consistency between the overall score and the JSR, the Spearman rank correlation coefficient reflects the monotonic consistency of the overall score as the JSR changes, and the Kendall rank correlation coefficient reflects the pairwise consistency among samples with different JSRs. The results are shown in Table 7 below.

[0170] Table 7: Correlation between overall score and interference-to-reliability ratio

[0171]

[0172] As shown in the table above, as the interference-to-information ratio (INR) increases from −10 dB to 10 dB, the overall score improves from 0.3511 to 0.7207. The Pearson correlation coefficient is 0.99685, and the Spearman and Kendall correlation coefficients are both 1, indicating that the overall score of this invention has a strong positive correlation with the INR and maintains a completely consistent monotonic and pairwise ranking relationship.

[0173] The results of the three types of contributions show that the InSAR application performance contribution of all five samples is the maximum value, indicating that the degradation of the average coherence coefficient and fringe sharpness constitutes the main source of damage in this group of samples, which is consistent with the mission sensitivity of InSAR applications to interferometric phase and coherence.

[0174] This invention also provides a radar jamming effect evaluation device that combines imaging quality and application performance, such as... Figure 9 As shown, the device includes:

[0175] The complex SAR data acquisition module 1 is used to acquire the reference complex SAR interferometric pair and the disturbed complex SAR interferometric pair to be evaluated in the same area, and to determine the point target area, the distributed target area and the interferometric performance evaluation area.

[0176] The index value extraction module 2 is used to extract the baseline index value and the disturbed index value of multiple evaluation indicators based on the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair.

[0177] The evaluation metrics include point target quality metrics, distributed target quality metrics, and InSAR application performance metrics. These metrics are extracted from the point target region, distributed target region, and interferometric performance evaluation region, respectively. Point target quality metrics include azimuth integral sidelobe ratio and range integral sidelobe ratio; distributed target quality metrics include contrast and image entropy; and InSAR application performance metrics include average coherence coefficient and interferometric fringe sharpness.

[0178] The degradation degree calculation module 3 is used to calculate and normalize the positive degradation amount of each evaluation indicator based on the baseline and disturbed indicator values, thus obtaining the normalized degradation degree of each evaluation indicator. The larger the positive degradation amount of an evaluation indicator, the more severe the disturbance damage.

[0179] The basic weight determination module 4 divides the various evaluation indicators into point target quality indicator set, distributed target quality indicator set and InSAR application performance indicator set according to their types, and constructs an F-ANP network model to obtain the basic weights of each evaluation indicator.

[0180] The dynamic weight correction module 5 is used to construct dynamic correction factors based on the normalized degradation degree of each evaluation indicator, correct the basic weights, and obtain the adaptive weights of each evaluation indicator.

[0181] The comprehensive scoring module 6 is used to calculate the contribution of each evaluation indicator based on the adaptive weight and normalized degradation degree of each evaluation indicator, and to sum the contribution of all evaluation indicators to obtain a comprehensive score representing the interference effect.

[0182] As an improvement of this embodiment of the invention, the device further includes: a degradation source discrimination module, used to sum the contribution terms of the point target quality index, the distributed target quality index and the InSAR application performance index respectively to obtain the point target quality degradation score, the distributed target quality degradation score and the application performance degradation score, and to determine the main degradation source based on the point target quality degradation score, the distributed target quality degradation score and the application performance degradation score.

[0183] Specifically, the index value extraction module includes: a first calculation unit, used to determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the reference complex SAR interferometric pair, and calculate the integral side lobe ratio along the azimuth and range directions respectively, to obtain the reference index values ​​of the azimuth integral side lobe ratio and the range integral side lobe ratio.

[0184] The second calculation unit is used to determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the disturbed complex SAR interferometer pair, and calculate the integrated side lobe ratio along the azimuth and range directions respectively to obtain the disturbed index values ​​of the azimuth integrated side lobe ratio and the range integrated side lobe ratio.

[0185] The third calculation unit is used to calculate the baseline index value and the disturbed index value of the contrast based on the standard deviation and mean of the distribution target area of ​​the baseline complex SAR interferometer pair and the disturbed complex SAR interferometer pair.

[0186] The fourth calculation unit is used to calculate the baseline index value and the disturbed index value of image entropy based on the gray-level histogram or amplitude histogram of the target area of ​​the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair.

[0187] The fifth calculation unit is used to set local windows within the interferometric performance evaluation area, calculate the local coherence coefficient based on the cross-correlation and energy of the two complex SAR channels of the reference complex SAR interferometer pair within the local window, and average the local coherence coefficients of each local window to obtain the benchmark index value of the average coherence coefficient.

[0188] The sixth calculation unit is used to calculate the local coherence coefficient based on the cross-correlation and energy of the two complex SAR channels of the disturbed complex SAR interferometer pair within the local window, and to average the local coherence coefficients of each local window to obtain the disturbed index value of the average coherence coefficient.

[0189] The seventh calculation unit calculates the phase consistency term based on the average magnitude of the complex phase vector within the local window of the reference complex SAR interferometer pair, calculates the phase gradient stability term based on the variance of the interferometric phase gradient within the local window of the reference complex SAR interferometer pair, and calculates the benchmark index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the reference complex SAR interferometer pair.

[0190] The eighth calculation unit calculates the phase consistency term based on the average magnitude of the complex phase vector within the local window of the disturbed complex SAR interferometer pair, calculates the phase gradient stability term based on the variance of the interferometric phase gradient within the local window of the disturbed complex SAR interferometer pair, and calculates the disturbance index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the disturbed complex SAR interferometer pair.

[0191] Accordingly, the degradation calculation module includes a degradation calculation unit, used to calculate the positive degradation of contrast, average coherence coefficient and interference fringe sharpness based on the decrease of the baseline index values ​​of contrast, average coherence coefficient and interference fringe sharpness relative to the disturbed index values.

[0192] The incremental calculation unit is used to calculate the positive degradation of the azimuth integral sidelobe ratio and the range integral sidelobe ratio based on the increment of the disturbed index values ​​of the azimuth integral sidelobe ratio and the range integral sidelobe ratio relative to the reference index values.

[0193] The deviation calculation unit is used to calculate the positive degradation of image entropy based on the deviation of the perturbed index value of image entropy from the reference index value.

[0194] The normalization module is used to set the upper and lower cutoff thresholds, and to truncate and normalize the positive degradation of each evaluation indicator to obtain the normalized degradation degree of each evaluation indicator.

[0195] As an example, the basic weight determination module includes a model building unit, which is used to divide the various evaluation indicators into a set of point target quality indicators, a set of distributed target quality indicators, and a set of InSAR application performance indicators according to their categories, and to build an F-ANP network model.

[0196] The fuzzy judgment matrix construction unit is used to construct a fuzzy judgment matrix that reflects the internal dependencies of various evaluation indicators and the dependencies between the point target quality indicator set, the distributed target quality indicator set, and the InSAR application performance indicator set.

[0197] An unweighted hypermatrix construction unit is used to calculate local weights and construct an unweighted hypermatrix based on a fuzzy judgment matrix.

[0198] The weighted hypermatrix generation unit is used to perform block weighting on the unweighted hypermatrix based on the component weights of the point target quality index set, the distributed target quality index set, and the InSAR application performance index set, to obtain a column-randomized weighted hypermatrix.

[0199] The sorting unit is used to perform limit sorting on the weighted hypermatrix to obtain the basic weights of each evaluation index.

[0200] In this invention, the dynamic weight correction module includes a dynamic correction factor construction unit, which is used to construct dynamic correction factors based on the normalized degradation degree of each evaluation index.

[0201] ,in, and These are the normalized degradation degree and dynamic correction factor of the i-th evaluation index, respectively. , To adaptively adjust parameters, The function used to construct the dynamic correction factor. Satisfy The requirement of monotony without reduction.

[0202] The correction unit is used to correct the basic weights according to the dynamic correction factor to obtain the adaptive weights of each evaluation index.

[0203] ,in, and These are the basic weight and adaptive weight of the i-th evaluation indicator, respectively.

[0204] Based on the above specific example, the comprehensive scoring module includes: a contribution item calculation unit, used to calculate the contribution item of each evaluation indicator according to the adaptive weight and normalized degradation degree of each evaluation indicator.

[0205] ,in, This is the contribution term to the i-th evaluation indicator.

[0206] The comprehensive scoring calculation unit is used to sum the contribution items of all evaluation indicators to obtain a comprehensive score representing the interference effect. .

[0207]

[0208] The apparatus provided in the above embodiments corresponds one-to-one with the aforementioned method embodiments in terms of its implementation principle and the resulting technical effects. For the sake of brevity, any parts of the apparatus not mentioned in the embodiments can be referred to the corresponding content in the embodiments of the aforementioned methods. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the modules and units described in this apparatus can all be referred to the corresponding processes in the embodiments of the aforementioned methods, and will not be repeated here.

[0209] The radar jamming effect evaluation method combining imaging quality and application performance described in the above embodiments of the present invention can implement business logic through a computer program and record it on a storage medium. This storage medium can be read and executed by a computer to achieve the effects of the scheme described in the method embodiments of this specification. Therefore, the embodiments of the present invention also provide a computer-readable storage medium for evaluating radar jamming effects combining imaging quality and application performance, including a memory for storing processor-executable instructions. When executed by a processor, these instructions implement the steps of the radar jamming effect evaluation method combining imaging quality and application performance described in the foregoing embodiments.

[0210] The storage medium may include a physical device for storing information, typically digitizing the information and then storing it using electrical, magnetic, or optical methods. The storage medium may include: devices that store information using electrical energy, such as various types of memory, like RAM and ROM; devices that store information using magnetic energy, such as hard disks, floppy disks, magnetic tapes, magnetic core memory, bubble memory, and USB flash drives; and devices that store information using optical methods, such as CDs or DVDs. Of course, there are other readable storage media, such as quantum memories and graphene memories.

[0211] The storage medium described above may also include other implementation methods according to the description of the method embodiments. The implementation principle and technical effects of this embodiment are the same as those of the foregoing method embodiments. For details, please refer to the description of the relevant method embodiments, which will not be repeated here.

[0212] This invention also provides an apparatus for evaluating radar jamming effects by combining imaging quality and application performance. The apparatus may be a standalone computer, or it may include an actual operating device that uses one or more of the methods or embodiments described in this specification. The apparatus for evaluating radar jamming effects by combining imaging quality and application performance may include at least one processor and a memory storing computer-executable instructions. When the processor executes the instructions, it implements the steps of any one or more of the radar jamming effect evaluation methods combining imaging quality and application performance.

[0213] The device described above may also include other implementation methods according to the method embodiments. The implementation principle and technical effects of this embodiment are the same as those of the foregoing method embodiments. For details, please refer to the description of the relevant method embodiments, which will not be repeated here.

[0214] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the scope of the technology disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. All should be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating radar jamming effects that combines imaging quality and application performance, characterized in that, The method includes: S1: Obtain the reference complex SAR interferometric pair and the disturbed complex SAR interferometric pair to be evaluated in the same area, and determine the point target area, the distributed target area and the interferometric performance evaluation area; S2: Extract the baseline index value and the disturbed index value of multiple evaluation indicators based on the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair; The evaluation indicators include point target quality indicators, distributed target quality indicators, and InSAR application performance indicators, which are extracted from the point target region, distributed target region, and interferometric performance evaluation region, respectively. The point target quality indicators include azimuth integral sidelobe ratio and range integral sidelobe ratio; the distributed target quality indicators include contrast and image entropy; and the InSAR application performance indicators include average coherence coefficient and interferometric fringe sharpness. S3: Calculate the positive degradation of each evaluation indicator based on the benchmark and disturbed indicator values ​​and normalize it to obtain the normalized degradation degree of each evaluation indicator. The larger the value of the positive degradation of the evaluation index, the more severe the disturbance damage. S4: Divide the various evaluation indicators into point target quality indicator set, distributed target quality indicator set and InSAR application performance indicator set according to their types, and construct the F-ANP network model to obtain the basic weights of each evaluation indicator. S5: Construct a dynamic correction factor based on the normalized degradation degree of each evaluation indicator, and correct the basic weights to obtain the adaptive weights of each evaluation indicator. S6: Calculate the contribution of each evaluation indicator based on the adaptive weight and normalized degradation degree of each evaluation indicator, and sum the contribution of all evaluation indicators to obtain a comprehensive score representing the interference effect.

2. The radar jamming effect evaluation method combining imaging quality and application performance according to claim 1, characterized in that, The method further includes: S7: Sum the contribution terms of the point target quality index, the distributed target quality index, and the InSAR application performance index respectively to obtain the point target quality degradation score, the distributed target quality degradation score, and the application performance degradation score, and determine the main degradation source based on the point target quality degradation score, the distributed target quality degradation score, and the application performance degradation score.

3. The radar jamming effect evaluation method combining imaging quality and application performance according to claim 2, characterized in that, S2 includes: S201: Determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the reference complex SAR interferometric pair, calculate the integral side lobe ratio along the azimuth and range directions respectively, and obtain the reference index values ​​of the azimuth integral side lobe ratio and the range integral side lobe ratio. S202: Determine the main lobe region and side lobe region in the two-dimensional impulse response corresponding to the point target region of the disturbed complex SAR interferometer pair, and calculate the integral side lobe ratio along the azimuth and range directions respectively to obtain the disturbed index values ​​of the azimuth integral side lobe ratio and the range integral side lobe ratio.

4. The radar jamming effect evaluation method combining imaging quality and application performance according to claim 3, characterized in that, S2 further includes: S211: Calculate the baseline index value and the disturbed index value of the contrast based on the standard deviation and mean of the distribution target area of ​​the baseline complex SAR interferometer pair and the disturbed complex SAR interferometer pair; S212: Calculate the baseline index value and the disturbed index value of the image entropy based on the gray-level histogram or amplitude histogram of the target region of the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair.

5. The radar jamming effect evaluation method combining imaging quality and application performance according to claim 4, characterized in that, S2 further includes: S221: Set a local window within the interferometric performance evaluation area, calculate the local coherence coefficient based on the cross-correlation and energy of the two complex SAR channels of the reference complex SAR interferometer pair within the local window, and average the local coherence coefficients of each local window to obtain the reference index value of the average coherence coefficient. S222: Calculate the local coherence coefficient based on the cross-correlation and energy of the two complex SAR channels of the disturbed complex SAR interferometer pair within the local window, and average the local coherence coefficients of each local window to obtain the disturbed index value of the average coherence coefficient. S223: Calculate the phase consistency term based on the average magnitude of the complex phase vector within the local window of the reference complex SAR interferometer pair, calculate the phase gradient stability term based on the variance of the interferometric phase gradient within the local window of the reference complex SAR interferometer pair, and calculate the reference index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the reference complex SAR interferometer pair. S224: Calculate the phase consistency term based on the average magnitude of the complex phase vector within the local window of the disturbed complex SAR interferometer pair, calculate the phase gradient stability term based on the variance of the interferometric phase gradient within the local window of the disturbed complex SAR interferometer pair, and calculate the disturbance index value of the interferometric fringe sharpness based on the phase consistency term and the phase gradient stability term of the disturbed complex SAR interferometer pair.

6. The radar jamming effect evaluation method combining imaging quality and application performance according to claim 5, characterized in that, S3 includes: S31: Calculate the positive degradation of the contrast, average coherence coefficient, and interference fringe sharpness based on the decrease in the baseline index values ​​of the contrast, average coherence coefficient, and interference fringe sharpness relative to the disturbed index values. S32: Calculate the positive degradation of the azimuth integral sidelobe ratio and the range integral sidelobe ratio based on the increment of the disturbed index values ​​of the azimuth integral sidelobe ratio and the range integral sidelobe ratio relative to the reference index values; S33: Calculate the positive degradation of the image entropy based on the deviation of the disturbed index value of the image entropy from the reference index value; S34: Set upper and lower cutoff thresholds to cut off and normalize the positive degradation of each evaluation indicator to obtain the normalized degradation degree of each evaluation indicator.

7. The radar jamming effect evaluation method combining imaging quality and application performance according to claim 6, characterized in that, S4 includes: S41: Divide the various evaluation indicators into point target quality indicator set, distributed target quality indicator set and InSAR application performance indicator set according to type, and construct the F-ANP network model; S42: Construct a fuzzy judgment matrix that reflects the internal dependencies of each evaluation index and the dependencies between the point target quality index set, the distributed target quality index set, and the InSAR application performance index set; S43: Calculate the local weights based on the fuzzy judgment matrix and construct an unweighted hypermatrix; S44: The unweighted hypermatrix is ​​block-weighted according to the component weights of the point target quality index set, the distributed target quality index set, and the InSAR application performance index set to obtain a column-random weighted hypermatrix. S45: Perform limit sorting on the weighted supermatrix to obtain the basic weights of each evaluation index.

8. The radar jamming effect evaluation method combining imaging quality and application performance according to claim 7, characterized in that, S5 includes: S51: Construct dynamic correction factors based on the normalized degradation degree of each evaluation indicator; in, and These are the normalized degradation degree and dynamic correction factor of the i-th evaluation index, respectively. , To adaptively adjust parameters, The function used to construct the dynamic correction factor. Satisfy The requirement of monotony without reduction; S52: Adjust the basic weights according to the dynamic correction factor to obtain the adaptive weights of each evaluation index; in, and These are the basic weight and adaptive weight of the i-th evaluation indicator, respectively.

9. The radar jamming effect evaluation method combining imaging quality and application performance according to claim 8, characterized in that, S6 includes: S61: Calculate the contribution of each evaluation indicator based on the adaptive weight and normalized degradation degree of each evaluation indicator; in, The contribution term for the i-th evaluation indicator; S62: Sum the contribution items of all evaluation indicators to obtain a comprehensive score representing the interference effect; in, This is a comprehensive score.

10. A radar jamming effect evaluation device combining imaging quality and application performance, characterized in that, The device includes: The complex SAR data acquisition module is used to acquire the reference complex SAR interferometric pairs and the disturbed complex SAR interferometric pairs to be evaluated in the same area, and to determine the point target area, the distributed target area and the interferometric performance evaluation area. The index value extraction module is used to extract the baseline index value and the disturbed index value of multiple evaluation indicators based on the baseline complex SAR interferometric pair and the disturbed complex SAR interferometric pair. The evaluation indicators include point target quality indicators, distributed target quality indicators, and InSAR application performance indicators, which are extracted from the point target region, distributed target region, and interferometric performance evaluation region, respectively. The point target quality indicators include azimuth integral sidelobe ratio and range integral sidelobe ratio; the distributed target quality indicators include contrast and image entropy; and the InSAR application performance indicators include average coherence coefficient and interferometric fringe sharpness. The degradation degree calculation module is used to calculate the positive degradation amount of each evaluation indicator based on the benchmark index value and the disturbed index value of each evaluation indicator and normalize it to obtain the normalized degradation degree of each evaluation indicator. The larger the value of the positive degradation of the evaluation index, the more severe the disturbance damage. The basic weight determination module divides the various evaluation indicators into point target quality indicator set, distributed target quality indicator set and InSAR application performance indicator set according to their types, and constructs an F-ANP network model to obtain the basic weights of each evaluation indicator. The dynamic weight correction module is used to construct a dynamic correction factor based on the normalized degradation degree of each evaluation indicator, and correct the basic weight to obtain the adaptive weight of each evaluation indicator. The comprehensive scoring module is used to calculate the contribution of each evaluation indicator based on the adaptive weights and normalized degradation degree of each evaluation indicator, and to sum the contribution of all evaluation indicators to obtain a comprehensive score representing the interference effect.

Images