發(fā)布時(shí)間：2018-02-13 00:50

  本文關(guān)鍵詞： 到達(dá)時(shí)差 到達(dá)時(shí)間 多維尺度分析 TDOA/FDOA聯(lián)合定位 克拉美-羅下界　出處：《西安電子科技大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：無(wú)論是在民用系統(tǒng)還是在軍用系統(tǒng)中,對(duì)目標(biāo)的精確定位,都有著非常重要的作用。有源定位、無(wú)源定位以及自定位是目前常見(jiàn)的三種目標(biāo)定位問(wèn)題。其中,無(wú)源定位是在對(duì)目標(biāo)不發(fā)射電磁波的條件下,通過(guò)測(cè)量輻射源諸如通信發(fā)射機(jī)、雷達(dá)等的電磁波,來(lái)確定目標(biāo)的位置信息。其定位方式?jīng)Q定了無(wú)源定位具有隱蔽性強(qiáng)、不易被察覺(jué)的優(yōu)點(diǎn),因而使其成為現(xiàn)代一體化防空系統(tǒng)、遠(yuǎn)程預(yù)警系統(tǒng)以及機(jī)載對(duì)敵等方面的重要組成部分,在電子對(duì)抗領(lǐng)域發(fā)揮著與日俱增的關(guān)鍵作用。目前,在對(duì)目標(biāo)的定位問(wèn)題中,常用的定位參數(shù)主要有到達(dá)時(shí)差(TDOA)、到達(dá)時(shí)間(TOA)、到達(dá)角(AOA)以及它們的混合參數(shù)等。一方面,本文分別研究并分析了基于TDOA信息的靜止目標(biāo)和基于TDOA/FDOA信息的運(yùn)動(dòng)目標(biāo)的定位算法。對(duì)于靜止目標(biāo),主要介紹了幾種經(jīng)典的TDOA無(wú)源定位算法,并分析了各自的定位性能;對(duì)于運(yùn)動(dòng)目標(biāo),主要研究了幾種常用的基于TDOA測(cè)量值和FDOA測(cè)量值的聯(lián)合定位算法。另一方面,本文還介紹了一種基于TOA測(cè)量值的MDS(multi-dimensional scaling)定位算法,并對(duì)該算法進(jìn)行改進(jìn),提出了一種新的利用多個(gè)時(shí)刻TOA測(cè)量值的MDS定位算法,大大提高了定位精度。本文的所有工作主要著眼于下述幾個(gè)方面:(1)第一章首先簡(jiǎn)要敘述了幾種常見(jiàn)的目標(biāo)定位問(wèn)題,尤其是無(wú)源定位的研究背景、研究意義及其發(fā)展歷史和研究現(xiàn)狀。隨后重點(diǎn)介紹了用于定位的幾種主要方法及其數(shù)學(xué)模型,同時(shí)研究了對(duì)于各種定位算法的常用的定位精度評(píng)價(jià)指標(biāo)。(2)第二章首先介紹了TDOA定位算法的基本原理以及估計(jì)TDOA值的主要方法,然后重點(diǎn)介紹了3種典型的TDOA定位算法,包括加權(quán)最小二乘(WLS)算法、泰勒級(jí)數(shù)法以及Chan算法,并分別分析比較了各算法的優(yōu)缺點(diǎn)及其定位性能。(3)第三章首先介紹了一種近些年提出的多維尺度分析(MDS)算法以及它在TOA定位問(wèn)題中的應(yīng)用,隨后在此基礎(chǔ)上對(duì)該算法進(jìn)行改進(jìn),針對(duì)多運(yùn)動(dòng)基站的TOA定位模型,提出了一種新的利用多個(gè)時(shí)刻TOA測(cè)量值的MDS定位算法,該算法考慮了二階誤差項(xiàng)的影響,在傳統(tǒng)MDS算法的基礎(chǔ)上利用了多個(gè)時(shí)刻的基站位置信息和TOA測(cè)量信息,進(jìn)一步提高了定位精度。(4)第四章主要研究了針對(duì)運(yùn)動(dòng)目標(biāo)的定位問(wèn)題,介紹了幾種常用的基于TDOA測(cè)量值以及FDOA測(cè)量值的聯(lián)合定位算法,包括總體最小二乘(TLS)算法、泰勒級(jí)數(shù)法以及兩步最小二乘算法,并分析比較了它們各自對(duì)目標(biāo)位置和速度的估計(jì)性能。
[Abstract]:In both civil and military systems, the precise positioning of targets plays a very important role. Active location, passive location and self-positioning are three common target positioning problems. Passive location is to determine the location information of the target by measuring the electromagnetic waves of emitter such as communication transmitter, radar and so on under the condition that no electromagnetic wave is emitted to the target. Its undetectable advantages make it an important component of modern integrated air defense systems, long-range early warning systems and airborne enemies, playing an increasingly critical role in the field of electronic countermeasures. In the problem of target location, the commonly used location parameters are time difference of arrival (TDOA), arrival time (TOAA), arrival angle (AOAA) and their mixed parameters. In this paper, the static target location algorithm based on TDOA information and the moving target location algorithm based on TDOA/FDOA information are studied and analyzed respectively. For the static target, several classical TDOA passive localization algorithms are mainly introduced, and their localization performance is analyzed. For moving target, several commonly used joint localization algorithms based on TDOA measurement and FDOA measurement are studied. On the other hand, a MDS(multi-dimensional scaling algorithm based on TOA measurement is introduced, and the algorithm is improved. In this paper, a new MDS localization algorithm using TOA measurements at multiple times is proposed, which greatly improves the positioning accuracy. The first chapter focuses on the following aspects: in Chapter 1, several common target localization problems are briefly described. In particular, the research background, research significance, development history and present situation of passive location are introduced. Then, several main methods and their mathematical models for location are introduced. The second chapter introduces the basic principle of TDOA localization algorithm and the main methods of estimating TDOA value, and then introduces three typical TDOA localization algorithms. Including weighted least squares (WLS) algorithm, Taylor series method and Chan algorithm, The advantages and disadvantages of each algorithm and its localization performance are analyzed and compared respectively. In chapter 3, a multi-dimensional scale analysis (MDS) algorithm proposed in recent years and its application in TOA localization are introduced, and then the algorithm is improved. Based on the TOA location model of multi-moving base stations, a new MDS localization algorithm based on multi-time TOA measurements is proposed, which takes into account the effect of second-order error terms. Based on the traditional MDS algorithm, the position information of the base station and the TOA measurement information at several times are used to further improve the positioning accuracy. Chapter 4th focuses on the localization of moving targets. This paper introduces several common joint localization algorithms based on TDOA measurements and FDOA measurements, including the total least squares algorithm, the Taylor series method and the two-step least squares algorithm. The performance of their estimation of target position and velocity is analyzed and compared.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN95

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