基于空時自適應的天地波混合雷達海雜波抑制方法研究
發(fā)布時間:2019-02-22 18:50
【摘要】:高頻天地波混合雷達是一種天波發(fā)射-地波接收的雙基地雷達。它具有探測距離遠、覆蓋范圍大、反隱身等能力,可以實現(xiàn)對我國廣闊海域進行有效而經濟地遠程監(jiān)控和海態(tài)遙感。然而,天地波混合雷達的雜波背景復雜,海雜波污染嚴重,不利于對目標進行檢測。因此,研究展寬海雜波抑制方法對于雷達性能的提升具有重要的理論意義和實際應用價值。本文從天地波混合雷達一階海雜波展寬的機理入手,首先分析擦地角、雙基地角和電離層擾動這三個因素對一階海雜波展寬的影響。其中,應用兩種方法研究電離層對海雜波展寬的影響:第一、不同積累時間,電離層擾動對一階海雜波的展寬影響不同;第二、應用高階模糊函數(shù)(HAF)分析電離層擾動對一階海雜波的影響,并依據(jù)此標準,提出了電離層擾動有無的判斷準則。其次,理論上分析了一階海雜波的空時耦合性并在此基礎上首次推導了理想情況下的一階海雜波的有效秩;诙嘤柧殬颖镜慕稻S空時自適應(Space Time Adaptive Processing,STAP)算法需要分析樣本之間的相關性,本文從Doppler維、方位維和距離維分析了檢測樣本與訓練樣本之間相關性。Doppler維和方位維的分析結果,確定了降維STAP算法的局域處理自由度;距離維相關性為多樣本選擇提供依據(jù)(相關系數(shù)門限均設為0.7)。為下文算法研究提供了理論依據(jù)。再次,對于存在多個訓練樣本情況下,研究了基于多訓練樣本的降維STAP算法,包括局域空時聯(lián)合處理算法、改進的局域空時聯(lián)合處理算法和空時多波束算法。本文從海雜波被抑制前后目標SNR的變化和主要計算量兩個方面比較了三種算法的性能。最后,針對當某檢測樣本受到電離層快相徑擾動時,很難在鄰近的樣本中找到與檢測樣本具有同態(tài)性的多個樣本的情況,本課題研究了基于快速近似冪迭代算法(Fast Approximation of Power Iteration,FAPI)的單樣本STAP算法。不同于機載雷達,天地波混合雷達雜波環(huán)境復雜,其雜波協(xié)方差矩陣的雜波子空間維數(shù)不能確定。本文結合FAPI算法的目標函數(shù)提出了FAPI-STAP算法數(shù)據(jù)構建評價準則和基于二分法的雜波子空間維數(shù)估計方法。提出的算法不僅可以快速估計出雜波維數(shù),而且計算速度快。同時,本文從海雜波被抑制前后的目標SNR的變化和主要計算量兩個方面評價了FAPI-STAP算法的性能。
[Abstract]:The high frequency ground wave radar is a kind of bistatic radar which transmits the sky wave and receives the ground wave. It has the capability of long detection distance, large coverage and anti-stealth. It can realize effective and economical remote monitoring and remote sensing of sea state in the vast sea area of China. However, the clutter background is complex and the sea clutter pollution is serious, which is not conducive to target detection. Therefore, it is of great theoretical significance and practical application value to study the suppression method of broadening sea clutter for improving radar performance. In this paper, the mechanism of the first order sea clutter broadening of the mixed radar is discussed. Firstly, the influence of three factors, namely, the ground erasing angle, the bistatic angle and the ionospheric disturbance, on the first order sea clutter broadening is analyzed. Two methods are used to study the influence of ionosphere on the broadening of sea clutter: first, the influence of ionospheric disturbance on the broadening of first-order sea clutter is different at different accumulation time; Second, the influence of ionospheric disturbance on first-order sea clutter is analyzed by using high-order fuzzy function (HAF). According to this criterion, a criterion for judging whether ionospheric disturbance exists or not is proposed. Secondly, the space-time coupling of the first-order sea clutter is theoretically analyzed and the effective rank of the first-order sea clutter is derived for the first time in the ideal case. Space time adaptive (Space Time Adaptive Processing,STAP algorithm based on multi-training samples needs to analyze the correlation between samples. The correlation between the detection samples and the training samples is analyzed in the azimuth dimension and the range dimension. The results of the Doppler and the azimuth dimension analysis are used to determine the local processing freedom of the reduced dimension STAP algorithm. Distance correlation provides a basis for the selection of multiple samples (the threshold of correlation coefficient is set to 0.7). It provides a theoretical basis for the following algorithm research. Thirdly, the dimensionality reduction STAP algorithm based on multiple training samples is studied, including the local space-time joint processing algorithm, the improved local space-time joint processing algorithm and the space-time multi-beam algorithm. In this paper, the performance of the three algorithms is compared in terms of the changes of the target SNR before and after the sea clutter is suppressed and the main computational complexity. Finally, when a detected sample is disturbed by the ionospheric fast phase path, it is very difficult to find multiple samples with homomorphism with the detected sample in the adjacent samples. In this paper, the fast approximate power iteration algorithm (Fast Approximation of Power Iteration, is studied. FAPI) single sample STAP algorithm. Unlike airborne radar, the clutter environment of the hybrid radar is complex, and the clutter covariance matrix of the clutter can not be determined in space dimension. In this paper, based on the objective function of FAPI algorithm, an evaluation criterion for data construction of FAPI-STAP algorithm and a method for estimating the dimension of clutter subspace based on dichotomy are proposed. The proposed algorithm not only can estimate the clutter dimension quickly, but also can calculate quickly. At the same time, the performance of the FAPI-STAP algorithm is evaluated from two aspects: the change of the target SNR before and after the sea clutter is suppressed and the main computational complexity.
【學位授予單位】:哈爾濱工業(yè)大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TN958
本文編號:2428507
[Abstract]:The high frequency ground wave radar is a kind of bistatic radar which transmits the sky wave and receives the ground wave. It has the capability of long detection distance, large coverage and anti-stealth. It can realize effective and economical remote monitoring and remote sensing of sea state in the vast sea area of China. However, the clutter background is complex and the sea clutter pollution is serious, which is not conducive to target detection. Therefore, it is of great theoretical significance and practical application value to study the suppression method of broadening sea clutter for improving radar performance. In this paper, the mechanism of the first order sea clutter broadening of the mixed radar is discussed. Firstly, the influence of three factors, namely, the ground erasing angle, the bistatic angle and the ionospheric disturbance, on the first order sea clutter broadening is analyzed. Two methods are used to study the influence of ionosphere on the broadening of sea clutter: first, the influence of ionospheric disturbance on the broadening of first-order sea clutter is different at different accumulation time; Second, the influence of ionospheric disturbance on first-order sea clutter is analyzed by using high-order fuzzy function (HAF). According to this criterion, a criterion for judging whether ionospheric disturbance exists or not is proposed. Secondly, the space-time coupling of the first-order sea clutter is theoretically analyzed and the effective rank of the first-order sea clutter is derived for the first time in the ideal case. Space time adaptive (Space Time Adaptive Processing,STAP algorithm based on multi-training samples needs to analyze the correlation between samples. The correlation between the detection samples and the training samples is analyzed in the azimuth dimension and the range dimension. The results of the Doppler and the azimuth dimension analysis are used to determine the local processing freedom of the reduced dimension STAP algorithm. Distance correlation provides a basis for the selection of multiple samples (the threshold of correlation coefficient is set to 0.7). It provides a theoretical basis for the following algorithm research. Thirdly, the dimensionality reduction STAP algorithm based on multiple training samples is studied, including the local space-time joint processing algorithm, the improved local space-time joint processing algorithm and the space-time multi-beam algorithm. In this paper, the performance of the three algorithms is compared in terms of the changes of the target SNR before and after the sea clutter is suppressed and the main computational complexity. Finally, when a detected sample is disturbed by the ionospheric fast phase path, it is very difficult to find multiple samples with homomorphism with the detected sample in the adjacent samples. In this paper, the fast approximate power iteration algorithm (Fast Approximation of Power Iteration, is studied. FAPI) single sample STAP algorithm. Unlike airborne radar, the clutter environment of the hybrid radar is complex, and the clutter covariance matrix of the clutter can not be determined in space dimension. In this paper, based on the objective function of FAPI algorithm, an evaluation criterion for data construction of FAPI-STAP algorithm and a method for estimating the dimension of clutter subspace based on dichotomy are proposed. The proposed algorithm not only can estimate the clutter dimension quickly, but also can calculate quickly. At the same time, the performance of the FAPI-STAP algorithm is evaluated from two aspects: the change of the target SNR before and after the sea clutter is suppressed and the main computational complexity.
【學位授予單位】:哈爾濱工業(yè)大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TN958
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