Adaptive Compensation Method for Multi-Pulse Spatiotemporal Dispersion Effect Error in Plasma Sheath

Abstract

An adaptive compensation method for multi-pulse spatiotemporal dispersion error of plasma sheath is proposed. This method addresses the real-world scenario of multiple scattering centers and spatiotemporal dispersion error coupling in hypersonic targets. It employs an image peak search method to segment scattering points affected by different dispersion errors. Based on image focusing theory, maximum contrast self-focusing compensation is performed on each segmented scattering point. Simultaneously, the inter-point regions are judged and compensated to achieve accurate compensation for the spatiotemporal dispersion error of the target covered by the plasma sheath. This invention features high compensation accuracy, high compensation efficiency, strong scalability, and simple calculation steps.

Description

Technical Field

[0001] This invention relates to the field of radar imaging technology, specifically to an adaptive compensation method for errors caused by multi-pulse spatiotemporal dispersion effects in plasma sheaths. Background Technology

[0002] When a near-space hypersonic vehicle travels at speeds approaching Mach 10, various air molecules undergo aerothermal ionization to form plasma that adheres to the target surface, creating a plasma sheath. Due to the dispersion effect of the plasma sheath, an additional secondary phase is introduced into the radar echo in the frequency domain, causing radar echo broadening and resulting in defocusing during radar imaging. This leads to decreased imaging accuracy and target loss. Because the plasma sheath on the surface of a hypersonic vehicle has flow field distribution characteristics, the parameters of the plasma sheath vary significantly in different regions (stagnation zone, intermediate zone, and tail zone), and change with the vehicle's altitude, speed, and attitude. Therefore, the dispersion effect of the plasma sheath on the target surface is space-time varied, and the dispersion phase error introduced into the radar echo during target detection and imaging is also space-time varied. However, existing methods for compensating for the dispersion effect of the plasma sheath do not take into account the key factor of the spatiotemporal dispersion effect of the plasma sheath on the surface of hypersonic targets. Given the multiple scattering centers that hypersonic targets exhibit in radar imaging, there is currently no research specifically addressing the impact of the spatiotemporal dispersion effect of the plasma sheath and the coupling problem of multiple scattering points on ISAR imaging.

[0003] Existing techniques for compensating for defocusing in ISAR imaging caused by the dispersion effect of plasma sheaths mainly assume the quasi-static characteristics of the plasma sheath and use a uniform dispersion effect phase error to compensate for different scattering points of hypersonic targets. Based on the principle of maximum contrast autofocus and prior knowledge, a dispersion compensation factor and iteration step size are constructed in the frequency domain, and a dispersion compensation function is constructed in combination with the radar frequency. The iteration step size is adjusted according to the image contrast before and after compensation. Through continuous iteration, a uniform compensation for the dispersion effect phase error is achieved (Publication No.: CN116859388A, Title: A Method for Suppressing Dispersion Effect in ISAR Imaging of Targets Covered by Plasma Sheaths).

[0004] Existing technologies do not take into account the spatiotemporal variation of the dispersion effect caused by the plasma sheath. Considering the multi-scattering center distribution of hypersonic targets in radar imaging, traditional methods cannot solve the radar imaging defocusing problem caused by the coupling effect of phase error of spatiotemporal dispersion effect and multi-scattering points. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, the present invention aims to provide an adaptive compensation method for the error of multi-pulse spatiotemporal dispersion effect of plasma sheath, which realizes accurate compensation of the error of spatiotemporal dispersion effect of target covered by plasma sheath, and has the characteristics of high compensation accuracy, high compensation efficiency, strong scalability and simple calculation steps.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] An adaptive compensation method for multi-pulse spatiotemporal dispersion error of plasma sheath is proposed. This method addresses the real-world scenario of multiple scattering centers and spatiotemporal dispersion error coupling in hypersonic targets. It employs an image peak search method to segment scattering points affected by different dispersion errors. Based on image focusing theory (Carrara W, Goodman RS, Majewski R M. Spotlight Synthetic Aperture Radar: Signal Processing Algorithms[J].1995.), maximum contrast self-focusing compensation is performed on each segmented scattering point. Simultaneously, the inter-point regions are judged and compensated to achieve accurate compensation for the spatiotemporal dispersion error of the target covered by the plasma sheath.

[0008] An adaptive compensation method for multi-pulse spatiotemporal dispersion effect error in plasma sheaths includes the following steps:

[0009] Step 1, Scattering Center Search: Using the peak search method, search for strong scattering points P1, P2, ..., P in the image to be processed. n ;

[0010] Step 2, Window selection and image segmentation: For the multiple strong scattering points P1, P2, ..., P obtained in Step 1... n Select a window to perform image segmentation, and obtain the two-dimensional image matrix A1, A2, ..., A n ;

[0011] Step 3, Scattering point region compensation and dispersion error estimation: Set the initial dispersion compensation factor γ, iteration step size Δγ, and construct the dispersion compensation function. The dispersion error detection threshold γ is calculated based on image focusing theory. g The dispersion compensation factor is adjusted based on the contrast of the two-dimensional image matrix before and after compensation. Through continuous iterative iteration, the two-dimensional image matrix A1, A2, ..., A n The compensation is performed, and the two-dimensional image matrices A1, A2, ..., A are estimated. n The secondary phase errors Φ1,Φ2,…,Φ n ;

[0012] Step 4, Inter-point region judgment and compensation: Based on the quadratic phase error Φ1,Φ2,…,Φ of the two-dimensional image matrix in Step 3. n Determine whether the area between points needs compensation; if so, perform compensation.

[0013] Step 5, Image Combining: Combine the compensated images according to their original positions before segmentation to form a new image A. final .

[0014] Step 2 specifically includes:

[0015] Taking a strong scattering point P1 as an example, a window with a range length of x1 and an azimuth length of y1 is used to extract it, resulting in a two-dimensional image matrix A1 (a matrix of x1×y1); similarly, for scattering points P2, ..., P... n The image is sequentially divided into a two-dimensional image matrix A2 (a matrix of x2×y2), and the two-dimensional image matrix image A... n (x n ×y n (matrix).

[0016] Step 3 specifically involves:

[0017] Step 3.1, taking the two-dimensional image matrix A1 as an example, set its dispersion compensation factor γ1 and iteration step size Δγ, and calculate the dispersion error detection threshold γ according to image focusing theory. g The calculation formula is:

[0018]

[0019] In the formula, B w For the bandwidth of the radar system;

[0020] The formula for calculating the constructed dispersion compensation function is as follows:

[0021]

[0022] In the formula, f is the radar frequency used (f0-B) w / 2≤f≤f0+B w / 2), f0 is the radar carrier frequency, and j is the imaginary unit;

[0023] Step 3.2: Perform a Fast Fourier Transform (FFT) on the two-dimensional image matrix A1, and multiply it in the range frequency domain by a dispersion compensation function. Compensation is performed, followed by an Inverse Fast Fourier Transform (IFFT) to transform it back to the distance-time domain. The calculation formula is as follows:

[0024]

[0025]

[0026]

[0027] In the formula, To compensate for the temporal data of the previous two-dimensional image matrix A1, To compensate for the distance frequency domain data of the previous two-dimensional image matrix A1, To compensate for the data with coordinates (x1, y1) in the distance frequency domain data of the previous two-dimensional image matrix A1, To compensate for the distance frequency domain data of the two-dimensional image matrix A1, To compensate for the data with coordinates (x1, y1) in the time domain of the two-dimensional image matrix A1, This is to compensate for the data with coordinates (x1, y1) in the distance frequency domain data of the two-dimensional image matrix A1;

[0028] Step 3.3: Calculate the image contrast C before and after compensation for the nth two-dimensional image matrix. n1 and C n2 The calculation formula is:

[0029]

[0030]

[0031] In the formula, I n1 (x,y) is a two-dimensional image matrix A n The temporal magnitude of each data point in the matrix before compensation, I n2 (x,y) is a two-dimensional image matrix A n The temporal magnitude of each data point in the compensated matrix;

[0032] Step 3.4, based on the image contrast C before and after compensation. n1 and C n2 The size relationship is adjusted by changing the iteration step size. If C n1 >C n2 Then Δγ takes the value -Δγ / 2, if C n1 <C n2 Then Δγ is taken as Δγ, and a new dispersion compensation function is constructed based on this. Through continuous iteration, when the iteration step size Δγ is less than the dispersion error detection threshold γ... g When the loop ends, the dispersion compensation factor γ at which the image has maximum contrast is obtained. 1_max The second phase error is obtained, and the calculation formula is:

[0033]

[0034] Step 4 specifically involves:

[0035] Taking the two-dimensional image matrices A1 and A2 containing scattering points 1 and 2 as an example, according to the quadratic phase errors Φ1 and Φ2 calculated in step 3, if (|Φ1|-|Φ2|)>π / 4, then compensation is needed for the region between scattering points 1 and 2. The dispersion compensation factor is selected as 1 / (2(γ 1_max +γ 2_max The algorithm searches and determines whether strong scattering points appear after compensation. If they do, step 3 is performed on this area. If no strong scattering points appear after compensation, the area between scattering point 1 and scattering point 2 is considered not to need compensation. If (|Φ1|-|Φ2|)<π / 4, the area between scattering point 1 and scattering point 2 is considered not to need compensation.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] 1. This invention features high compensation accuracy. It considers the coupling between multiple scattering centers and space-time-varying dispersion error during radar imaging of hypersonic targets, and compensates separately for different scattering centers affected by different dispersion error patterns. Compared to existing unified compensation methods based on static dispersion error models, this invention can more accurately compensate for space-time-varying dispersion error coupled with the target's multiple scattering centers, exhibiting high compensation accuracy.

[0038] 2. This invention features high compensation efficiency. It only needs to compensate the scattering point region, then judges the regions between scattering points and compensates as needed. Compared to other methods that process each pulse individually, this invention has high computational efficiency for large amounts of data and full-scene radar echo data.

[0039] 3. This invention is highly scalable. Because the dispersion effect error compensation principle and detection threshold selection of this invention are unaffected by the aircraft's altitude, speed, or attitude, it can be flexibly applied to plasma sheaths under various temperature and pressure conditions and radar systems in multiple frequency bands, thus exhibiting extremely high scalability.

[0040] 4. This invention features simple calculation steps. It adaptively compensates for the space-time variation dispersion effect error in hypersonic target radar detection through only five steps, with simple and clear steps. Attached Figure Description

[0041] Figure 1 This is a flowchart of the method of the present invention.

[0042] Figure 2These are radar imaging images of multi-point target dispersion effect before and after compensation, obtained by simulation in an embodiment of the present invention. (a) is the radar imaging image before compensation, and (b) is the radar imaging image after compensation.

[0043] Figure 3 These are radar echo images of multi-point targets before and after dispersion effect error compensation obtained from simulation in an embodiment of the present invention. Among them, (a) is the radar echo image of point P1 before dispersion effect error compensation, (b) is the radar echo image of point P1 after dispersion effect error compensation, (c) is the radar echo image of point P2 before dispersion effect error compensation, (d) is the radar echo image of point P2 after dispersion effect error compensation, (e) is the radar echo image of point P3 before dispersion effect error compensation, and (f) is the radar echo image of point P3 after dispersion effect error compensation. Detailed Implementation

[0044] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0045] An adaptive compensation method for multi-pulse spatiotemporal dispersion effect error in plasma sheaths includes the following steps:

[0046] Step 1, Scattering Center Search: Using the peak search method, search for strong scattering points P1, P2, ..., P in the image to be processed. n ;

[0047] Step 2, Window selection and image segmentation: For the multiple strong scattering points P1, P2, ..., P obtained in Step 1... n Select a window to perform image segmentation, and obtain the two-dimensional image matrix A1, A2, ..., A n Specifically:

[0048] Taking a strong scattering point P1 as an example, a window with a range length of x1 and an azimuth length of y1 is used to extract it, resulting in a two-dimensional image matrix A1 (a matrix of x1×y1); similarly, for scattering points P2, ..., P... n The data is sequentially divided into a two-dimensional image matrix A2 (a matrix of x2×y2). n (x n ×y n (matrix);

[0049] Step 3, Scattering point region compensation and dispersion error estimation: Set the initial dispersion compensation factor γ, iteration step size Δγ, and construct the dispersion compensation function. The dispersion error detection threshold γ is calculated based on image focusing theory. g The dispersion compensation factor is adjusted based on the contrast of the two-dimensional image matrix before and after compensation. Through continuous iterative iteration, the two-dimensional image matrix A1, A2, ..., A n The compensation is performed, and the two-dimensional image matrices A1, A2, ..., A are estimated.n The secondary phase errors Φ1,Φ2,…,Φ n Specifically:

[0050] Step 3.1, taking the two-dimensional image matrix A1 as an example, set its dispersion compensation factor γ1 and iteration step size Δγ, and calculate the dispersion error detection threshold γ according to image focusing theory. g The calculation formula is:

[0051]

[0052] In the formula, B w For the bandwidth of the radar system;

[0053] The formula for calculating the constructed dispersion compensation function is as follows:

[0054]

[0055] In the formula, f is the radar frequency used (f0-B) w / 2≤f≤f0+B w / 2), f0 is the radar carrier frequency, and j is the imaginary unit;

[0056] Step 3.2: Perform a Fast Fourier Transform (FFT) on the two-dimensional image matrix A1, and multiply it in the range frequency domain by a dispersion compensation function. Compensation is performed, followed by an Inverse Fast Fourier Transform (IFFT) to transform it back to the distance-time domain. The calculation formula is as follows:

[0057]

[0058]

[0059]

[0060] In the formula, To compensate for the temporal data of the previous two-dimensional image matrix A1, To compensate for the distance frequency domain data of the previous two-dimensional image matrix A1, To compensate for the data with coordinates (x1, y1) in the distance frequency domain data of the previous two-dimensional image matrix A1, To compensate for the distance frequency domain data of the two-dimensional image matrix A1, To compensate for the data with coordinates (x1, y1) in the time domain of the two-dimensional image matrix A1, This is to compensate for the data with coordinates (x1, y1) in the distance frequency domain data of the two-dimensional image matrix A1;

[0061] Step 3.3: Calculate the image contrast C before and after compensation for the nth two-dimensional image matrix. n1 and C n2 The calculation formula is:

[0062]

[0063]

[0064] In the formula, I n1 (x,y) is a two-dimensional image matrix A n The temporal magnitude of each data point in the matrix before compensation, I n2 (x,y) is a two-dimensional image matrix A n The temporal magnitude of each data point in the compensated matrix;

[0065] Step 3.4, based on the image contrast C before and after compensation. n1 and C n2 The size relationship is adjusted by changing the iteration step size. If C n1 >C n2 Then Δγ takes the value -Δγ / 2, if C n1 <C n2 Then Δγ is taken as Δγ, and a new dispersion compensation function is constructed based on this. Through continuous iteration, when the iteration step size Δγ is less than the dispersion error detection threshold γ... g When the loop ends, the dispersion compensation factor γ at which the image has maximum contrast is obtained. 1_max The second phase error is obtained, and the calculation formula is:

[0066]

[0067] Step 4, Inter-point region judgment and compensation: Based on the quadratic phase error Φ1,Φ2,…,Φ of the two-dimensional image matrix in Step 3. n Determine whether the area between points needs compensation; if so, perform compensation. Specifically:

[0068] Taking the two-dimensional image matrices A1 and A2 containing scattering points 1 and 2 as an example, according to the quadratic phase errors Φ1 and Φ2 calculated in step 3, if (|Φ1|-|Φ2|)>π / 4, then compensation is needed for the region between scattering points 1 and 2. The dispersion compensation factor is selected as 1 / (2(γ 1_max +γ 2_max The algorithm searches and determines whether strong scattering points appear after compensation. If they do, step 3 needs to be performed on this area. If no strong scattering points appear after compensation, the area between scattering point 1 and scattering point 2 is considered not to need compensation. If (|Φ1|-|Φ2|)<π / 4, the area between scattering point 1 and scattering point 2 is considered not to need compensation.

[0069] Step 5, Image Combining: Combine the compensated images according to their original positions before segmentation to form a new image A. final .

[0070] The application effects of the present invention will be described in detail below with reference to the embodiments.

[0071] The embodiment uses simulation to obtain radar images of targets covered by plasma sheaths under the dispersion effect. Since it is currently impossible to directly obtain the quadratic term coefficient information of the dispersion effect phase error of the plasma sheath on the reentry vehicle surface, this embodiment simulates a radar image of a combination of three point targets under the influence of dispersion effect error. Different quadratic term coefficients of the dispersion effect phase error are applied to the three points. The parameter selection refers to the experimental results of RAM-C (Radio Attenuation Measurement) (Beck, FB; Castellow; Swift, CT; Thomson, J. RAM C-3S-band diagnostic experiment. NASA Special Publication, 1970, 1.). The parameters involved in the processing are shown in Table 1:

[0072] Table 1 Parameters of the Example

[0073]

[0074] Reference Figure 1 An adaptive compensation method for multi-pulse spatiotemporal dispersion effect error in plasma sheaths includes the following steps:

[0075] Step 1, Scattering Center Search: Using the peak search method, the strong scattering points P1 and P2 in the image to be processed (300×161) are searched.

[0076] Step 2, Window Selection and Image Segmentation: Select a suitable window for the two strong scattering points obtained in Step 1 to perform image segmentation, obtaining the two-dimensional image matrices A1 and A2 to be processed.

[0077] For the strong scattering point P1, a window with a range length of 161 and an azimuth length of 20 is used to extract it, resulting in a two-dimensional image matrix A1 (20×161); similarly, the scattering point P2 is divided into a two-dimensional image matrix A2 (20×161).

[0078] Step 3, Scattering point region compensation and dispersion error estimation: Set the initial dispersion compensation factor γ, iteration step size Δγ, and construct the dispersion compensation function. The dispersion error detection threshold γ is calculated based on image focusing theory. gThe dispersion compensation factor is adjusted based on the contrast of the two-dimensional image matrix before and after compensation. Through continuous iterative iteration, the compensation of the two-dimensional image matrix A1 and A2 is achieved, and the secondary phase errors Φ1 and Φ2 of the two-dimensional image matrix A1 and A2 are estimated.

[0079] Step 3.1, for the two-dimensional image matrix A1, set its dispersion compensation factor γ1 = 1 × 10⁻¹⁰. -16 The iteration step size Δγ = 1 × 10 -17 The dispersion error detection threshold γ was calculated. g =3.14×10 -18 The calculation formula is:

[0080]

[0081] In the formula, B w For the bandwidth of the radar system;

[0082] The formula for calculating the constructed dispersion compensation function is as follows:

[0083]

[0084] In the formula, f is the radar frequency used (f0-B) w / 2≤f≤f0+B w / 2), f0 is the radar carrier frequency, and j is the imaginary unit;

[0085] Similarly, for a two-dimensional image matrix A2, its dispersion compensation factor γ2 is set to 1 × 10. -16 The iteration step size Δγ = 1 × 10 -17 The dispersion error detection threshold γ is calculated based on image focusing theory. g =3.14×10 -18 ;

[0086] The formula for calculating the constructed dispersion compensation function is as follows:

[0087]

[0088] Step 3.2: Perform a range-direction FFT on the two-dimensional image matrix A1, and multiply it in the range frequency domain by a dispersion compensation function. Compensation is performed, followed by IFFT transformation back to the distance-time domain. The calculation formula is as follows:

[0089]

[0090]

[0091]

[0092] In the formula, To compensate for the temporal data of the previous two-dimensional image matrix A1, To compensate for the distance frequency domain data of the previous two-dimensional image matrix A1, To compensate for the data with coordinates (20, 161) in the distance frequency domain data of the previous two-dimensional image matrix A1, To compensate for the distance frequency domain data of the two-dimensional image matrix A1, To compensate for the data with coordinates (20, 161) in the time domain of the two-dimensional image matrix A1;

[0093] Similarly, perform a range-direction FFT on the two-dimensional image matrix A2, and multiply it in the range frequency domain by the dispersion compensation function. Compensation is performed, followed by IFFT transformation back to the distance-time domain. The calculation formula is as follows:

[0094]

[0095]

[0096]

[0097] In the formula, To compensate for the temporal data of the previous two-dimensional image matrix A2, To compensate for the distance frequency domain data of the previous two-dimensional image matrix A2, To compensate for the data with coordinates (20, 161) in the distance frequency domain data of the previous two-dimensional image matrix A2, To compensate for the distance frequency domain data of the two-dimensional image matrix A2, To compensate for the data with coordinates (20, 161) in the time domain of the two-dimensional image matrix A2;

[0098] Step 3.3: For the two-dimensional image matrix A1, calculate the image contrast C before compensation. 11 =9.13 and the compensated image contrast C 12 =7.91, the calculation formula is:

[0099]

[0100]

[0101] In the formula, I 11 (x,y) represents the temporal magnitude of each data point in the two-dimensional image matrix A1 before compensation. 12 (x,y) represents the temporal magnitude of each data point in the two-dimensional image matrix A1 after compensation.

[0102] For a two-dimensional image matrix A2, calculate the image contrast C before compensation. 21 =7.50 and the compensated image contrast C22 =6.80, the calculation formula is:

[0103]

[0104]

[0105] In the formula, I 21 (x,y) represents the temporal magnitude of each data point in the two-dimensional image matrix A2 before compensation. 22 (x,y) represents the temporal magnitude of each data point in the matrix after A2 compensation of the image;

[0106] Step 3.4, for the two-dimensional image matrix A1, since C 11 >C 12 , then Δγ=-1 / (2Δγ)=-5×10 -18 And based on this, a new dispersion compensation function is constructed. Through continuous iteration, when the iteration step size Δγ = 3.50 × 10 -20 Less than the dispersion error detection threshold γ g =6.98×10 -20 When the loop ends, the dispersion compensation factor γ at which the image has maximum contrast is obtained. 1_max =1.25×10 -17 The secondary phase error Φ1 = 0.99π is obtained, and the calculation formula is as follows:

[0107]

[0108] Similarly, for a two-dimensional image matrix A2, since C 21 >C 22 , then Δγ=-1 / (2Δγ)=-5×10 -18 And based on this, a new dispersion compensation function is constructed. Through continuous iteration, when the iteration step size Δγ = 3.91 × 10 -20 Less than the dispersion error detection threshold γ g =6.98×10 -20 When the loop ends, the dispersion compensation factor γ at which the image has maximum contrast is obtained. 2_max =2.80×10 -17 The secondary phase error Φ2 = 2.23π is obtained, and the calculation formula is:

[0109]

[0110] Step 4, Inter-point Region Judgment and Compensation: Based on the secondary phase errors Φ1 and Φ2 in Step 3, determine whether the inter-point region needs compensation. If so, perform compensation; specifically:

[0111] Based on the secondary phase errors Φ1 and Φ2 calculated in step 3, since |Φ1|-|Φ2|>π / 4, a compensation is needed for the region between scattering point 1 and scattering point 2. The dispersion compensation factor is selected as 1 / (2(γ 1_max +γ 2_max ))=2.025×10 -17 After searching and judging, a strong scattering point P3 was found after compensation. After compensating this new P3 point by step 3, its second phase error Φ3=1.09π was found. After continuing to compensate the region between P1 and P3, and between P2 and P3, it was found that there was no scattering point in the middle region, and the compensation ended.

[0112] Step 5, Image Combination: Combine the compensated images P1, P2, and P3 according to their original positions before segmentation to form a new image A. final .

[0113] Reference Figure 2 , Figure 2 The ISAR image obtained after this embodiment shows that the defocusing at scattering points P1 and P3 is effectively suppressed, and the target loss at P2 caused by dispersion effect is also recovered after compensation. Meanwhile, referring to... Figure 3 In this embodiment, radar echo maps of the three scattering points before and after dispersion error compensation are also given. Before compensation, the radar echoes showed varying degrees of broadening. After compensation, the quality evaluation index of the radar echoes was greatly improved. The evaluation indexes of the three scattering points are shown in Table 2. Among them, the range resolution of P1 increased from 0.40m to 0.13m, the peak sidelobe ratio increased from -0.29dB to -13.26dB, and the integral sidelobe ratio increased from -1.72dB to -9.99dB. Table 3 presents the estimated values ​​of the quadratic coefficients of the dispersion effect phase error at the three scattering points. Comparison with the theoretical values ​​reveals that the relative errors in estimating the quadratic coefficients of the dispersion effect phase error at P1 are 0.8%, at P2 0.4%, and at P3 0.7%. This analysis demonstrates that the adaptive compensation algorithm used in this paper can accurately estimate the quadratic coefficients of the dispersion effect phase error experienced by different radar echoes, thereby achieving precise compensation for the dispersion effect error. Therefore, the adaptive compensation method for the multi-pulse spatiotemporal varying dispersion effect error of a plasma sheath proposed in this invention can accurately compensate for the impact of the spatiotemporal varying dispersion effect error of the plasma sheath on radar imaging, verifying the effectiveness of the algorithm.

[0114] Table 2

[0115]

[0116] Table 3

[0117]

[0118] In summary, the above embodiments demonstrate that the adaptive compensation method for the multi-pulse spatiotemporal dispersion effect error of plasma sheath proposed in this invention can accurately and easily compensate for the spatiotemporal dispersion effect error of the target covered by the plasma sheath.

Claims

1. An adaptive compensation method for multi-pulse spatiotemporal dispersion effect error in plasma sheaths, characterized in that: For the practical scenario of multiple scattering centers and spatiotemporal dispersion error coupling of hypersonic targets, an image peak search method is adopted to segment scattering points affected by different dispersion error. Based on image focusing theory, maximum contrast self-focusing compensation is performed on the segmented scattering points. At the same time, the inter-point regions are judged and compensated to achieve accurate compensation of spatiotemporal dispersion error of plasma sheath-encased targets. The aforementioned adaptive compensation method for multi-pulse spatiotemporal dispersion effect error in plasma sheaths includes the following steps: Step 1, Scattering Center Search: Using the peak search method, search for strong scattering points P1, P2, ..., P in the image to be processed. n ; Step 2, Window selection and image segmentation: For the multiple strong scattering points P1, P2, ..., P obtained in Step 1... n Select a window to perform image segmentation, and obtain the two-dimensional image matrix A1, A2, ..., A n ; Step 3, Scattering point region compensation and dispersion error estimation: Set the initial dispersion compensation factor γ, iteration step size Δγ, and construct the dispersion compensation function. 1≤k≤n, calculate the dispersion error detection threshold γ based on image focusing theory. g The dispersion compensation factor is adjusted based on the contrast of the two-dimensional image matrix before and after compensation. Through continuous iterative iteration, the two-dimensional image matrix A1, A2, ..., A n The compensation is performed, and the two-dimensional image matrices A1, A2, ..., A are estimated. n The secondary phase errors Φ1,Φ2,…,Φ n ; Step 3 specifically involves: Step 3.1: For the two-dimensional image matrix A1, set its dispersion compensation factor γ1 and iteration step size Δγ, and calculate the dispersion error detection threshold γ based on image focusing theory. g The calculation formula is: In the formula, B w For the bandwidth of the radar system; The formula for calculating the constructed dispersion compensation function is as follows: In the formula, f is the radar frequency used, and f0-B w / 2≤f≤f0+B w / 2, f0 is the radar carrier frequency, and j is the imaginary unit; Step 3.2: Perform a Fast Fourier Transform (FFT) on the two-dimensional image matrix A1, and multiply it in the range frequency domain by a dispersion compensation function. Compensation is performed, followed by an Inverse Fast Fourier Transform (IFFT) to transform it back to the distance-time domain. The calculation formula is as follows: In the formula, To compensate for the temporal data of the previous two-dimensional image matrix A1, To compensate for the distance frequency domain data of the previous two-dimensional image matrix A1, To compensate for the data with coordinates (x1, y1) in the distance frequency domain data of the previous two-dimensional image matrix A1, To compensate for the distance frequency domain data of the two-dimensional image matrix A1, This is to compensate for the data with coordinates (x1, y1) in the distance frequency domain data of the two-dimensional image matrix A1; Step 3.3: Calculate the image contrast C before and after compensation for the nth two-dimensional image matrix. n1 and C n2 The calculation formula is: In the formula, I n1 (x,y) is a two-dimensional image matrix A n The temporal magnitude of each data point in the matrix before compensation, I n2 (x,y) is a two-dimensional image matrix A n The temporal magnitude of each data point in the compensated matrix; Step 3.4, based on the image contrast C before and after compensation. n1 and C n2 The size relationship is adjusted by changing the iteration step size. If C n1 >C n2 Then Δγ takes the value -Δγ / 2, if C n1 <C n2 Then Δγ is taken as Δγ, and a new dispersion compensation function is constructed based on this. Through continuous iteration, when the iteration step size Δγ is less than the dispersion error detection threshold γ... g When the loop ends, the dispersion compensation factor γ at which the image has maximum contrast is obtained. 1_max The second phase error is obtained, and the calculation formula is as follows: Step 4, Inter-point region judgment and compensation: Based on the quadratic phase error Φ1,Φ2,…,Φ of the two-dimensional image matrix in Step 3. n Determine whether the area between points needs compensation; if so, perform compensation. Step 5, Image Combining: Combine the compensated images according to their original positions before segmentation to form a new image A. final .

2. The method according to claim 1, characterized in that, Step 2 specifically includes: For a strong scattering point P1, a window with a range length of x1 and an azimuth length of y1 is used to extract it, resulting in a two-dimensional image matrix A1, which is an x1×y1 matrix; similarly, for scattering points P2, ..., P... n The image is sequentially divided into a two-dimensional image matrix A2, which is an x2×y2 matrix; the two-dimensional image matrix image A n x n ×y n The matrix.

3. The method according to claim 1, characterized in that, Step 4 specifically involves: For the two-dimensional image matrices A1 and A2 containing scattering points 1 and 2, based on the quadratic phase errors Φ1 and Φ2 calculated in step 3, if (|Φ1|-|Φ2|)>π / 4, then compensation is needed for the region between scattering points 1 and 2. The dispersion compensation factor is selected as 1 / (2(γ)). 1_max +γ 2_max The algorithm searches and determines whether strong scattering points appear after compensation. If they do, step 3 is performed on this area. If no strong scattering points appear after compensation, the area between scattering point 1 and scattering point 2 is considered not to need compensation. If (|Φ1|-|Φ2|)<π / 4, the area between scattering point 1 and scattering point 2 is considered not to need compensation.

Images