本文選題：雷達(dá)目標(biāo)識別 + 微運(yùn)動��； 參考：《西安電子科技大學(xué)》2014年博士論文

【摘要】：隨著目標(biāo)識別技術(shù)的快速發(fā)展,各種反探測、反識別的技術(shù)也獲得了快速發(fā)展,為目標(biāo)的探測與識別帶來了新的困難,同時也對目標(biāo)探測與識別提出了更高的技術(shù)要求,越來越要求對目標(biāo)細(xì)節(jié)的描述及運(yùn)動狀態(tài)的精細(xì)刻畫。雷達(dá)目標(biāo)微運(yùn)動產(chǎn)生的微多普勒特征包含著目標(biāo)的運(yùn)動和結(jié)構(gòu)信息,從中可提取出微動目標(biāo)固有的特性。自從雷達(dá)目標(biāo)微多普勒特征被發(fā)現(xiàn)以來,其在目標(biāo)探測、分類與識別領(lǐng)域的重要價值已經(jīng)引起了國內(nèi)外學(xué)術(shù)界和工程界的廣泛關(guān)注。因此,深入研究雷達(dá)目標(biāo)的微多普勒特征及其在軍事和民用領(lǐng)域的應(yīng)用具有重要的理論及應(yīng)用價值。本文主要圍繞雷達(dá)目標(biāo)的微運(yùn)動產(chǎn)生的微多普勒特征數(shù)學(xué)分析、微多普勒特征提取方法、微動信號分離及微多普勒特征在微動參數(shù)估計和目標(biāo)識別中的應(yīng)用等方面展開研究,論文主要工作有以下幾個方面:1.研究了微多普勒特征的產(chǎn)生原理,建立了加速、振動、旋轉(zhuǎn)、錐旋、擺動等典型微動模型,推導(dǎo)了其產(chǎn)生的微多普勒特征的數(shù)學(xué)表達(dá)式及其與微運(yùn)動參數(shù)之間的對應(yīng)關(guān)系;針對目標(biāo)微運(yùn)動特征的復(fù)雜性和差異性,以有旋翼和無旋翼目標(biāo)識別為研究背景,建立了具有平動、加速與振動運(yùn)動特征的復(fù)合運(yùn)動微動模型和具有平動、加速、振動及旋轉(zhuǎn)運(yùn)動特征的復(fù)合運(yùn)動微動模型,推導(dǎo)了兩種復(fù)合運(yùn)動產(chǎn)生的微多普勒特征及其與目標(biāo)結(jié)構(gòu)和微運(yùn)動參數(shù)的關(guān)系,比較了其微多普勒特征的差異性,為識別這兩類目標(biāo)奠定了理論基礎(chǔ)。2.針對微多普勒特征的提取問題,研究了從微動目標(biāo)雷達(dá)回波中提取微多普勒特征的常用方法,并分析了各自的優(yōu)缺點(diǎn),提出了使用重排平滑偽Wigner-Ville分布提取目標(biāo)微多普勒特征的方法,該方法能夠有效地提取微動信號的微多普勒特征;研究了運(yùn)動目標(biāo)的平動速度、加速度、雷達(dá)的載頻和雷達(dá)PRF對提取微多普勒特征的影響及相應(yīng)對策,為有效提取雷達(dá)目標(biāo)微多普勒特征提供了理論指導(dǎo)。3.提出了基于Radon變換的目標(biāo)主體信號與微動信號的分離方法,首先對回波信號進(jìn)行時頻變換,然后在時頻平面上通過Radon變換來分離目標(biāo)主體信號與微動信號,再通過逆Radon變換得到分離信號的時頻分布;針對常見微動信號表現(xiàn)為正弦調(diào)頻信號的特點(diǎn),提出了基于時頻分析和相關(guān)搜索法的正弦調(diào)頻信號的分離方法,首先在時頻域采用時頻分析的方法預(yù)估計信號的類別和相關(guān)參數(shù)范圍,進(jìn)而在時域通過相關(guān)法搜索參數(shù)對多分量正弦調(diào)頻信號進(jìn)行分離。4.提出了利用提取時頻分析矩陣頻率向最大值的峰值提取和最小二乘擬合直線相結(jié)合估計目標(biāo)微動參數(shù)的方法,通過該方法有效地估計了加速與振動目標(biāo)的加速度、振動頻率和振動幅度;估計了加速與旋轉(zhuǎn)目標(biāo)的加速度、旋轉(zhuǎn)角速度及旋轉(zhuǎn)半徑;在此基礎(chǔ)上,建立了線性旋轉(zhuǎn)剛體目標(biāo)的微動模型并分析了其產(chǎn)生的微多普勒特征,估計了線性旋轉(zhuǎn)剛體目標(biāo)的旋轉(zhuǎn)角速度及剛體長度;進(jìn)而,建立了直升機(jī)旋翼目標(biāo)的微動模型,分析了其產(chǎn)生的微多普勒特征,估計了直升機(jī)旋翼旋轉(zhuǎn)角速度、旋翼長度和旋翼葉片數(shù),為對目標(biāo)進(jìn)行精確識別奠定了基礎(chǔ)。5.針對真假彈頭的辨識問題,建立了錐體彈頭進(jìn)動、章動和誘餌目標(biāo)擺動的微動模型,分析了它們產(chǎn)生的微多普勒特征,比較了彈頭的進(jìn)動、章動和誘餌擺動所具有的不同的微多普勒特征,提出了依據(jù)微多普勒特征的差異性對真假彈頭進(jìn)行辨識的方法;針對輪式車和履車帶車輛的辨識問題,建立了輪式車和履帶車的微動模型,分析了輪式車和履車帶車輛產(chǎn)生的微多普勒特征及其差異性,提出了依據(jù)微多普勒特征的差異性對輪式車和履車帶車輛進(jìn)行辨識的方法。
[Abstract]:With the rapid development of target recognition technology, various anti detection and anti recognition technologies have also gained rapid development. It brings new difficulties for target detection and recognition. At the same time, it also puts forward higher technical requirements for target detection and recognition, and more and more demands for the description of target details and fine depiction of motion state. The micro Doppler features produced by the motion include the motion and structural information of the target, which can extract the inherent characteristics of the micro moving target. Since the detection of the radar target micro Doppler features, the important value in the field of target detection, classification and recognition has aroused wide attention from both the academic and Engineering circles at home and abroad. The micro Doppler characteristics and its application in military and civil fields are of important theoretical and practical value. This paper mainly focuses on the mathematical analysis of the micro Doppler characteristics produced by the micro motion of radar targets, the extraction method of micro Doppler features, the separation of micro signal and the micro Doppler feature in the estimation and the mesh of the micromotion parameters. The main work of this paper is as follows. The main work of this paper is as follows: 1. the principle of micro Doppler characteristics is studied, and the typical microdynamic models of acceleration, vibration, rotation, cone rotation and swing are established, and the mathematical expressions of the micro Doppler characteristics and the correspondence between the micro motion parameters and the corresponding relations are derived. With the complexity and difference of the feature of the target micro motion, the compound motion micromotion model with the characteristics of translational, acceleration and vibration motion is established, and the compound motion model with the characteristics of translational, acceleration, vibration and rotation motion is established. The microdynamics of two kinds of compound motion are derived. The characteristic of.2. and its relation to the target structure and the micro motion parameters, and compare the difference of their micro Doppler characteristics. In order to identify these two kinds of targets, it lays a theoretical foundation for the extraction of micro Doppler features, and studies the common methods of extracting the characteristics of micro Doppler from the echo of the moving target radar, and analyzes their respective advantages and disadvantages. The method of extracting the target micro Doppler features using the rearrangement smooth pseudo Wigner-Ville distribution is proposed. This method can effectively extract the micro Doppler characteristics of the moving signal, and study the influence of the moving speed of the moving target, the acceleration, the carrier frequency of the radar and the radar PRF on the extraction of the micro Doppler characteristics and the corresponding countermeasures. The radar target micro Doppler features provide theoretical guidance for.3.. The separation method based on Radon transform is proposed for the target main signal and the microdynamic signal. First, the time frequency conversion is carried out on the echo signal, then the target body signal and the fretting signal are separated by the Radon transform on the time frequency plane, and then the separated signal is obtained by inverse Radon transform. In view of the characteristics of the common fretting signal as sine frequency modulation signal, the separation method of sinusoidal frequency modulation signal based on time frequency analysis and correlation search method is proposed. First, the classification of the signal and the range of related parameters are preestimated by time-frequency analysis in time and frequency domain, and then the correlation method is used to search for more parameters in time domain. The component sinusoidal frequency modulation signal is separated by.4.. A method is proposed to estimate the microdynamic parameters of the target by extracting the peak value of the time frequency analysis matrix and the least square fitting line. The acceleration, the vibration frequency and the amplitude of the vibration are estimated effectively by this method, and the acceleration and rotation are estimated. The acceleration of the target, the rotational angular velocity and the rotation radius, and on this basis, the microdynamic model of the linear rotating rigid object is established and the micro Doppler characteristics are analyzed. The rotation angular velocity and the rigid body length of the linear rotating rigid object are estimated, and then the microdynamic model of the helicopter rotor target is established, and its production is analyzed. With the characteristics of micro Doppler, the rotational angular velocity of the helicopter rotor, the length of the rotor and the number of rotor blades are estimated. For the accurate recognition of the target, the identification of the true and false warhead is established by the accurate recognition of the target. The microdynamic model of the cone warhead precession, the nutation and the swinging of the decoy target is established, and the micro Doppler characteristics of the.5. are analyzed, and the comparison is made. The different micro Doppler characteristics of the precession of the warhead, the nutation and the bait swing, and the method of identifying the true and false warheads according to the difference of the characteristics of the micro Doppler. The fretting model of the wheeled vehicle and the caterpillar car is established for the identification of the wheeled vehicle and the track car, and the vehicle and the car belt vehicle are analyzed. Based on the characteristics of micro Doppler and their differences, a method of identifying wheeled vehicles and carriages with vehicles based on the difference of micro Doppler features is proposed.
【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

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

1 孫照強(qiáng);魯耀兵;李寶柱;;彈道目標(biāo)進(jìn)動特性的微多普勒研究與特征分析[J];航天電子對抗;2008年01期

2 劉進(jìn);馬梁;王雪松;王國玉;;微多普勒的參數(shù)化估計方法[J];信號處理;2009年11期

，

本文編號：1962000