A SAR Space Imaging Performance Evaluation Method Based on Three-Dimensional Point Spread Function

Abstract

This invention belongs to the field of radar imaging technology, specifically relating to a SAR spatial imaging performance evaluation method based on a three-dimensional point spread function. By using a target evaluation system to image an ideal point target using a three-dimensional point spread function, and building upon the traditional two-dimensional integral sidelobe ratio (ISLR) evaluation method, this invention introduces parameters affecting the radar system's height resolution and image domain factors affecting the target's three-dimensional resolution. This allows for effective evaluation of three-dimensional imaging performance and provides a direct assessment of the system's three-dimensional imaging performance, making it an efficient method for evaluating the spatial imaging performance of synthetic aperture radar. Furthermore, this invention does not involve complex computational operations and its implementation is relatively simple.

Description

Technical Field

[0001] This invention belongs to the field of radar imaging technology, specifically relating to a SAR spatial imaging performance evaluation method based on a three-dimensional point spread function. Background Technology

[0002] Synthetic Aperture Radar (SAR) is a microwave imaging system capable of generating high-resolution two-dimensional images under various weather conditions, 24 / 7. However, these traditional two-dimensional SAR images are merely projections of three-dimensional objects onto a two-dimensional plane at a certain height, and may not accurately represent the complete appearance or features of the imaged object. Compared to two-dimensional imaging, three-dimensional imaging can acquire richer feature information, including the target's relative position, size, and scattering characteristics in three-dimensional space. This information can be used in subsequent tasks to improve the accuracy and speed of target detection, identification, and classification. Three-dimensional synthetic aperture radar (3D SAR) imaging technology is an indispensable technology for the future and has been receiving increasing attention from academia and industry in recent years.

[0003] Several quality metrics are currently used to evaluate synthetic aperture radar (SAR) images, including spatial resolution (SR), peak sidelobe ratio (PSLR), and integral sidelobe ratio (ISLR). However, simulation results show that traditional evaluation metrics are insufficient to accurately assess the quality of 3D SAR images. Therefore, finding a comprehensive and intuitive method to evaluate the performance of 3D SAR imaging is of great significance. Summary of the Invention

[0004] The purpose of this invention is to address the aforementioned problems and shortcomings by providing a SAR spatial imaging performance evaluation method based on a three-dimensional point spread function. This method, during the synthetic aperture radar (SAR) three-dimensional imaging process, uses a target evaluation system to image an ideal point target using a three-dimensional point spread function. It combines the traditional two-dimensional integral sidelobe ratio (ISLR) evaluation method with the introduction of parameters affecting the radar system's height resolution and image domain factors affecting the target's three-dimensional resolution. This effectively evaluates the three-dimensional imaging performance and provides a direct assessment of the system's three-dimensional imaging performance. It is a highly efficient method for evaluating the spatial imaging performance of SAR.

[0005] The technical solution of this invention is: a SAR space imaging performance evaluation method based on a three-dimensional point spread function, comprising the following steps:

[0006] S1. Use SAR to perform three-dimensional imaging of an ideal point target, and set the three-dimensional imaging scale to be exactly the same, to obtain an N×N×N pixel three-dimensional array containing phase information, that is, the range, azimuth and height directions are all N;

[0007] S2. Normalize the obtained N×N×N pixel three-dimensional array containing phase information, converting the complex signal into a physical quantity containing the scattering intensity of each actual image pixel. A three-dimensional array of (dB);

[0008] S3. Set a reference value in dB. ref The obtained three-dimensional array is traversed to extract values ​​greater than or equal to dB. ref The three-dimensional coordinates of the pixels and their corresponding (dB) value, to generate three-dimensional image domain imaging results;

[0009] S4. Obtain the average value of the angle between the formed 3D image and the vertical direction in the 3D image domain imaging result, denoted as the side lobe angle η. Obtain the radian value of the circumference of the side lobe of the 3D image and the side lobe arc length Δ. φ ;

[0010] S5. The evaluation index SISLR is calculated using the following formula:

[0011]

[0012] The above equation ∫∫∫ -3dB Idxdydz is the physical quantity obtained in step S2. Perform three-dimensional integration, that is, integrate the three-dimensional array obtained in step S2 that satisfies the condition I ≥ -3dB. The values ​​are accumulated, where Similarly.

[0013] The performance of SAR space imaging is evaluated using the obtained evaluation index SISLR value, and the evaluation method is that the lower the SISLR value, the better the performance.

[0014] This invention effectively evaluates 3D imaging performance by combining the traditional two-dimensional integral sidelobe ratio (ISLR) evaluation method with the introduction of radar system parameters that affect altitude resolution and radar system parameters and image domain factors that affect target 3D resolution. This ensures an intuitive and efficient evaluation of synthetic aperture radar spatial imaging performance.

[0015] The advantages of this invention are that it provides an intuitive and efficient way to evaluate the spatial imaging performance of synthetic aperture radar, and that it does not involve complex calculations during implementation. Attached Figure Description

[0016] Figure 1 This is a flowchart of the present invention;

[0017] Figure 2 This is a schematic diagram of the three-dimensional point spread function of an ideal full-aperture circular SAR under certain radar system parameter conditions.

[0018] Figure 3 It's dB ref = -40dB three-dimensional image domain imaging results;

[0019] Figure 4 This is a schematic diagram of the front view of the 3D point extension function;

[0020] Figure 5 This is a schematic diagram of the side lobe angle η;

[0021] Figure 6 This is a top view diagram of the three-dimensional point extension function;

[0022] Figure 7 It is the arc length of the side lobe Δ φ A schematic diagram;

[0023] Figure 8 This is a graph showing the performance evaluation results of radar echoes using this method and traditional methods when the simulation parameters are at a height of 200 meters.

[0024] Figure 9 This is a graph showing the performance evaluation results of radar echoes using this method and traditional methods when the simulation parameters are at a height of 300 meters.

[0025] Figure 10 This is a graph showing the performance evaluation results of using this method and the traditional method when the echoes of the two sets of parameters are superimposed. Detailed Implementation

[0026] The present invention will now be described in detail with reference to the accompanying drawings and simulation examples to demonstrate its practicality.

[0027] As attached Figure 1 As shown, this invention provides a SAR spatial imaging performance evaluation method based on a three-dimensional point spread function to effectively evaluate three-dimensional imaging performance, ensuring an intuitive and efficient evaluation of synthetic aperture radar spatial imaging performance. The specific implementation steps are as follows:

[0028] Step 1: Use the measured system or the radar system parameters to be evaluated to perform three-dimensional imaging of the ideal point target. Any imaging algorithm is applicable. It should be noted that the three-dimensional scale of the imaging must be exactly the same to ensure the accuracy of the evaluation results. For example, 1m×1m×1m, thus obtaining a three-dimensional array (complex number) containing phase information with N×N×N (range, azimuth, and altitude) pixels.

[0029] Step 2: Perform normalized data processing on the newly obtained N×N×N pixel 3D array containing phase information, converting the complex signal into a physical quantity containing the scattering intensity of each pixel in the actual imaging. A three-dimensional array of (dB).

[0030] Step 3: Set a suitable reference value in dB ref Iterate through the three-dimensional array from the previous step and extract those greater than or equal to dB. ref The three-dimensional coordinates of the pixels and their corresponding (dB) value. Generates 3D image domain imaging results.

[0031] Step 4: Obtain the average value of the angles formed by the three-dimensional image and the vertical direction in the image domain, denoted as the side lobe angle η. Obtain the radian value of the circumference of the side lobe of the three-dimensional image and the side lobe arc length Δ. φ .

[0032] Step 5: Calculate using the following formula:

[0033]

[0034] The above equation ∫∫∫ -3dB Idxdydz is the physical quantity obtained in step 2. Perform three-dimensional integration, that is, integrate the three-dimensional array obtained in step S2 that satisfies the condition I ≥ -3dB. The values ​​are accumulated, where The same applies to Idxdydz.

[0035] The performance of SAR space imaging is evaluated using the obtained evaluation index SISLR value, and the evaluation method is that the lower the SISLR value, the better the performance.

[0036] Simulation Example

[0037] The above method is attached. Figure 1 The simulation parameters are set as follows: circular SAR imaging mode is used, the radar is 200 meters above the ground, the imaging radius is 500 meters, the transmitted signal is in the X-band, and the center carrier frequency is 11.2 GHz.

[0038] Figure 2 The three-dimensional point spread function of an ideal full-aperture circular SAR is given;

[0039] Figure 3 The three-dimensional image domain imaging results obtained by simulation using the above parameters are presented.

[0040] Figure 4 A schematic diagram of the front view of a three-dimensional point extension function is given, which usually looks like the front view of two opposing ice cream cones;

[0041] Figure 5 A schematic diagram of the sidelobe angle is given, which is expressed in radians in the formula. When the sidelobe angle decreases, the height increases towards resolution, and vice versa.

[0042] Figure 6 A schematic diagram of the top view of a three-dimensional point spread function at a certain height is given, which is usually an annulus;

[0043] Figure 7 A schematic diagram of the side lobe arc length is given. The side lobe arc length is directly proportional to the aperture size, and the maximum arc length is 2π in full aperture imaging.

[0044] Figure 8 The results of performance evaluation of radar echoes using this method and traditional methods are presented, with simulation parameters at a height of 200 meters.

[0045] Figure 9 The results of performance evaluation of radar echoes using this method and traditional methods are presented in the figure when the simulation parameters are at an altitude of 300 meters.

[0046] Figure 10 The results of performance evaluation using this method and the traditional method when the echoes of the above two sets of parameters are superimposed are given.

[0047] By comparison Figure 8 , Figure 9 , Figure 10 The results clearly show that using two-dimensional metrics such as peak sidelobe ratio (PSLR) and integral sidelobe ratio (ISLR) to evaluate three-dimensional imaging results is not intuitive and cannot directly determine the quality of the imaging. The method provided by this invention can effectively evaluate three-dimensional imaging performance, yielding intuitive results and facilitating comparisons of three-dimensional imaging performance.

[0048] In conclusion, the method provided by this invention has practical value based on the processing results.

Claims

1. A method for evaluating the performance of SAR spatial imaging based on a three-dimensional point spread function, characterized in that, Includes the following steps: S1. Use SAR to perform three-dimensional imaging of an ideal point target, and set the three-dimensional imaging scale to be exactly the same, to obtain an N×N×N pixel three-dimensional array containing phase information, that is, the range, azimuth and height directions are all N; S2. Normalize the obtained N×N×N pixel three-dimensional array containing phase information, converting the complex signal into a physical quantity containing the scattering intensity of each actual image pixel. A three-dimensional array of (dB); S3. Set a reference value in dB. ref The obtained three-dimensional array is traversed to extract values ​​greater than or equal to dB. ref The three-dimensional coordinates of the pixels and their corresponding (dB) value, to generate three-dimensional image domain imaging results; S4. Obtain the average value of the angle between the formed 3D image and the vertical direction in the 3D image domain imaging result, denoted as the side lobe angle η. Obtain the radian value of the circumference of the side lobe of the 3D image and the side lobe arc length Δ. φ ; S5. The evaluation index SISLR is calculated using the following formula: The above equation ∫∫∫ -3dB Idxdydz is the physical quantity obtained in step S2. Perform three-dimensional integration, that is, integrate the three-dimensional array obtained in step S2 that satisfies the condition I ≥ -3dB. The values ​​are accumulated, where Similarly; The performance of SAR space imaging was evaluated using the obtained evaluation index SISLR, and the evaluation method was that the lower the SISLR value, the better the performance.

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