Improvement of large angle criterion in ISAL imaging and joint modeling method of multi-dimensional index

Abstract

This invention provides an improved method for determining large turning angles in ISAL imaging and a multi-dimensional index joint modeling method, relating to the field of radar imaging signal processing technology. First, this invention constructs azimuth and range scattering center trajectory factors to achieve collaborative quantization of two-dimensional imaging blur levels. Second, by fusing the two-dimensional trajectory factors, a two-dimensional joint total blur factor is obtained, which, combined with a fixed dimensionless threshold, completes the division and level determination of three-level turning angle intervals. Third, based on the differentiated imaging modeling compensation scheme corresponding to the turning angle level matching, the compensation strategy is accurately adapted to the distortion level, significantly improving the targeting of the correction operation. Finally, through multi-condition dimensionless normalization fitting, a global determination boundary constraint relationship is derived. By leveraging the inverse proportionality between size and turning angle factors, the limitations of traditional fixed determination thresholds are overcome, providing a universal capability to adapt to different target sizes and system resolutions, significantly optimizing the ISAL imaging modeling accuracy and final imaging quality under complex attitude conditions.

Description

Technical Field

[0001] This invention relates to the field of radar imaging signal processing technology, specifically to an improved method for determining large turning angles in ISAL imaging and a method for joint modeling of multi-dimensional indicators. Background Technology

[0002] Inverse Synthetic Aperture Laser (ISAL) utilizes the short wavelength characteristics of laser light to acquire centimeter-level fine imaging results of targets, making it a core detection equipment for long-range target identification in aviation and aerospace applications. ISAL constructs a synthetic aperture based on the target's three-dimensional composite attitude motion relative to the radar, including azimuth rotation, pitch, and roll. The scattering center of the target surface shifts along the radar's line of sight. When the target's attitude angle is large, this shift exhibits significant nonlinear characteristics. If a linear imaging model adapted for small angles is used, problems such as defocusing, contour distortion, and loss of detail will occur. Therefore, accurately classifying the target's angle level and matching corresponding compensation modeling strategies at the imaging front end is a crucial preliminary step to ensure the clarity of images of targets with complex attitudes.

[0003] In related technologies, the currently common ISAL large-angle determination method relies solely on the absolute angle of the target in a single azimuth, simply classifying the conditions into small and large angles. Some improved solutions introduce a normalized angle factor to mitigate the limitations of absolute angles from a single angular dimension. The existing determination process only collects the azimuth-viewpoint change as the sole input, failing to quantify the range-direction scattering center drift caused by pitch and roll motions. The determination threshold remains fixed and cannot be adaptively adjusted according to target size and radar system resolution. Furthermore, the angle classification only sets two levels, lacking distinction between intermediate angle transition conditions. After determination, manual matching of the imaging compensation algorithm is still required, lacking standardized and universal determination boundaries, and is mostly used in idealized simulation scenarios with stable attitudes and uniform target sizes.

[0004] In other words, the existing corner determination scheme has the following fundamental defects: First, the determination only covers a single orientation dimension, ignoring the nonlinear drift of the distance scattering center under three-dimensional attitude coupling, and cannot fully characterize the degree of image blur. Second, the determination rules do not have the ability to be uniformly adapted, and the fixed corner threshold cannot be adapted to ISAL systems with different target sizes and different hardware parameters, which is prone to misjudgment or overcompensation. Third, only a binary corner classification interval is set, which cannot match differentiated modeling compensation methods according to the severity of blur, and it is difficult to simultaneously take into account the image clarity and the real-time computing efficiency of the system. Summary of the Invention

[0005] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides an improved method for determining large turning angles in ISAL imaging and a multi-dimensional index joint modeling method. It also solves the technical problems of existing turning angle determination methods, such as single dimension, lack of normalization and adaptation capability, and coarse turning angle classification that cannot match differentiated modeling compensation.

[0006] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides an improved method for determining large turning angles in ISAL imaging and a method for joint modeling of multi-dimensional indicators, including: The azimuth scattering center trajectory factor is constructed based on the target's maximum structural size at azimuth, azimuth attitude angle, and system azimuth resolution, and the range scattering center trajectory factor is constructed based on the target's maximum structural size at range, pitch attitude angle, and system range resolution. The two types of scattering center trajectory factors are used to quantify the imaging blur in the azimuth and range directions, respectively. By fusing the two types of scattering center trajectory factors, a two-dimensional joint total fuzzy factor is obtained; The two-dimensional joint total fuzzy factor is compared with the preset two-level fuzzy threshold to determine the small, medium, and large three-level turning angle judgment interval to which it belongs, and the corresponding target turning angle level is output. Based on the pre-defined correspondence between the rotation level and the set of imaging modeling compensation methods, an imaging modeling compensation scheme that is compatible with the target rotation level is matched. Multiple sets of different working conditions are selected. The system azimuth resolution and system distance resolution under each set of working conditions are combined. The maximum structural size of the target's azimuth and distance, as well as the azimuth and pitch attitude angles under the same set of working conditions, are normalized in dimensionless manner to obtain normalized size factors and normalized angle factors. The two-level fuzzy thresholds are used as constraints for fitting to obtain a universal angle determination boundary constraint relationship in which the two types of normalized factors are inversely proportional. Substitute the normalized size factor and normalized rotation factor of the new target into the rotation determination boundary constraint relationship to determine the rotation level of the new target and its corresponding imaging modeling compensation scheme.

[0007] Secondly, the present invention provides an improved device for determining large turning angles in ISAL imaging and a multi-dimensional index joint modeling device, comprising: The dual-dimensional trajectory factor construction module is used to construct the azimuth scattering center trajectory factor based on the target's maximum structural size at azimuth, azimuth attitude angle and system azimuth resolution, and to construct the range scattering center trajectory factor based on the target's maximum structural size at range, pitch attitude angle and system range resolution. The two types of scattering center trajectory factors are used to quantify the imaging blur in the azimuth and range directions, respectively. The fuzzy factor fusion processing module is used to fuse the two types of scattering center trajectory factors to obtain a two-dimensional joint total fuzzy factor; The corner level determination module is used to compare the two-dimensional joint total fuzzy factor with the preset two-level fuzzy threshold, determine the small, medium and large three-level corner determination interval to which it belongs, and output the corresponding target corner level. The compensation scheme matching module is used to match an imaging modeling compensation scheme that is compatible with the target rotation angle level based on the preset correspondence between the rotation angle level and the set of imaging modeling compensation methods. The general boundary fitting modeling module is used to select multiple different working conditions, combine the system azimuth resolution and system distance resolution under each working condition, and perform dimensionless normalization on the target's azimuth, distance, maximum structural size, azimuth, pitch attitude and rotation angle under the same working condition to obtain normalized size factor and normalized rotation angle factor. Then, the module uses the two-level fuzzy threshold as constraints to fit and obtain the global general rotation angle determination boundary constraint relationship in which the two types of normalized factors are inversely proportional. The new target adaptive determination module is used to substitute the normalized size factor and normalized rotation factor of the new target into the rotation determination boundary constraint relationship to determine the rotation level of the new target and its corresponding imaging modeling compensation scheme.

[0008] As a further improvement to the large-angle criterion and multi-dimensional index joint modeling method or device in the above-mentioned ISAL imaging, the azimuth scattering center trajectory factor and the range scattering center trajectory factor are both constructed by dimensionless ratio calculation, and are used to quantify the proportion of the target scattering center trajectory offset relative to the system azimuth resolution in the azimuth dimension and the proportion of the target scattering center trajectory offset relative to the system range resolution in the range dimension, respectively.

[0009] As a further improvement to the large-angle criterion and multi-dimensional index joint modeling method or device in the above-mentioned ISAL imaging, the fusion of the two types of scattering center trajectory factors adopts L2 norm operation, specifically: the azimuth scattering center trajectory factor and the range scattering center trajectory factor are squared and summed, and then the square root is taken to obtain the two-dimensional joint total ambiguity factor.

[0010] As a further improvement to the aforementioned ISAL imaging large-angle criterion and multi-dimensional index joint modeling method or device, the preset two-level fuzzy thresholds are 0.35 and 0.707, respectively; the small, medium, and large-angle determination intervals include: For small turning intervals, the corresponding two-dimensional joint total fuzzy factor is less than 0.35; In the intermediate turning angle interval, the corresponding two-dimensional joint total fuzzy factor is greater than or equal to 0.35 and less than 0.707; And for the large turning angle interval, the corresponding two-dimensional joint total fuzzy factor is greater than or equal to 0.707.

[0011] As a further improvement to the large-angle criterion in the aforementioned ISAL imaging and the multi-dimensional index joint modeling method or device, the correspondence between the preset angle level and the set of imaging modeling compensation methods includes: A set of weak blur correction imaging modeling compensation methods is configured for small turning angle levels, including at least principal component analysis and fast Fourier transform; A set of adaptive iterative correction imaging modeling compensation methods is configured for intermediate rotation angle levels, including at least phase gradient autofocus and moving target detection; And a set of global reconstruction imaging modeling compensation methods for large-angle distortion at large-angle levels, including at least back projection and imaging-calibration synchronous modeling.

[0012] As a further improvement to the large-angle criterion and multi-dimensional index joint modeling method or device in the above-mentioned ISAL imaging, the imaging-calibration synchronous modeling method includes at least one of the following: an image-optimal imaging and calibration modeling method, an imaging and calibration joint modeling method based on the phase of a prominent point, and an imaging and calibration synchronous modeling method based on sparse representation.

[0013] As a further improvement to the above-mentioned method or device for joint modeling of large turning angle criteria and multi-dimensional indexes in ISAL imaging, the improved method for joint modeling of large turning angle criteria and multi-dimensional indexes in ISAL imaging is applicable to laser band ISAL imaging systems with a laser wavelength of 1.55 μm, and the system's azimuth resolution and distance resolution are both fixed at 0.03 m.

[0014] Thirdly, the present invention provides a storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the improved method for large-angle criterion and multi-dimensional index joint modeling in ISAL imaging as described in the first aspect.

[0015] Fourthly, the present invention provides an electronic device, the electronic device comprising: The processor, the memory, and the program instructions stored in the memory and executable by the processor, wherein when the processor executes the program instructions, it implements the improved method for large-angle criterion and multi-dimensional index joint modeling in ISAL imaging as described in the first aspect.

[0016] (III) Beneficial Effects This invention provides an improved method for determining large turning angles in ISAL imaging and a joint modeling method for multi-dimensional indices. Compared with existing technologies, it has the following advantages: This invention first constructs azimuth and range scattering center trajectory factors to achieve collaborative quantification of dual-dimensional imaging blur levels, comprehensively covering the imaging distortion features caused by target attitude rotation, effectively improving the comprehensiveness and accuracy of blur state assessment. Secondly, by fusing the dual-dimensional trajectory factors, a two-dimensional joint total blur factor is obtained, which, combined with a fixed dimensionless threshold, completes the division and level determination of three-level rotation intervals, achieving standardized and hierarchical identification of imaging distortion levels. Thirdly, based on the differentiated imaging modeling compensation scheme corresponding to the rotation level, the compensation strategy is precisely adapted to the distortion level, significantly improving the targeting of correction operations. Finally, through multi-condition dimensionless normalization fitting, a global judgment boundary constraint relationship is derived. By leveraging the inverse proportionality between size and rotation factor, the limitations of traditional fixed judgment thresholds are overcome, providing a universal capability to adapt to different target sizes and system resolutions, significantly optimizing ISAL imaging modeling accuracy and final imaging quality under complex attitude conditions. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 The flowchart of the matching of the rotation level determination and imaging modeling compensation scheme under a single working condition is provided for an improved method of large rotation criterion and multi-dimensional index joint modeling method in ISAL imaging, which is an embodiment of the present invention. Figure 2 A block diagram illustrating an improved method for determining large turning angles in ISAL imaging and a multi-dimensional index joint modeling method provided in this embodiment of the invention. Figure 3 A scale-angle normalized two-dimensional joint total fuzzy factor distribution cloud map is provided for an embodiment of the present invention; Figure 4 A two-dimensional joint total fuzzy factor contour map of a 2.5m×2.5m target provided in an embodiment of the present invention; Figure 5 A three-dimensional display diagram of the two-dimensional joint total fuzziness factor of a 2.5m×2.5m target provided for an embodiment of the present invention; Figure 6 A normalized turning angle factor for a 2.5m × 2.5m target provided in an embodiment of the present invention. The curve of relative angle change; Figure 7 A two-dimensional joint total fuzzy factor contour map of a 25m×25m target is provided for an embodiment of the present invention; Figure 8 A three-dimensional display diagram of the two-dimensional joint total fuzziness factor of a 25m×25m target is provided in an embodiment of the present invention; Figure 9 A normalized turning angle factor for a 25m×25m target provided in an embodiment of the present invention. The curve of relative angle change; Figure 10 A contour map of the two-dimensional joint total fuzzy factor for different target sizes when the two-dimensional rotation angle is 0.02°, provided as an embodiment of the present invention; Figure 11 A three-dimensional display diagram of the joint total fuzziness factor of two-dimensional targets with different sizes when the two-dimensional rotation angle is 0.02° is provided for an embodiment of the present invention; Figure 12 A contour map of the two-dimensional joint total fuzzy factor for different target sizes when the two-dimensional rotation angle is 0.04°, provided for an embodiment of the present invention; Figure 13 A three-dimensional display diagram of the joint total fuzziness factor of two-dimensional targets with different sizes when the two-dimensional rotation angle is 0.04° is provided for an embodiment of the present invention; Figure 14 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0019] Component labeling explanation: 100 - electronic device, 101 - memory, 102 - processor, 103 - display. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described clearly and completely. Obviously, the described embodiments are only some embodiments of the present invention, 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] To address the technical problems of traditional ISAL imaging, such as single-dimensional corner determination, coarse-grained classification, poor adaptability to working conditions, and difficulty in matching differentiated modeling compensation, this invention proposes an improved method for large corner determination in ISAL imaging and a multi-dimensional index joint modeling method.

[0022] The overall technical process of this embodiment revolves around a complete chain of multi-dimensional fuzzy quantization, factor fusion and classification, hierarchical compensation matching, global boundary fitting, and adaptive adaptation. Each technical step is interconnected and mutually adapted. For example... Figure 1 As shown, the overall execution flow of this method is as follows: First, input the ISAL system parameters (including system azimuth resolution, system range resolution, etc.) and target prior information (including target maximum structural size at azimuth, target maximum structural size at range, azimuth attitude angle, pitch attitude angle, etc.).

[0023] Next, the azimuth scattering center trajectory factor and the range scattering center trajectory factor are calculated, and a two-dimensional joint total fuzzy factor is constructed based on these factors. .

[0024] Subsequently, based on the two-dimensional joint total fuzzy factor Two-level fuzzy threshold determination is carried out, and the values ​​are respectively classified into small angle, medium angle or large angle interval.

[0025] Finally, the judgment result is output, and the corresponding imaging modeling compensation scheme is matched according to the rotation level.

[0026] The above process completes the determination of the rotation angle level and compensation scheme under a single set of working conditions. On this basis, dimensionless normalization and fitting processing are then carried out through multiple sets of different working conditions. Figure 1 (not shown in the figure), thus obtaining the universal rotation angle determination boundary constraint relationship, and realizing adaptive determination under new target working conditions.

[0027] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0028] like Figure 2 As shown, an improved method for determining large turning angles in ISAL imaging and a joint modeling method for multi-dimensional indices include: S1. Construct azimuth scattering center trajectory factors based on the target's maximum structural size at azimuth, azimuth attitude angle and system azimuth resolution, and construct range scattering center trajectory factors based on the target's maximum structural size at range, pitch attitude angle and system range resolution. The two types of scattering center trajectory factors are used to quantify the imaging blur in the azimuth and range directions, respectively. S2. Merge the two types of scattering center trajectory factors to obtain the two-dimensional joint total fuzzy factor; S3. Compare the two-dimensional joint total fuzzy factor with the preset two-level fuzzy threshold to determine the small, medium, and large three-level turning angle judgment interval to which it belongs, and output the corresponding target turning angle level. S4. Based on the preset correspondence between the rotation level and the set of imaging modeling compensation methods, match an imaging modeling compensation scheme that is compatible with the target rotation level. S5. Select multiple sets of different working conditions, and combine the system azimuth resolution and system distance resolution under each set of working conditions. Perform dimensionless normalization on the target's azimuth, distance, maximum structural size, azimuth, pitch attitude, and rotation angle under the same set of working conditions to obtain normalized size factor and normalized rotation angle factor. Then, use the two-level fuzzy threshold as constraints to fit and obtain a universal rotation angle determination boundary constraint relationship in which the two types of normalized factors are inversely proportional. S6. Substitute the normalized size factor and normalized rotation factor of the new target into the rotation determination boundary constraint relationship to determine the rotation level of the new target and its corresponding imaging modeling compensation scheme.

[0029] This embodiment improves the imaging quality and algorithm efficiency of the ISAL system for targets with complex poses, providing technical support for the engineering application of the ISAL imaging system.

[0030] Specifically, in step S1, firstly, based on the target's maximum structural size, azimuth attitude angle, and system azimuth resolution, an azimuth scattering center trajectory factor is constructed to quantify the degree of imaging blur in the azimuth direction.

[0031] Specifically, this step constructs the azimuth scattering center trajectory factor based on the target rotation characteristics in the ISAL imaging azimuth direction. This factor is constructed using dimensionless ratio calculation, directly representing the proportion of the target scattering center trajectory offset relative to the system's azimuth resolution in the azimuth dimension. It can accurately quantify the degree of imaging blur in the azimuth direction, providing a core physical indicator for determining large turning angles.

[0032] (1) in, The maximum structural dimension of the target in the azimuth direction (unit: m) represents the extent of the target's extension in the azimuth direction and can be measured based on the actual structural parameters of the target. The change in azimuth angle (i.e., azimuth attitude angle, unit: rad or deg) can be acquired in real time through the attitude measurement module of the ISAL system. The system's azimuth resolution (in meters) is determined by parameters such as the system's laser wavelength and synthetic aperture length. The azimuth migration caused by the angle (unit: m).

[0033] It should be noted that, The physical meaning is clearly defined as: it is used to characterize the multiple of the trajectory offset from the azimuth to a single scattering center relative to the system's azimuth resolution. The larger the value, the more significant the drift of the azimuth scattering center, and the more severe the azimuth imaging blur; conversely, the smaller the value, the more significant the drift. The smaller the value, the clearer the azimuth imaging. Furthermore, due to the use of dimensionless ratio calculations for construction, the azimuth scattering center trajectory factor... The number is dimensionless, which eliminates the influence of dimensions and facilitates subsequent threshold comparison.

[0034] In step S1, a range scattering center trajectory factor is then constructed based on the target distance maximum structural size, pitch attitude angle, and system range resolution to quantify the degree of range-oriented imaging blur.

[0035] Specifically, to address the range scattering center drift problem caused by three-dimensional attitude changes such as target pitch and roll, a range scattering center trajectory factor is constructed by extending the azimuth trajectory factor. , and the azimuth scattering center trajectory factor Similarly, this factor is also constructed using dimensionless ratio calculation, directly representing the proportion of the target scattering center trajectory offset relative to the system range resolution in the range dimension. It can accurately quantify the degree of imaging blur in the range direction and achieve a comprehensive expansion of the judgment dimensions.

[0036] (2) in, The maximum structural dimension (in meters) of the target in the range direction and the maximum structural dimension in the azimuth direction. Correspondingly, it represents the range of the target in the distance direction; The pitch angle change along the distance axis (i.e., pitch attitude angle, unit: rad or deg) reflects the change in the target's pitch attitude and can be collected in real time by the system's attitude measurement module. The system distance resolution (unit: m) is determined by parameters such as the system laser bandwidth; This represents the distance migration to the location caused by the turning angle (unit: m).

[0037] It should be noted that, The physical meaning is clearly defined as: it is used to characterize the ratio of the trajectory offset from a single scattering center to the system's range resolution. The larger the value, the more severe the blurring in the distance direction; The smaller the value, the clearer the range-oriented imaging, thus enabling precise quantification of the degree of range-oriented blur. Furthermore, the range-oriented scattering center trajectory factor... Similarly, since they are dimensionless, the influence of dimensions is eliminated, which facilitates subsequent threshold comparison.

[0038] In step S2, the two types of scattering center trajectory factors are fused to obtain the two-dimensional joint total fuzzy factor.

[0039] This step integrates the azimuth scattering center trajectory factor. Trajectory factor of the range scattering center Construct a two-dimensional joint total fuzzy factor Through a scientific synthesis method, the degree of nonlinear ambiguity in the two-dimensional directions of azimuth and range is comprehensively reflected, achieving an integrated representation of multi-dimensional influences. In some implementations, the fusion of the two types of scattering center trajectory factors can be performed using L2 norm operations. Specifically, the squares of the azimuth scattering center trajectory factor and the range scattering center trajectory factor are taken, summed, and then the square root is taken to obtain the joint total ambiguity factor. The calculation formula is as follows: (3) It is understandable that the two-dimensional joint total fuzzy factor can be obtained by solving the above formula. This is a synthesized value normalized to two-dimensional resolution, possessing both normalization and two-dimensional comprehensiveness: on the one hand, it eliminates the influence of parameters such as target size and system resolution, making it adaptable to different scenarios; on the other hand, it integrates ambiguity information from both orientation and distance dimensions, comprehensively characterizing the overall imaging blur caused by changes in the target's three-dimensional pose. The numerical value is positively correlated with the overall severity of fuzziness, providing a core basis for establishing subsequent classification criteria.

[0040] In step S3, the two-dimensional joint total fuzzy factor is compared with the preset two-level fuzzy threshold to determine the small, medium, and large three-level turning angle judgment interval to which it belongs, and the corresponding target turning angle level is output.

[0041] This embodiment draws upon the range migration criterion principle in the field of Synthetic Aperture Radar (SAR), and combines it with the technical characteristics of the ISAL laser band. Extensive simulation experiments and engineering verification were conducted beforehand to determine... The two-level fuzziness threshold divides the corners of ISAL imaging into three levels of judgment intervals: small, medium, and large. It clarifies the fuzziness characteristics and judgment criteria of each level, ensuring the scientific nature and practicality of the classification.

[0042] The SAR range migration criterion uses the proportion of the scattering center trajectory offset relative to the system resolution cell as the basis for judgment, which is a well-known technology in this field and will not be described in detail here.

[0043] Preferably, the preset two-level fuzzy thresholds are 0.35 and 0.707, respectively.

[0044] Accordingly, the three-level turning angle determination intervals of small, medium, and large specifically include: 1) In the small turning angle interval, the corresponding two-dimensional joint total fuzzy factor is less than 0.35.

[0045] At this point, the drift of the scattering center in the two-dimensional directions of azimuth and range is extremely small, and the degree of image blur is almost negligible. The distance migration caused by the rotation angle can be directly ignored, and no additional blur compensation is required. A clear image can be obtained by using the traditional small-angle imaging algorithm. For specific algorithm selection, please refer to the following introduction.

[0046] 2) In the intermediate turning angle interval, the corresponding two-dimensional joint total fuzzy factor is greater than or equal to 0.35 and less than 0.707.

[0047] At this point, there is slight blurring in the two-dimensional direction, and the distance migration caused by the corner is not negligible. Without targeted compensation, the image quality will slightly deteriorate. Therefore, a dedicated corner compensation algorithm is needed to balance image quality and computational efficiency. Specific algorithm selection will be discussed later. 3) For large turning intervals, the corresponding two-dimensional joint total fuzzy factor is greater than or equal to 0.707.

[0048] At this point, significant nonlinear blurring occurs in the two-dimensional direction, and the distance migration is large. The traditional small-angle imaging model is completely ineffective. If the traditional model is used, it will lead to severe image distortion and defocus. A special modeling algorithm for large-angle imaging must be used to ensure image quality. The specific algorithm selection will be introduced later.

[0049] Therefore, this step is based on the above-mentioned small, medium, and large three-level turning angle determination intervals, combined with the two-dimensional joint total fuzzy factor. The specific value can be determined directly. The corresponding target turning angle level enables precise classification of large turning angles.

[0050] In step S4, based on the preset correspondence between the rotation level and the set of imaging modeling compensation methods, an imaging modeling compensation scheme that is compatible with the target rotation level is matched.

[0051] Based on the above-mentioned grading criteria, this embodiment combines the fuzzy features of each corner level to match the optimal ISAL imaging modeling compensation scheme for each corner level, realizing the integrated matching of criteria and algorithm, which not only ensures imaging quality but also optimizes algorithm running efficiency.

[0052] In some implementations, the correspondence between the preset rotation level and the set of imaging modeling compensation methods includes: 1) When the angle is small, the imaging blur is almost negligible and the distance migration is very small. Configure a set of weak blur correction imaging modeling compensation methods, including at least Principal Component Analysis (PCA) and Fast Fourier Transform (FFT).

[0053] 2) When the image is at the mid-turn level, there is slight blurring and small distance migration. Configure an adaptive iterative correction imaging modeling compensation method set, including at least phase gradient autofocus (PGA) and moving target detection (MTD).

[0054] 3) When at large turning angles, significant nonlinear blurring occurs with large distance migration. A set of global reconstruction imaging modeling compensation methods for large-angle distortion should be configured, including at least back projection. Projection (BP) and imaging-calibration synchronous modeling.

[0055] The two-dimensional joint total fuzziness factor range, imaging fuzziness features, adaptive modeling compensation methods, and applicable algorithms corresponding to each rotation level in this embodiment can be found in Table 1.

[0056] Table 1. Correspondence between rotation level, imaging blur features, and adaptive modeling compensation methods. It is understood that PCA, FFT, PGA, MTD, BP, and the imaging-calibration synchronous modeling method are all mature imaging signal processing and modeling algorithms publicly available in the field. Among them, FFT is mainly used for frequency domain imaging processing; PCA is used for dimensionality reduction and feature extraction of signal components; PGA is a classic phase iterative autofocus algorithm used to compensate for phase errors; MTD is mostly used for filtering target signals and suppressing clutter; and BP is a commonly used time-domain imaging algorithm, adapted to range-azimuth two-dimensional echo coherence accumulation under large rotation angles. The imaging-calibration synchronous modeling method may include processing steps such as echo signal decoupling, imaging iterative solution, and synchronous calibration correction of system errors, enabling simultaneous calibration of system parameters during the imaging solution process, adapting to distortion compensation under large rotation angle conditions. For example, the imaging-calibration synchronous modeling method includes at least one of the following: an image-optimal imaging and calibration modeling method, an imaging and calibration joint modeling method based on the phase of a prominent point, and an imaging-calibration synchronous modeling method based on sparse representation.

[0057] It should be noted that the specific algorithms listed above are only examples of embodiments and are not intended to limit the present invention. The specific implementation process of the above algorithms belongs to the prior art and will not be elaborated further.

[0058] Therefore, based on the above correspondence, this step can match the optimal ISAL imaging modeling compensation method for blur features of different corner levels, so as to establish a one-to-one correspondence between "corner level - blur feature - adaptation algorithm", achieve accurate matching between algorithm and blur degree, and avoid over-compensation or under-compensation.

[0059] In step S5, multiple different working conditions are selected, and the two-level fuzzy thresholds are used as constraints. Combining the system azimuth resolution and system distance resolution under each working condition, the maximum structural size of the target azimuth, the maximum structural size of the target distance, the azimuth attitude angle and the pitch attitude angle under the same working condition are subjected to dimensionless normalization processing. The normalized size factor and the normalized angle factor are inversely proportional to each other, and the universal angle determination boundary constraint relationship of the whole domain is obtained by fitting.

[0060] Based on the factor calculation and angle classification criteria under a single working condition, i.e., the above steps S1-S5, in order to eliminate the limitations on the use of criteria caused by the difference in target size and system resolution, and to realize the universal judgment across working conditions, multiple groups of different working conditions are selected. In this embodiment, the two-level fuzzy threshold in step S4 is used as a constraint condition, and combined with the system azimuth resolution and system distance resolution corresponding to each group of different working conditions, dimensionless normalization processing is performed on the maximum structural size of the target azimuth, the maximum structural size of the target distance, the azimuth attitude angle and the pitch attitude angle under the same group of working conditions.

[0061] It should be noted that step S5 is a cross-condition inductive modeling based on the single-condition judgment rules established in steps S1 to S4, and does not involve redetermining or optimizing the two-level fuzzy thresholds. Specifically, for each selected condition, the azimuth scattering center trajectory factor and range scattering center trajectory factor are constructed as described in step S1, and the two-dimensional joint total fuzzy factor is obtained as described in step S2. The two-level fuzzy thresholds used in step S3 are used as the boundary conditions between small and medium turning angles, and between medium and large turning angles, respectively. The target structure size, attitude angle, and system resolution parameter combinations corresponding to the two-dimensional joint total fuzzy factor reaching the corresponding fuzzy threshold are determined. The parameter combinations are dimensionlessly normalized, and the normalized parameter combinations obtained under multiple different conditions are fitted to obtain the universal turning angle judgment boundary constraint relationship between the normalized size factor and the normalized turning angle factor.

[0062] The correspondence between the rotation level and the imaging modeling compensation scheme established in step S4 is not used as a fitting variable for the universal rotation determination boundary constraint relationship. In step S6, after determining the rotation level of the new target based on the position of the normalized size factor and normalized rotation factor of the new target relative to the universal rotation determination boundary constraint relationship, the correspondence established in step S4 is called to match and obtain an imaging modeling compensation scheme that is suitable for the rotation level.

[0063] By fitting normalized parameters under multiple operating conditions, a universally applicable rotation angle determination boundary constraint relationship with an inverse relationship between the normalized size factor and the normalized rotation angle factor is obtained. By performing dimensionless normalization on the target size and attitude rotation angle, the influence of different target sizes and system resolutions is eliminated, establishing a determination boundary under the normalized dimension. This provides a unified rule for the rapid invocation of criteria in various ISAL scenarios, improving the engineering applicability of this solution. The specific process is as follows: Define the normalized size factor: , (4) in, These are the normalized maximum structural dimensions of the target's azimuth and the maximum structural dimensions of the target's distance, respectively.

[0064] Define the normalized rotation factor: , (5) in, These are the normalized azimuth and pitch attitude angles, respectively. The wavelength of the laser; This indicates the desired azimuth resolution. Minimum required azimuth angle.

[0065] It should be noted that this embodiment utilizes the minimum azimuth angle. Dimensionless normalization was performed on both the azimuth and pitch attitude angles. The range-dimensional attitude angle was also normalized with reference to the minimum line-of-sight angle in the azimuth direction, ensuring a unified comparison benchmark for the two types of angle factors. It should be understood that this embodiment's choice to uniformly normalize the pitch attitude angle with reference to the minimum line-of-sight angle in the azimuth direction does not imply that the range resolution does not have a corresponding theoretical minimum angle. Rather, it ensures that the azimuth-range dual-dimensional angle factors have completely consistent dimensional benchmarks, allowing both types of factors to directly participate in subsequent fusion calculations.

[0066] Therefore, the two-dimensional joint total fuzzy factor is calculated. : (6) Under the exemplary specific conditions of two-dimensional size-resolution matching, equal system azimuth and range resolution, and equal azimuth-range normalized rotation angles (this condition is only used to facilitate the derivation of the analytical expression and is not a limiting condition for the implementation of this invention), namely... , , and order Then the two-dimensional joint total fuzzy factor The corresponding analysis can be simplified: (7) Because the rotation angle is generally very small under laser ISAL imaging conditions, it is necessary to satisfy the small angle requirement. Approximate relationship ,right Further simplification yields: (8) (9) In the formula, The threshold values ​​for the two-dimensional joint total fuzzy factor classification correspond to the boundary criteria for small-to-medium turning angles and medium-to-large turning angles, respectively. From this formula, the normalized size factor can be determined. With normalized turn factor They exhibit an inverse proportional constraint relationship.

[0067] To clarify again, the above refers to the analytical boundary under the matching condition; for general mismatched conditions, the numerical form of the universal rotation angle determination boundary constraint is obtained by fitting multiple sets of different conditions. That is, the universal rotation angle determination boundary obtained by this fitting includes both the analytical solution under the aforementioned matching condition and the numerical boundary obtained through multi-condition simulation under general conditions.

[0068] Finally, based on the predetermined two-dimensional joint total fuzzy factor... By using two threshold levels, the global boundary constraint relationship under normalized parameters is derived, and the judgment boundary in which the normalized size factor and the normalized rotation factor are inversely proportional is obtained, as follows: Small corner boundary: ; Mid-angle boundary: ; Large corner boundary: .

[0069] It should be noted that the core advantage of this universal boundary constraint relationship is that, for any laser frequency band, any resolution ISAL system, and any size target, no complex calculations are required; only the normalized size factor needs to be calculated. and normalized turn factor By understanding the relationship between these factors, the corner level can be quickly determined, and the corresponding modeling compensation method can be matched, greatly improving the engineering practicality and adaptability of the criteria.

[0070] After multi-condition normalization fitting, an inverse proportional constraint relationship between the normalized size factor and the normalized rotation angle factor was obtained. The visualization cloud map of the global decision boundary is shown below. Figure 3 As shown; Figure 3 normalized size factor For the horizontal axis, normalized rotation factor With the vertical axis as the dividing line, the white dashed lines in the figure represent the boundaries between small and medium turning angles and medium and large turning angles, which intuitively reflect the inverse proportional constraint between the normalized size factor and the normalized turning angle factor.

[0071] In step S6, the normalized size factor and normalized rotation factor of the new target are substituted into the global universal rotation determination boundary constraint relationship to determine the rotation level of the new target and its corresponding imaging modeling compensation scheme.

[0072] After obtaining the universal rotation determination boundary constraints under normalized dimensions, this step, for a new target to be processed, obtains the corresponding normalized size factor and normalized rotation factor. Substituting these two factors into the already fitted universal rotation determination boundary constraints, the rotation level of the new target can be quickly determined. Based on a preset correspondence, a suitable imaging modeling compensation scheme is then obtained. This method eliminates the need for repeated large-scale simulation iterations for each new target; it can quickly determine the rotation level of targets of different sizes under different azimuth angles using only the pre-fitted boundary constraints. It is intuitive, convenient, and effectively reduces computational overhead in engineering applications.

[0073] The following section uses typical ISAL simulation scenarios and two sets of simulation implementation cases of typical targets to verify the application process and implementation effect of the boundary constraint relationship for the global universal corner determination of this invention.

[0074] Using laser frequency band, ISAL system azimuth / range resolution of 0.03m, and laser wavelength of 1.55μm as typical application scenarios, simulation verification was carried out on small targets of 2.5m×2.5m and large targets of 25m×25m respectively. The corresponding azimuth and elevation physical rotation angle thresholds are given to verify the effectiveness and feasibility of the boundary constraint relationship of the universal rotation angle determination of the present invention.

[0075] Case 1: Small target (2.5m × 2.5m) ) This type of target mainly includes small drones and small ground equipment. Due to their small structural size, the impact of cornering on imaging is relatively mild. The specific cornering threshold and adaptation method are as follows: Small turning angle threshold: both azimuth and pitch angles are ≤0.25°. At this time, the calculated two-dimensional joint total blur factor (hereinafter referred to as the total blur factor in this case) satisfies the small turning angle interval condition, and the imaging blur can be ignored. By using small turning angle basic imaging models such as principal component analysis (PCA) or fast Fourier transform (FFT), a clear image can be obtained. Mid-turn angle threshold: When the azimuth / pitch angle is between 0.25° and 0.5°, the total blur factor falls into the mid-turn angle range, and there is slight blur. Mid-turn angle compensation algorithms such as phase gradient autofocus (PGA) or moving target detection (MTD) can effectively suppress blur. Large turning angle threshold: Both azimuth and pitch angles are >0.5°. At this point, the total blur factor falls into the large turning angle range, resulting in significant blurring. Special methods for large turning angles, such as back projection (BP) or imaging-calibration synchronous modeling, are used to ensure imaging quality.

[0076] See the contour line for the total fuzzy factor corresponding to Case 1. Figure 4 The corresponding three-dimensional visualization results of the total fuzzy factor can be found in [link to documentation]. Figure 5 : Figure 4 Using azimuth and pitch angles as the horizontal and vertical axes respectively, the contour line colors represent the magnitude of the total ambiguity factor. The white dashed lines marked in the figure correspond to the two threshold levels of the total ambiguity factor, 0.35 and 0.707, respectively, which can intuitively distinguish the parameter ranges corresponding to small, medium and large angles. Figure 5 The view is rendered in three dimensions, with azimuth and pitch angles as the two independent coordinate axes. The vertical axis represents the magnitude of the total blur factor, which intuitively shows the variation of the degree of image blur under the combined effect of two-dimensional attitude angles. Figure 4 , Figure 5 The effect of the 2D azimuth-pitch angle change on the total ambiguity factor of a small target is visually demonstrated, and the threshold boundaries corresponding to small, medium and large angles are marked.

[0077] The trend of the normalized rotation factor with azimuth rotation for this small-sized target is as follows: Figure 6 As shown; Figure 6 The horizontal axis represents the physical azimuth angle, and the vertical axis represents the normalized azimuth factor. The curve reflects the relationship between the normalized turning angle factor and the actual azimuth turning angle of the target. It can be used to compare the difference in the judgment effect between the normalized turning angle factor and the total fuzzy factor, demonstrating the advantages of the criterion of this invention.

[0078] Case 2: Large target (25m×25m) ) This type of target mainly includes large aircraft, ships, and large buildings. Due to their large structural dimensions, the scattering center drift is greater at the same rotation angle. The specific rotation angle threshold and adaptation method are as follows: Small turning angle threshold: both azimuth and pitch angles are less than or equal to 0.03°. At this time, the calculated two-dimensional joint total blur factor (hereinafter referred to as the total blur factor in this case) satisfies the small turning angle interval condition, and the imaging blur can be ignored. PCA / FFT modeling can be used. Mid-turn angle threshold: When the azimuth / pitch angle is between 0.03° and 0.05°, the total ambiguity factor falls into the mid-turn angle range, and there is slight ambiguity. The PGA / MTD compensation algorithm is used. Large turning angle threshold: Both azimuth and pitch angles are greater than 0.05°. At this point, the total blur factor falls into the large turning angle range, resulting in significant nonlinear blur. The BP / imaging-calibration synchronous modeling method is adopted to ensure that the target details are clearly distinguishable.

[0079] See the contour line for the total fuzzy factor in Case 2. Figure 7 For the three-dimensional visualization results of the total fuzzy factor, please refer to [link / reference]. Figure 8 : Figure 7 , Figure 8 The drawing logic is the same as the aforementioned Figure 4 , Figure 5 Maintaining complete consistency, it only adapts to simulation conditions of large-size targets; due to the enlarged target size, the rotation angle corresponding to the same ambiguity level becomes significantly smaller. (Comparison) Figure 4 and Figure 7 It is evident that, under the same turning angle conditions, larger targets are more likely to enter the ambiguity range of medium and large turning angles.

[0080] The trend of the normalized rotation factor with azimuth rotation for this large-size target is as follows: Figure 9 As shown; Figure 9 Coordinate axis definition and Figure 6 Maintain consistency, Figure 6 and Figure 9 By making a horizontal comparison, we can intuitively observe the difference in the change of the normalized rotation factor with the physical rotation angle under small and large targets, and further verify the adaptability of the criterion of this invention to targets of different sizes.

[0081] As can be seen from the two sets of cases above, under the same ISAL system, the physical corner thresholds for different target sizes are significantly different; however, the universal corner determination boundary constraint obtained by the normalization process of this invention can achieve unified discrimination under the normalized parameter dimension, avoiding the adaptation limitations brought about by directly using fixed physical corner thresholds.

[0082] To further demonstrate the impact of target size on image blur, this embodiment also simulates the distribution of total blur factor under various target sizes. The simulation results are as follows: Figures 10-13 As shown. Among them, Figure 10 , Figure 11 The simulation results were obtained under the condition that the two-dimensional rotation angle was fixed at 0.02°. Figure 10 Contour lines representing the total fuzziness factor for different target sizes. Figure 11 This is the corresponding 3D rendered view; Figure 12 , Figure 13The simulation results are for a larger two-dimensional rotation angle with a fixed rotation angle of 0.04°. The two sets of simulations can be compared horizontally to intuitively show that, while keeping the attitude rotation angle constant, as the target structure size increases, the total blur factor increases and the degree of image blur intensifies.

[0083] Based on the same inventive concept, embodiments of the present invention also provide an improved device for determining large turning angles in ISAL imaging and a joint modeling device for multi-dimensional indicators, comprising: The dual-dimensional trajectory factor construction module is used to construct the azimuth scattering center trajectory factor based on the target's maximum structural size at azimuth, azimuth attitude angle and system azimuth resolution, and to construct the range scattering center trajectory factor based on the target's maximum structural size at range, pitch attitude angle and system range resolution. The two types of scattering center trajectory factors are used to quantify the imaging blur in the azimuth and range directions, respectively. The fuzzy factor fusion processing module is used to fuse the two types of scattering center trajectory factors to obtain a two-dimensional joint total fuzzy factor; The corner level determination module is used to compare the two-dimensional joint total fuzzy factor with the preset two-level fuzzy threshold, determine the small, medium and large three-level corner determination interval to which it belongs, and output the corresponding target corner level. The compensation scheme matching module is used to match an imaging modeling compensation scheme that is compatible with the target rotation angle level based on the preset correspondence between the rotation angle level and the set of imaging modeling compensation methods. The general boundary fitting modeling module is used to select multiple different working conditions, combine the system azimuth resolution and system distance resolution under each working condition, and perform dimensionless normalization on the target's azimuth, distance, maximum structural size, azimuth, pitch attitude and rotation angle under the same working condition to obtain normalized size factor and normalized rotation angle factor. Then, the module uses the two-level fuzzy threshold as constraints to fit and obtain the global general rotation angle determination boundary constraint relationship in which the two types of normalized factors are inversely proportional. The new target adaptive determination module is used to substitute the normalized size factor and normalized rotation factor of the new target into the rotation determination boundary constraint relationship to determine the rotation level of the new target and its corresponding imaging modeling compensation scheme.

[0084] Each module in the above-mentioned device can be implemented by a processor executing program instructions stored in memory, or by software components, hardware circuits, or a combination of both. The module name is only used to distinguish its main function and does not require that each module correspond to a separate physical device; a processing unit can implement the functions of multiple modules, and the same module can also be distributed on multiple controlled computing nodes.

[0085] Based on the same inventive concept, embodiments of the present invention also provide a storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the improved method for large-angle criterion and multi-dimensional index joint modeling in ISAL imaging as provided in any embodiment of the present invention.

[0086] In embodiments of the present invention, any combination of one or more storage media may be used. The storage medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, RAM, ROM, erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in connection with an instruction execution system, apparatus, or device.

[0087] Based on the same inventive concept, embodiments of the present invention also provide an electronic device. Figure 14 The diagram shown is a structural schematic of the electronic device 100 provided in an embodiment of the present invention. In some embodiments, the electronic device may be a mobile phone, tablet computer, wearable device, in-vehicle device, augmented reality (AR) / virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), or other terminal device. Furthermore, the improved method for determining large angles in ISAL imaging and the joint modeling method for multi-dimensional indicators provided in this embodiment of the present invention can also be applied to databases, servers, and service response systems based on terminal artificial intelligence. This embodiment of the present invention does not limit the specific application scenarios of the improved method for determining large angles in ISAL imaging and the joint modeling method for multi-dimensional indicators.

[0088] like Figure 14 As shown, the electronic device 100 provided in this embodiment of the invention includes a memory 101 and a processor 102.

[0089] The memory 101 is used to store computer programs; preferably, the memory 101 includes various media that can store program code, such as ROM, RAM, magnetic disk, USB flash drive, memory card or optical disk.

[0090] Specifically, memory 101 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory. Electronic device 100 may further include other removable / non-removable, volatile / non-volatile computer system storage media. Memory 101 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0091] The processor 102 is connected to the memory 101 and is used to execute the computer program stored in the memory 101 to implement the improved large-angle criterion and multi-dimensional index joint modeling method for ISAL imaging provided in any embodiment of the present invention.

[0092] In an optional implementation, the processor 102 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates, transistor logic devices, and discrete hardware components.

[0093] In an optional embodiment, the electronic device 100 of this invention may further include a display 103. The display 103 is communicatively connected to the memory 101 and the processor 102, and is used to display the relevant GUI interactive interface of the improved large-angle criterion and multi-dimensional index joint modeling method in ISAL imaging.

[0094] It is understood that the improved large-angle criterion and multi-dimensional index joint modeling device, storage medium and electronic device in ISAL imaging provided in the embodiments of the present invention correspond to the improved large-angle criterion and multi-dimensional index joint modeling method in ISAL imaging provided in the embodiments of the present invention. The explanation, examples and beneficial effects of the relevant contents can be referred to the corresponding parts of the method, and will not be repeated here.

[0095] In summary, compared with existing technologies, this invention has significant advantages in terms of criterion accuracy, imaging quality, algorithm computation efficiency, and engineering applicability, as detailed below: 1. The accuracy of the judgment criteria has been significantly improved. This invention introduces a trajectory factor with clear physical meaning and constructs a two-dimensional joint total fuzzy factor, overcoming the shortcomings of traditional corner criterion with its single dimension and lack of normalization, and significantly improving the accuracy and adaptability of large corner level determination; it can be adapted to ISAL imaging scenarios with different sizes, different three-dimensional attitudes, and different system parameters.

[0096] 2. Imaging quality is effectively improved. This invention utilizes the results of small, medium, and large turning angle classification to match corresponding imaging modeling and compensation strategies, which can specifically suppress nonlinear imaging blur of different degrees, improve image distortion and defocusing under large turning angle conditions, and enhance the imaging clarity and detail recognition capability of the ISAL system for complex pose targets.

[0097] 3. The algorithm's computational efficiency has been optimized. This invention achieves integrated matching of corner criterion and compensation algorithm, avoiding the problems of overcompensation in small corner scenes and undercompensation in large corner scenes; it achieves accurate algorithm selection based on two-dimensional joint total fuzz factor, reduces redundant iterative simulation calculations, lowers computational overhead, and meets the application requirements of real-time imaging in ISAL engineering.

[0098] 4. Highly practical engineering applications This invention obtains the boundary constraint relationship for universal corner determination across the entire domain through normalization analysis, and provides corner thresholds under typical target sizes and resolutions. It also provides visualization simulation results of the criteria, which can be directly used for ISAL system parameter design, algorithm debugging and field deployment, reducing the difficulty of engineering implementation.

[0099] 5. Good versatility and scalability The evaluation index construction and joint modeling approach of this invention are universal. In addition to high-resolution ISAL systems, it can also be adapted to ISAL systems with longer laser wavelengths. It can also be extended to similar synthetic aperture imaging technologies such as inverse synthetic aperture radar (ISAR). It has a wide range of applications and high promotion value.

[0100] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0101] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications 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.

Claims

1. An improved method for determining large turning angles in ISAL imaging and a joint modeling method for multi-dimensional indices, characterized in that, include: The azimuth scattering center trajectory factor is constructed based on the target's maximum structural size at azimuth, azimuth attitude angle, and system azimuth resolution, and the range scattering center trajectory factor is constructed based on the target's maximum structural size at range, pitch attitude angle, and system range resolution. The two types of scattering center trajectory factors are used to quantify the imaging blur in the azimuth and range directions, respectively. By fusing the two types of scattering center trajectory factors, a two-dimensional joint total fuzzy factor is obtained; The two-dimensional joint total fuzzy factor is compared with the preset two-level fuzzy threshold to determine the small, medium, and large three-level turning angle judgment interval to which it belongs, and the corresponding target turning angle level is output. Based on the pre-defined correspondence between the rotation level and the set of imaging modeling compensation methods, an imaging modeling compensation scheme that is compatible with the target rotation level is matched. Multiple sets of different working conditions are selected. The system azimuth resolution and system distance resolution under each set of working conditions are combined. The maximum structural size of the target's azimuth and distance, as well as the azimuth and pitch attitude angles under the same set of working conditions, are normalized in dimensionless manner to obtain normalized size factors and normalized angle factors. The two-level fuzzy thresholds are used as constraints for fitting to obtain a universal angle determination boundary constraint relationship in which the two types of normalized factors are inversely proportional. Substitute the normalized size factor and normalized rotation factor of the new target into the rotation determination boundary constraint relationship to determine the rotation level of the new target and its corresponding imaging modeling compensation scheme.

2. The improved method for determining large turning angles in ISAL imaging and the joint modeling method of multi-dimensional indices as described in claim 1, characterized in that, Both the azimuth scattering center trajectory factor and the range scattering center trajectory factor are constructed using dimensionless ratio calculations, and are used to quantify the proportion of the target scattering center trajectory offset relative to the system azimuth resolution in the azimuth dimension and the proportion of the target scattering center trajectory offset relative to the system range resolution in the range dimension, respectively.

3. The improved method for determining large turning angles in ISAL imaging and the joint modeling method of multi-dimensional indices as described in claim 1, characterized in that, The fusion of the two types of scattering center trajectory factors adopts L2 norm operation, specifically: the azimuth scattering center trajectory factor and the range scattering center trajectory factor are squared and summed, and then the square root is taken to obtain the two-dimensional joint total fuzzy factor.

4. The improved method for determining large turning angles in ISAL imaging and the joint modeling method of multi-dimensional indicators as described in claim 1, characterized in that, The preset two-level fuzzy thresholds are 0.35 and 0.707, respectively; the three-level turning angle determination intervals (small, medium, and large) include: For small turning intervals, the corresponding two-dimensional joint total fuzzy factor is less than 0.35; In the intermediate turning angle interval, the corresponding two-dimensional joint total fuzzy factor is greater than or equal to 0.35 and less than 0.707; And for the large turning angle interval, the corresponding two-dimensional joint total fuzzy factor is greater than or equal to 0.

707.

5. The improved method for determining large turning angles in ISAL imaging and the joint modeling method of multi-dimensional indices as described in claim 1, characterized in that, The correspondence between the preset rotation level and the set of imaging modeling compensation methods includes: A set of weak blur correction imaging modeling compensation methods is configured for small turning angle levels, including at least principal component analysis and fast Fourier transform; A set of adaptive iterative correction imaging modeling compensation methods is configured for intermediate rotation angle levels, including at least phase gradient autofocus and moving target detection; And a set of global reconstruction imaging modeling compensation methods for large-angle distortion at large-angle levels, including at least back projection and imaging-calibration synchronous modeling.

6. The improved method for determining large turning angles in ISAL imaging and the joint modeling method of multi-dimensional indices as described in claim 5, characterized in that, The imaging-calibration synchronous modeling method includes at least one of the following: an image-optimal imaging and calibration modeling method, an imaging and calibration joint modeling method based on the phase of prominent points, and an imaging and calibration synchronous modeling method based on sparse representation.

7. The improved method for large-angle criterion and multi-dimensional index joint modeling in ISAL imaging as described in any one of claims 1 to 6, characterized in that, The improved large-angle criterion and multi-dimensional index joint modeling method in ISAL imaging are applicable to laser band ISAL imaging systems with a laser wavelength of 1.55 μm. The system's azimuth resolution and distance resolution are both fixed at 0.03 m.

8. An improved device for large-angle criterion and multi-dimensional index joint modeling in ISAL imaging, characterized in that, include: The dual-dimensional trajectory factor construction module is used to construct the azimuth scattering center trajectory factor based on the target's maximum structural size at azimuth, azimuth attitude angle and system azimuth resolution, and to construct the range scattering center trajectory factor based on the target's maximum structural size at range, pitch attitude angle and system range resolution. The two types of scattering center trajectory factors are used to quantify the imaging blur in the azimuth and range directions, respectively. The fuzzy factor fusion processing module is used to fuse the two types of scattering center trajectory factors to obtain a two-dimensional joint total fuzzy factor; The corner level determination module is used to compare the two-dimensional joint total fuzzy factor with the preset two-level fuzzy threshold, determine the small, medium and large three-level corner determination interval to which it belongs, and output the corresponding target corner level. The compensation scheme matching module is used to match an imaging modeling compensation scheme that is compatible with the target rotation angle level based on the preset correspondence between the rotation angle level and the set of imaging modeling compensation methods. The general boundary fitting modeling module is used to select multiple different working conditions, combine the system azimuth resolution and system distance resolution under each working condition, and perform dimensionless normalization on the target's azimuth, distance, maximum structural size, azimuth, pitch attitude and rotation angle under the same working condition to obtain normalized size factor and normalized rotation angle factor. Then, the module uses the two-level fuzzy threshold as constraints to fit and obtain the global general rotation angle determination boundary constraint relationship in which the two types of normalized factors are inversely proportional. The new target adaptive determination module is used to substitute the normalized size factor and normalized rotation factor of the new target into the rotation determination boundary constraint relationship to determine the rotation level of the new target and its corresponding imaging modeling compensation scheme.

9. A storage medium, characterized in that, It stores a computer program, wherein when the computer program is executed by a processor, it implements the improved method for joint modeling of large-angle criteria and multi-dimensional indicators in ISAL imaging as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, The electronic device includes: The processor, the memory, and the program instructions stored in the memory and executable by the processor, wherein when the processor executes the program instructions, it implements the improved method for joint modeling of large-angle criteria and multi-dimensional indicators in ISAL imaging as described in any one of claims 1 to 7.

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