本文選題：MIMO雷達 + 低空檢測�。� 參考：《國防科學技術(shù)大學》2014年博士論文

【摘要】：低空飛行目標檢測及跟蹤作為雷達面臨的四大威脅之一,至今未能有效的解決。多發(fā)多收(Multi-Input Multi-Output,MIMO)雷達做為近年備受關(guān)注的新雷達體制。MIMO雷達利用分集增益在目標檢測、參數(shù)估計、目標跟蹤、目標識別及抗干擾等方面較之傳統(tǒng)雷達有著明顯的優(yōu)勢。基于以上認識,MIMO雷達可以做為解決低空飛行難目標檢測的技術(shù)途徑。近年來國內(nèi)外學者對MIMO雷達在目標檢測、成像識別、參數(shù)估計進行了廣泛深入的研究,然而基于MIMO雷達技術(shù)的低空目標檢測及參數(shù)估計卻很少涉及。為解決了低空目標檢測及參數(shù)估計問題,論文圍繞低空MIMO雷達理論模型、低空MIMO雷達檢測器設(shè)計及低空MIMO雷達參數(shù)估計等關(guān)鍵問題展開研究,主要工作概括如下:第一章:首先闡述了低空目標檢測及跟蹤研究背景和意義,介紹了目前低空目標檢測及跟蹤的研究現(xiàn)狀及MIMO雷達概念、分類以及其在目標檢測領(lǐng)域的應(yīng)用;歸納和總結(jié)了低空目標檢測若干關(guān)鍵技術(shù)問題。第二章:以目前廣泛采用Swerling目標模型為基礎(chǔ),研究MIMO雷達對低空Swerling目標的檢測性能。首先推導了考慮大氣折射和地球曲率的反射系數(shù);介紹了MIMO雷達低空多徑信號模型,推導了低空非起伏目標和起伏目標的檢測概率和虛警概率,并通過仿真實驗分析了MIMO雷達對低空Swerling目標模型的檢測性能。為了從理論上證明MIMO雷達在低空目標檢測的優(yōu)勢,第三章主要分析對比了MIMO雷達和相控陣雷達在低空目標檢測的性能。首先分別推導了MIMO雷達和相控陣雷達低空多徑信號模型;運用奈曼-皮爾遜(Neyman-Pearson)準則分別推導了MIMO雷達和相控陣雷達的低空檢測概率和虛警概率;最后以相對熵為準則,分別分析了MIMO雷達和相控陣雷達的系統(tǒng)設(shè)計問題。理論分析和實驗結(jié)果表明:對于低空目標檢測問題,MIMO雷達要優(yōu)于相控陣雷達,且MIMO雷達檢測性能還跟天線數(shù)目、目標高度有關(guān)。低空雷達背景雜波模型常采用復合高斯模型。第四章研究了基于復合高斯雜波模型的低空MIMO雷達檢測器設(shè)計問題。首先建立低空MIMO雷達多徑矢量信號模型;在此基礎(chǔ)上,設(shè)計了二次線性廣義似然比檢測器、廣義似然比檢測器和Rao檢測器三種檢測器,并分析三種檢測器的低空檢測性能。研究發(fā)現(xiàn),GLRT和Rao檢測器都具有恒虛警率特性(Constant False Alarm Rate,CFAR),二次線性廣義似然比檢測器檢測器的低空檢測性能要優(yōu)于廣義似然比檢測器和Rao檢測器,多徑效應(yīng)在低空檢測重要性;雷達天線和目標高度都對低空檢測性能有著顯著地影響。第五章:針對期望最大化(Expectation-Maximization,EM)算法收斂慢的問題,本章提出了基于參數(shù)擴展期望最大化(Parameter-Expanded ExpectationMaximization,PX-EM)的MIMO雷達低空運動目標參數(shù)估計方法。主要內(nèi)容包括:(1)推導了MIMO雷達低空運動目標多徑信號模型,為低空參數(shù)估計奠定了理論基礎(chǔ);(2)針對目標參數(shù)和雜波參數(shù)的聯(lián)合估計問題,提出了最大似然估計算法;(3)針對未知參數(shù),提出了基于PX-EM算法的最大似然估計算法;(4)分別推導了紋理分量服從伽馬分布和反伽馬分布的克拉美-羅下界。第六章:總結(jié)了全文工作,并提出了若干需要進一步研究的問題。綜上,論文以近年來深受關(guān)注的MIMO雷達為研究對象,在系統(tǒng)概念、理論模型、系統(tǒng)設(shè)計、檢測器設(shè)計及參數(shù)估計等方面進行了初步探索。本文的研究成果將進一步豐富MIMO雷達理論體系,對認識、理解低空目標檢測和參數(shù)估計都有一定的參考價值。
[Abstract]:Low altitude target detection and tracking is one of the four major threat to radar, failed to effectively solve so far. MTMR (Multi-Input Multi-Output MIMO) radar is of concern in recent years new radar.MIMO radar system with diversity gain in target detection, parameter estimation, target tracking, target recognition and anti-jamming is the traditional radar has obvious advantages. Based on the above understanding, MIMO radar can do to solve the low altitude target detection difficult approach. In recent years, domestic and foreign scholars on the MIMO radar in target detection, image recognition, parameter estimation was carried out extensive and in-depth research, but the estimation of low altitude target MIMO radar detection and parameter based on rarely involved. In order to solve the low altitude target detection and parameter estimation problem, the low altitude radar MIMO model, low MIMO and low M radar detector design Study on the key problems of IMO radar parameter estimation, the main works are summarized as follows: the first chapter: first elaborated the low altitude target detection and tracking research background and significance, introduces the current low altitude target detection and tracking the status quo and Research on MIMO radar concept, classification and its application in the field of target detection; and summarized some key problems low altitude target detection technology. The second chapter: the current widely used Swerling target model based on the detection performance of MIMO radar for low altitude target Swerling. Firstly, considering the reflection coefficient of atmospheric refraction and the curvature of the earth; the MIMO of low altitude radar multipath signal model, detection probability and false alarm probability is low and non fluctuating targets the ups and downs of target, and analyze the detection performance of MIMO radar for low altitude target Swerling model through simulation experiments. In order to MIMO from the theory of Shanghai Ming Lei In the low altitude target detection, the third chapter mainly analyzed the performance of MIMO radar and phased array radar in the low altitude target detection. Firstly, the MIMO radar and phased array radar low altitude multipath signal model are derived by Naiman; Pearson (Neyman-Pearson) criterion is derived MIMO radar and phased array radar low detection probability and false alarm probability at last; relative entropy as the criterion, analyzes system design problems of MIMO radar and phased array radar. Theoretical analysis and experimental results show that for the problem of low altitude target detection of MIMO radar is superior to the phased array radar, and the detection performance of MIMO radar with antenna number, target height. Low altitude radar clutter model is often used to composite the Gauss model. The fourth chapter studies the composite Gauss clutter model for low altitude radar detector design based on MIMO. Firstly, the establishment of low MIMO ray As the vector signal multipath model; on this basis, designed two linear generalized likelihood ratio detector, generalized likelihood ratio detector and the Rao detector three detectors, and analysis of low altitude detection performance of the three detectors. The study found that GLRT and Rao detectors have constant false alarm rate (Constant False Alarm Rate, CFAR). Two linear generalized likelihood ratio of low altitude detection performance of the detector detector is better than that of the generalized likelihood ratio detector and Rao detector, the multipath effect in the low altitude detection importance; radar antenna and the target height of low altitude detection performance has a significant influence. The fifth chapter: Based on the expectation maximization (Expectation-Maximization, EM) the problem of slow convergence of the algorithm. The chapter is put forward based on the expectation maximization (Parameter-Expanded expanded parameter ExpectationMaximization, PX-EM) estimation of low altitude targets MIMO radar parameter method. The contents include: (1) low altitude targets MIMO radar multipath signal model is derived, which laid a theoretical foundation for the parameter estimation of low altitude; (2) estimation of target parameters and clutter parameters, proposed a maximum likelihood estimation algorithm; (3) with unknown parameters, proposed a maximum likelihood estimation algorithm PX-EM algorithm based on the derived; (4) texture component to gamma distribution and inverse gamma distribution of the CramerRao bound. The sixth chapter summarizes the work, and puts forward some problems that need further research. To sum up, the MIMO radar nearly years has attracted much attention as the research object, in the system concept, theoretical model the system design, has carried on the preliminary exploration of detector design and parameter estimation. The results of this study will further enrich the theoretical system of MIMO radar, understanding, understanding of low altitude target detection and parameter estimation are certain Reference value.

【學位授予單位】：國防科學技術(shù)大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TN958

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本文編號：1757219