【摘要】：本文主要研究強雜波或噪聲背景下雷達(dá)目標(biāo)檢測與分類問題。由于隱身飛機/艦艇、低空/超低空突防武器和綜合電子干擾在現(xiàn)代戰(zhàn)爭中的大規(guī)模應(yīng)用，雷達(dá)需要具有在強雜波和噪聲中檢測和分類目標(biāo)的能力。本文在雷達(dá)回波信號的聯(lián)合分布（時頻分布和時間-調(diào)頻率分布）和特征提取方面展開研究，并將研究成果應(yīng)用于海面微弱目標(biāo)檢測、空中機動距離擴展目標(biāo)檢測和空中直升機分類。 本文的研究成果可概括為以下四部分： 1，研究了海面微弱目標(biāo)檢測問題。分析了海面波浪的形成過程及結(jié)構(gòu)特點，由此得到海雜波的非平穩(wěn)特性。進而根據(jù)海雜波和目標(biāo)回波在時頻域的區(qū)別提出了基于時頻迭代分解的海面慢速微弱目標(biāo)檢測方法：基于特征值分解，我們首先提出快速信號合成方法（FSSM），F(xiàn)SSM可以從信號的維格納分布（WD）中更精確和快速地恢復(fù)出信號；然后，基于遮隔WD（MWD）和FSSM，提出信號迭代分解方法（IDM）；最后應(yīng)用IDM將海面回波分解成許多分量，并根據(jù)各分量的時頻聚集性從中找出目標(biāo)回波，實現(xiàn)目標(biāo)檢測。應(yīng)用實測海面回波驗證該檢測方法的結(jié)果表明其不僅能夠高效地檢測海面慢速微弱目標(biāo)還能夠顯示目標(biāo)的瞬時運動狀態(tài)。 2，研究了高斯白噪聲背景下空中機動距離擴展目標(biāo)檢測問題�；诟叻直胬走_(dá)（HRR）接收到的混頻器輸出，我們提出了三類距離擴展目標(biāo)檢測方法。(1)基于兩個相鄰混頻器輸出時頻分解特性的距離擴展目標(biāo)檢測方法：首先，基于奇異值分解我們提出一種信號合成方法，它可以從兩信號的互維格納分布（CWD）中合成兩個單位能量的信號，并且將兩信號的能量集中在兩個奇異值上；接著，提出了兩個相鄰混頻器輸出的互S-方法（CSM）。然后，將信號合成方法應(yīng)用于兩相鄰混頻器輸出的CSM，得到奇異值；最后，，根據(jù)所得奇異值的聚集性實現(xiàn)目標(biāo)檢測。應(yīng)用沒有經(jīng)過距離走動校正的雷達(dá)回波數(shù)據(jù)驗證所提檢測方法，結(jié)果表明所提方法的檢測性能優(yōu)于傳統(tǒng)方法且適用于高速運動目標(biāo)。另外，該方法具有恒虛警（CFAR）特性。(2)基于一個混頻器輸出的匹配信號的距離擴展目標(biāo)檢測方法：首先構(gòu)造混頻器輸出的匹配信號為頻率與混頻器輸出中目標(biāo)信號的最大頻率相同的正弦函數(shù)；然后定義一個混頻器輸出的匹配模糊函數(shù)（MAF）和改進匹配濾波器（MMF）；根據(jù)混頻器輸出在MAF和MMF中零多普勒/頻率的聚集性提出了兩種距離擴展目標(biāo)檢測方法，分別命名為MAF-D和MMF-D。該類檢測器利用一個回波因而可以檢測高速（包括平動速度和轉(zhuǎn)動速度）運動目標(biāo)。應(yīng)用實測數(shù)據(jù)的檢測結(jié)果表明該類方法的檢測性能優(yōu)于傳統(tǒng)的檢測器且對目標(biāo)姿態(tài)不敏感。(3)基于一個混頻器輸出的調(diào)頻率（FR）函數(shù)的距離擴展目標(biāo)檢測方法：首先根據(jù)三次相位函數(shù)（CPF）定義FR函數(shù)并確定應(yīng)用其分析離散線性調(diào)頻（LFM）信號時的FR范圍；然后根據(jù)回波信號在零FR處的聚集性實現(xiàn)目標(biāo)檢測。該方法可以檢測高速目標(biāo)。應(yīng)用于實測距離擴展目標(biāo)的檢測結(jié)果表明該方法優(yōu)于基于HRRP的檢測器。 3，針對高階多項式相位信號的參數(shù)估計問題，我們提出了一種高分辨時間-調(diào)頻率分布（TFRR），并分析了其在目標(biāo)檢測方面的潛在應(yīng)用。我們推導(dǎo)出該TFRR的分析表達(dá)式，并證明了其相對于CPF具有較高的分辨率。該TFRR可以用來分析兩個在時間-調(diào)頻率（TFR）域非�？拷男盘�。由于該TFRR是雙線性變換，所以當(dāng)兩信號的瞬時頻率（IF）信號相交或非�？拷鼤r會受到交叉項的困擾。為了抑制交叉項，我們通過引入一個FR窗提出了平滑TFRR（STFRR）。應(yīng)用STFRR分析噪聲背景下的高階多項式相位信號，結(jié)果表明STFRR具有檢測目標(biāo)的潛能。 4，研究了高脈沖重復(fù)頻率（PRF）雷達(dá)下直升機分類問題。分析了直升機主旋翼的微多普勒調(diào)制特征，針對回波信號積累時間是否大于兩“閃爍”之間間隔這兩種情況，我們提出了兩類直升機主旋翼參數(shù)估計方法，最終實現(xiàn)直升機分類。(1)針對回波信號積累時間大于兩“閃爍”之間間隔這種情況我們提出兩種直升機分類技術(shù)：第一種方法是匹配濾波器（MF）方法，包括時域匹配濾波器（TMF）和時頻域匹配濾波器（TFMF）；第二種方法為時頻遮隔模板（TFMs）方法。該類方法可以分類葉片數(shù)目不同但微多普勒參數(shù)相同的直升機。仿真結(jié)果表明它們對于直升機的姿態(tài)和微多普勒參數(shù)的估計誤差都具有魯棒性。(2)針對回波信號積累時間小于兩“閃爍”之間間隔這種情況我們提出了基于最小均方誤差（MMSE）的部分周期數(shù)據(jù)微多普勒參數(shù)估計方法：在MMSE準(zhǔn)則下應(yīng)用正弦信號擬合從時頻分布中提取出的旋翼葉片微多普勒信號，從而估計出葉片的轉(zhuǎn)速和半徑。仿真和實測數(shù)據(jù)的微多普勒參數(shù)估計結(jié)果都驗證了該方法的有效性與精確性。
[Abstract]:This paper mainly studies the detection and classification of radar targets under strong clutter or noise background. Due to the large-scale application of stealth aircraft / ship, low altitude / ultralow altitude penetration weapon and integrated electronic jamming in modern warfare, radar needs to have the ability to detect and classify the targets in strong clutter and noise. The joint distribution (time frequency distribution and time modulation frequency distribution) and feature extraction are studied, and the research results are applied to the detection of weak target in the sea, the target detection in air maneuver distance and the classification of helicopter in the air.
The research results of this paper can be summarized as follows:
1, the detection of weak target in the sea is studied. The formation process and structure characteristics of sea surface wave are analyzed, and the nonstationary characteristics of sea clutter are obtained. Based on the difference between sea clutter and target echo in time frequency domain, a slow weak target detection method based on time frequency iterative decomposition is proposed: Based on eigenvalue decomposition, we first First, the fast signal synthesis method (FSSM) is proposed, and FSSM can recover the signal more accurately and quickly from the Wigner distribution (WD) of the signal. Then, based on the WD (MWD) and FSSM, the signal iterative decomposition method (IDM) is proposed. At last, the sea surface echo is decomposed into many components with IDM, and the order of the time frequency aggregation of each component is found out. The target detection is realized by the target echo, and the result of the detection method using the measured sea surface echo shows that it can not only detect the slow and weak target of the sea surface, but also can display the instantaneous motion state of the target.
2, the problem of aerial mobile range expansion target detection under the background of Gauss white noise is studied. Based on the output of the mixer received by the high resolution radar (HRR), we propose three kinds of distance extended target detection methods. (1) a distance expansion target detection method based on the time frequency decomposition characteristics of two adjacent mixers: first, the singular value is based on the singular value. We propose a signal synthesis method that can synthesize two unit energy signals from the mutual Wigner distribution (CWD) of two signals and concentrate the energy of the two signal on two singular values. Then, the mutual S- method (CSM) for the output of two adjacent mixers is proposed. Then, the signal synthesis method is applied to the two adjacent mixers. The output CSM obtains the singular value; finally, the target detection is realized based on the aggregation of the singular value. The proposed detection method is applied without the radar echo data of the distance moving correction. The results show that the proposed method is superior to the traditional method and is suitable for the high-speed moving target. In addition, the method has the constant false alarm (CFAR). Characteristics. (2) a range expansion target detection method based on a matched signal of a mixer output: first, the matching signal of the mixer output is constructed as the sinusoidal function of the maximum frequency of the frequency and the target signal in the mixer output; then a matching fuzzy function (MAF) and an improved matching filter (MMF) are defined. According to the aggregation of mixer output in MAF and MMF, two range expansion target detection methods are proposed, named MAF-D and MMF-D., which can detect high speed (including translational speed and rotation speed) by using an echo. The detection performance of the method is superior to that of the traditional detector and is insensitive to the target attitude. (3) a range expansion target detection method based on the frequency modulation rate (FR) function of a mixer output: firstly, the FR function is defined according to the three phase function (CPF) and the FR range of the application for the analysis of the discrete linear frequency modulation (LFM) signal is determined; and then the echo signal is based on the echo signal. The target detection at zero FR is realized. The method can detect the high speed target. The detection results applied to the measured range expansion target show that the method is superior to the HRRP based detector.
3, in view of the parameter estimation of high order polynomial phase signals, we propose a high resolution time modulation frequency distribution (TFRR), and analyze its potential application in target detection. We deduce the analytical expression of the TFRR and prove that it has a higher resolution relative to the CPF. This TFRR can be used to analyze two in time. The TFR domain is very close to the signal. Since the TFRR is a bilinear transformation, it is troubled when the instantaneous frequency (IF) signal of the two signal is intersected or very close. In order to suppress the cross term, we introduce a FR window to put forward a smooth TFRR (STFRR). The high order polynomial in the noise background of the STFRR is applied to the STFRR analysis. Phase signals show that STFRR has the potential to detect targets.
4, the problem of helicopter classification under high pulse repetition frequency (PRF) radar is studied. The characteristics of the micro Doppler modulation of the helicopter main rotor are analyzed. For the two cases of whether the echo signal accumulation time is more than two "scintillation", we propose a method to estimate the parameters of the main rotor wing parameters of the two types of helicopters, and finally realize the helicopter classification. (1) Two kinds of helicopter classification techniques are proposed for the case of echo signal accumulation time greater than two "scintillation". The first method is a matched filter (MF) method, including time domain matched filter (TMF) and time domain matched filter (TFMF); the second square method is a time frequency blocking template (TFMs) method. This method can be divided into two methods. The helicopter with different number of blades but with the same micro Doppler parameters. The simulation results show that they are robust to the estimation error of the helicopter's attitude and the micro Doppler parameters. (2) we propose a partial week based on the minimum mean square error (MMSE) for the interval between the echo signal accumulation time less than two "scintillation". The method of estimating the phase data micro Doppler parameter: using the sinusoidal signal to fit the rotor blade micro Doppler signal extracted from the time frequency distribution under the MMSE criterion, the speed and radius of the blade are estimated. The results of the micro Doppler parameter estimation of the simulated and measured data all verify the validity and accuracy of the method.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN957.51

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