【摘要】：海面目標檢測因受到海雜波的影響,傳統(tǒng)目標檢測方法易產生高虛警問題,如何有效抑制非平穩(wěn)的、相關性強的海雜波,提高海面目標的檢測能力,一直是雷達檢測領域的難點問題。在高頻近似情況下,海面目標(例如艦船等)的后向散射常呈現(xiàn)出多散射中心的特點,散射中心數(shù)量一般遠小于觀測區(qū)域的可分辨單元數(shù)量,基本符合壓縮感知(CS,ComPressive Sensing)處理方法對目標散射稀疏先驗的要求。因此,本文利用壓縮感知技術重點開展了以下研究工作:1.在高斯噪聲背景下,研究了迭代軟閾值(IST,Iterative Soft Thresholding)算法的點目標重構能力和輸出噪聲特性。重點討論了基于IST的兩種固定門限檢測器,推導了相應的檢測概率和虛警概率的解析表達式,仿真分析表明,欠采樣下的IST固定門限檢測器性能優(yōu)于匹配濾波最優(yōu)檢測器。另外,給出了基于IST的恒虛警(CFAR)檢測器架構及其性能分析。2.在海雜波背景和點目標檢測條件下,建立了海雜波復合K分布模型,研究了 OMP(Orthogonal Matching Pursuit)和 FOCUSS(Focal Undetermined System Solver)算法對中低海情海雜波的抑制性能,相比經典的白化濾波方法,它們具有更好的海雜波濾除能力。針對海雜波的復雜動力學行為,初步探索了海雜波抑制的深度學習(DeeP Learning)方法,利用卷積自編碼器(CAE,Convolutional Auto-Encode)對回波譜圖中的海雜波和目標進行了有效分離,初步驗證了方法的可行性。3.在海雜波背景下,研究了擴展目標的稀疏檢測方法。擴展目標的多散射中心通常呈現(xiàn)區(qū)域連續(xù)分布的特點,這里利用目標連續(xù)區(qū)域邊界的稀疏性和非零的目標散射點與周圍散射點之間的連續(xù)依賴關系,提出了結合總體變分(Total Variation,TV)正則化約束的SF-LASSO算法,仿真結果表明SF-LASSO算法能較準確反演目標位置和基本輪廓。
[Abstract]:Because the sea surface target detection is affected by sea clutter, the traditional target detection method is easy to produce high false alarm problem. How to effectively suppress the non-stationary and strongly correlated sea clutter and improve the detection ability of the sea surface target, It has always been a difficult problem in the field of radar detection. In the case of high frequency approximation, the backscattering of sea surface targets (such as ships, etc.) often presents the characteristics of multiple scattering centers. The number of scattering centers is generally much smaller than the number of discernible units in the observed region, which basically accords with compression sensing (CS,). A priori requirement for sparse target scattering by ComPressive Sensing) processing method. Therefore, this paper focuses on the following research work using compressed sensing technology: 1. In the background of Gao Si noise, the point target reconstruction ability and output noise characteristics of iterative soft threshold (IST,Iterative Soft Thresholding) algorithm are studied. In this paper, two kinds of fixed threshold detectors based on IST are discussed, and the analytical expressions of detection probability and false alarm probability are derived. The simulation results show that the performance of IST fixed threshold detector under under-sampling is better than that of matched filter optimal detector. In addition, the architecture and performance analysis of CFAR (CFAR) detector based on IST are given. 2. Under the condition of sea clutter background and point target detection, the composite K distribution model of sea clutter is established, and the suppression performance of OMP (Orthogonal Matching Pursuit) and FOCUSS (Focal Undetermined System Solver) algorithms to sea clutter in middle and low sea conditions is studied, compared with the classical whitening filtering method. They have better filtering capability of sea clutter. Aiming at the complex dynamic behavior of sea clutter, the depth learning (DeeP Learning) method for sea clutter suppression is preliminarily explored. The sea clutter and target in echo spectrum are effectively separated by convolution self-encoder (CAE,Convolutional Auto-Encode). The feasibility of the method is preliminarily verified. 3. In the background of sea clutter, the sparse detection method of extended targets is studied. The multi-scattering centers of extended targets usually show the characteristics of continuous regional distribution. In this paper, the sparsity of the boundary of the continuous region of the target and the continuous dependence between the non-zero scattering points and the surrounding scattering points are used. A new SF-LASSO algorithm with global variation (Total Variation,TV) regularization constraints is proposed. The simulation results show that the SF-LASSO algorithm can accurately retrieve the target position and the basic contour.
【學位授予單位】：中國科學技術大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN957.51

【相似文獻】

相關期刊論文 前6條

1 寧蘭忠;;海面目標測控系統(tǒng)的一種設計方法[J];無線電工程;1987年02期

2 陳開元;宋元;;海面目標威脅評估指標體系分析[J];艦船電子工程;2009年06期

3 楊士英;;對海面遠距離目標的高精度定位方法研究[J];電子信息對抗技術;2010年06期

4 楊寶成,沈國土,洪鎮(zhèn)青,高蘭香,毛宏霞,朱文勇,高景;海面目標熱像理論模擬中的幾何構型問題[J];華東師范大學學報(自然科學版);2001年01期

5 陳小龍;關鍵;何友;;微多普勒理論在海面目標檢測中的應用及展望[J];雷達學報;2013年01期

6 孫春韋，，袁潭林，詹明陽，金亦華;2D搜索雷達對海面目標的群跟蹤[J];雷達與對抗;1995年04期

相關重要報紙文章 前1條

1 本報特約撰稿 王群;讓F—35們無處遁形的特殊雷達[N];中國國防報;2014年

相關碩士學位論文 前3條

1 趙洪宇;機載雷達對海目標數(shù)據(jù)處理方法研究[D];電子科技大學;2014年

2 張琦;海面目標的稀疏檢測方法研究[D];中國科學技術大學;2017年

3 馮艷華;海面目標紅外輻射特性研究[D];西安電子科技大學;2009年

本文編號：2382284