本文選題：雷達(dá)傳感器網(wǎng)絡(luò) + 多目標(biāo)分辨　； 參考：《電子科技大學(xué)》2014年碩士論文

【摘要】：雷達(dá)傳感器網(wǎng)絡(luò)(Radar Sensor Network,RSN)是由多個(gè)雷達(dá)傳感器(Radar Sensor,RS)組合而成,其模式可分為分布式RSN和集中式RSN系統(tǒng),由于相對(duì)集中式,分布式具有工程簡(jiǎn)單、系統(tǒng)靈敏度高以及遮蔽效果較小等諸多優(yōu)點(diǎn),使其在軍事以及交通等眾多領(lǐng)域,引起了足夠的重視,其未來(lái)應(yīng)用前景也是非常值得期待的。多目標(biāo)分辨檢測(cè)能力是RSN的綜合體現(xiàn)之一,直接關(guān)系到RSN系統(tǒng)靈敏度、準(zhǔn)確度等多個(gè)重要工作指標(biāo),然而現(xiàn)有RSN系統(tǒng)中少有從RSN實(shí)際分布情況及發(fā)射波分辨角度來(lái)考慮RSN的多目標(biāo)分辨問(wèn)題。因此,針對(duì)RSN的多目標(biāo)分辨,本文工作主要包括:1.本文首先介紹了雷達(dá)信號(hào)處理系統(tǒng)中所需要的基礎(chǔ)知識(shí),包括脈沖壓縮、匹配濾波、不同波形的介紹及分析等;為了研究RSN中波形的多目標(biāo)分辨,對(duì)每種信號(hào)的模糊函數(shù)進(jìn)行分析和研究;分析RSN的信道特性,考慮信道衰落與噪聲影響,建立RSN信道模型;介紹RSN信息融合的方法及理論,選擇合適的融合方式。2.為研究RSN的多目標(biāo)分辨問(wèn)題,建立RSN分析模型,研究其多目標(biāo)分辨情況。該模型考慮到雷達(dá)的發(fā)射波束(Beam),根據(jù)分布式RSN的工作特點(diǎn),結(jié)合協(xié)同工作狀態(tài)的RSs,給出RSN的多目標(biāo)分辨條件,結(jié)果證明對(duì)于相同目標(biāo)的情況,RSN具有更多的觀測(cè)方位和角度,其系統(tǒng)的多目標(biāo)分辨狀態(tài)不單單是相對(duì)獨(dú)立的RSs的集合,其分辨行性能要比單個(gè)RS優(yōu)越很多。此外給定三種不同形式的雷達(dá)發(fā)射信號(hào),分別對(duì)它們的多目標(biāo)分辨能力進(jìn)行了研究。3.建立RSN的多目標(biāo)分辨仿真模型,在Path-loss及高斯白噪聲的環(huán)境下,RSN融合中心利用最大似然比(LR)的判決準(zhǔn)則,對(duì)RSN模型的系統(tǒng)檢測(cè)和分辨性能做了綜合仿真和對(duì)比,并對(duì)三種波形的多目標(biāo)檢測(cè)分辨能力進(jìn)行了對(duì)比,并給出仿真結(jié)果;結(jié)果中顯示雷達(dá)檢測(cè)性能分別與信噪比SNR、RS個(gè)數(shù)以及目標(biāo)個(gè)數(shù)的影響關(guān)系,LFM信號(hào)的檢測(cè)分辨能力最好。4.建立一種多目標(biāo)高距離分辨的RSN模型,分析RSN和目標(biāo)角度與位置的幾何關(guān)系,使用LFM信號(hào),通過(guò)對(duì)信號(hào)模糊函數(shù)的推導(dǎo),給出該模型下的多目標(biāo)時(shí)域(即距離)分辨條件,仿真結(jié)果展示該模型的多目標(biāo)分辨情況,并且對(duì)比了不同雷達(dá)和目標(biāo)情況下該模型多目標(biāo)分辨的結(jié)果。
[Abstract]:Radar Sensor Network (RSNN) is composed of several radar sensors (Radar Sensor RSs). Its modes can be divided into distributed RSN and centralized RSN systems. Because of its high sensitivity and low shielding effect, the system has attracted enough attention in many fields, such as military and traffic, and its future application prospect is also worth looking forward to. The ability of multi-target resolution detection is one of the comprehensive embodiment of RSN, which is directly related to the sensitivity and accuracy of RSN system. However, in existing RSN systems, the multi-target resolution problem of RSN is rarely considered from the actual distribution of RSN and the angle of emission wave resolution. Therefore, for the multiple target resolution of RSN, the work in this paper mainly includes: 1. This paper first introduces the basic knowledge needed in radar signal processing system, including pulse compression, matched filtering, introduction and analysis of different waveforms, etc. Analyze and study the ambiguity function of each signal, analyze the channel characteristics of RSN, consider the influence of channel fading and noise, establish the RSN channel model, introduce the method and theory of RSN information fusion, choose the appropriate fusion mode. 2. In order to study the multi-target resolution problem of RSN, a RSN analysis model is established and its multi-target resolution is studied. In this model, considering the beam-beam of radar, according to the working characteristics of distributed RSN, combined with RSsof cooperative working state, the multi-target resolution condition of RSN is given. The results show that RSN has more observation azimuth and angle for the same target. The multi-target resolution state of the system is not only the set of the relative independent RSs, but also the performance of the row resolution is much better than that of the single RS. In addition, given three different types of radar transmit signals, their multi-target resolution is studied respectively. The multi-target resolution simulation model of RSN is established. In the environment of Path-loss and Gao Si white noise, the system detection and resolution performance of RSN model is simulated and compared by using the maximum likelihood ratio (LRR) criterion. The detection and resolution ability of the three kinds of waveforms is compared and the simulation results show that the detection performance of radar depends on the number of SNR SNR RS and the number of targets respectively. The detection and resolution ability of LFM signal is the best. 4. A high range resolution RSN model with multiple targets is established, and the geometric relationship between RSN and target angle and position is analyzed. By using LFM signal, the time domain (distance) resolution condition of multiple targets is given by deducing the ambiguity function of the signal. The simulation results show the multi-target resolution of the model, and the results of multi-target resolution under different radar and target conditions are compared.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN957.51

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 盛建鋒;相位編碼雷達(dá)信號(hào)處理及其性能分析[D];南京理工大學(xué);2004年

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本文編號(hào)：1999358