基于微多普勒特征的目標(biāo)分類方法研究
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資料類別
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電子電工畢業(yè)論文(設(shè)計) |
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課程(專業(yè))
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信號與信息處理 |
關(guān)鍵詞
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目標(biāo)分類|微多普勒 |
適用年級
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研究生 |
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普通會員 |
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2011-08-11 10:38:00 |
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碩士學(xué)位論文 基于微多普勒特征的目標(biāo)分類方法研究,正文共57頁。
【摘要】 近年來,微動特性在雷達(dá)目標(biāo)探測與識別中受到廣泛關(guān)注。微動是指雷達(dá)目標(biāo)除質(zhì)心平動以外的小幅振動、轉(zhuǎn)動和其他高階運動,由微動產(chǎn)生的多普勒頻率為微多普勒頻率,不同的微運動會產(chǎn)生不同的微多普勒,因此,基于目標(biāo)微動差異提取的相應(yīng)微多普勒特征可以用于雷達(dá)目標(biāo)識別。本文主要研究了飛機和彈頭兩種目標(biāo)的微動特性,并在微動基礎(chǔ)上,提取特征進(jìn)行識別分類。具體工作概括如下:論文首先介紹了微多普勒和微動的相關(guān)概念,并簡要說明了空中飛機目標(biāo)分類和導(dǎo)彈目標(biāo)分類的相關(guān)研究背景。論文詳細(xì)說明了基于微多普勒的直升機、螺旋槳飛機和噴氣式飛機分類相關(guān)問題。先建立旋翼的參數(shù)模型,在此基礎(chǔ)上分析微動對旋轉(zhuǎn)部件回波的調(diào)制作用;然后找到三類飛機微動特征差異,提取分類特征進(jìn)行識別,并驗證特征的有效性。論文還研究了彈頭目標(biāo)的識別問題。首先建立彈頭微動模型,推導(dǎo)了不同微運動下的微多普勒形式,利用時頻分析可以看到彈頭和誘餌微動特征的差異,并分別根據(jù)時頻分布及回波的傅里葉譜提取特征,以區(qū)分真假彈頭。
【Abstract】 Recently, micro-motion, as a significant characteristic in radar target detection andrecognition, has incurred abroad attentions. The radar target may have small vibrations,rotations or other high-order motions in addition to the center of mass, which is calledmicro-motion. The Doppler frequency produced by micro-motion is calledmicro-Doppler frequency. Since different micro-motions can produce differentmicro-Doppler, the corresponding micro-Doppler signatures extracted from differentmicro-motions, can be applied in radar target recognition.This dissertation mainly focuses on making an analysis of the micro-motions ofairplane and warhead, and extracting features based on them to distinguish differentclasses of targets. The main contents are as follows:Firstly, we introduce the conceptions of micro-Doppler and micro-motion, and givebrief reviews of the research background of airplane and warhead target classification.The dissertation then illuminates the problems of the classification of helicopter,propeller-driven aircraft and jet plane in detail. The parametric models of windstick areproposed, then, the modulations of the returns are analyzed. Finally, the differences ofmicro-motion signatures of the three kinds of plane are found. The signatures areextracted and used to classify the different airplane targets, with validated by simulateddata.We also do the research on the classification of warhead targets. Firstly, themicro-motion model is built. The forms of micro-Doppler in different micro-motionsare deduced. Then the differences of the micro-Doppler signatures of warhead anddecoy can be extracted via time-frequency analysis. Finally, the signatures are extractedbased on time-frequency analysis and the Fourier spectrum of echoes, which can beused to discriminate whether a warhead is true or false.
【關(guān)鍵詞】 目標(biāo)分類; 微動; 微多普勒; 噴氣引擎調(diào)制特性; 彈道導(dǎo)彈; 微動模型;
【Key words】 Target classification; micro-motion; micro-Doppler; JEM(Jet Engine Modulation)features; ballistic missile; micro-motion model;
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