發(fā)布時(shí)間：2018-05-15 10:29

  本文選題：到達(dá)時(shí)間 + 到達(dá)時(shí)間差��； 參考：《國(guó)防科學(xué)技術(shù)大學(xué)》2016年博士論文

【摘要】：利用運(yùn)動(dòng)觀測(cè)站獲取非合作輻射源位置信息的無源定位技術(shù),在軍用和民用領(lǐng)域有著廣泛的應(yīng)用�，F(xiàn)代無源定位系統(tǒng)正向著高精度、網(wǎng)絡(luò)化的方向發(fā)展,試圖使用最小的載荷代價(jià)對(duì)輻射源實(shí)現(xiàn)高精度定位�；谛盘�(hào)到達(dá)時(shí)間(Time of Arrival,TOA)和到達(dá)時(shí)間差(Time Difference of Arrival,TDOA)等時(shí)域觀測(cè)的定位體制,理論上單個(gè)觀測(cè)站僅需要單通道接收就可完成TOA或者TDOA的測(cè)量,對(duì)輻射源信號(hào)的調(diào)制類型的適應(yīng)能力強(qiáng),可最大限度地降低定位系統(tǒng)對(duì)載荷的要求,是高精度無源定位系統(tǒng)的首選定位體制。圍繞運(yùn)動(dòng)觀測(cè)站測(cè)時(shí)定位問題,本文針對(duì)單個(gè)運(yùn)動(dòng)觀測(cè)站和多個(gè)觀測(cè)站基于時(shí)域量測(cè)對(duì)非合作輻射源定位的定位原理,定位方法和性能分析等展開研究,主要研究?jī)?nèi)容包括:第二章研究了單個(gè)和多個(gè)運(yùn)動(dòng)觀測(cè)站測(cè)時(shí)無源定位模型。首先分析了利用運(yùn)動(dòng)單站或者運(yùn)動(dòng)多站無法同時(shí)檢測(cè)信號(hào)的非共視條件下,對(duì)于非合作輻射源基于TOA定位,需要輻射源信號(hào)發(fā)射具有周期特性。然后基于輻射源的周期特性建立了運(yùn)動(dòng)單站TOA定位模型,同時(shí)分析了雷達(dá)及通信輻射源內(nèi)蘊(yùn)的輻射源周期特性,最后分析了基于該模型定位的可觀測(cè)性�；谳椛湓吹闹芷谔匦越⒘藘煞N運(yùn)動(dòng)多站非共視TOA定位模型包括:以多個(gè)站各自測(cè)量的TOA作為時(shí)間基準(zhǔn)的多時(shí)間基準(zhǔn)異步TOA模型,和對(duì)所有TOA量測(cè)建立統(tǒng)一時(shí)間基準(zhǔn)的統(tǒng)一時(shí)間基準(zhǔn)異步TOA定位模型,分析了兩種模型的可觀測(cè)性。并分析了統(tǒng)一時(shí)間基準(zhǔn)異步TOA定位模型,站間距較大產(chǎn)生的模型參數(shù)辨識(shí)模糊問題。第三章研究了基于周期特性的運(yùn)動(dòng)單站TOA定位問題,在給定表征TOA結(jié)構(gòu)信息的模型參數(shù)條件下,推導(dǎo)了運(yùn)動(dòng)單站TOA定位的條件克拉美勞下限(Conditional Cramer-rao Lower Bound,C_CRLB)。從聯(lián)合估計(jì)目標(biāo)位置及周期的角度出發(fā),提出了基于高斯牛頓(Gaussian Newton,GN)迭代的目標(biāo)位置及周期聯(lián)合估計(jì)的批處理方法以及雙卡爾曼濾波(Kalman Filter,KF)結(jié)合高斯混合(Gaussian Mixture,GM)技術(shù)的聯(lián)合濾波方法,兩種方法在噪聲較小時(shí),可達(dá)到聯(lián)合估計(jì)的C_CRLB。第四章研究了基于周期特性的運(yùn)動(dòng)多站非共視條件下異步TOA定位問題。針對(duì)多時(shí)間基準(zhǔn)的運(yùn)動(dòng)多站非共視異步TOA定位問題,提出了列文伯格-馬奎特(Leverberg-Marquardt,LM)迭代方法,該定位方法在定位的同時(shí)可利用多站的TOA觀測(cè)實(shí)現(xiàn)周期的高精度估計(jì)。針對(duì)統(tǒng)一時(shí)間基準(zhǔn)的運(yùn)動(dòng)多站非共視異步TOA定位問題,充分考慮了站間距過大帶來的模型參數(shù)辨識(shí)模糊問題,考慮將目標(biāo)位置空間網(wǎng)格化,從提高周期估計(jì)的角度,提出了基于多觀測(cè)站TOA量測(cè)序列時(shí)延補(bǔ)償?shù)幕旌吓判蚬烙?jì)法(Time Delay Compensated Order,TDCO);從聯(lián)合估計(jì)目標(biāo)和周期的角度出發(fā),提出了基于網(wǎng)格劃分的多起始LM迭代(Grid-based Multiple Intialization LM,GB-LM);從運(yùn)算量考慮角度考慮,提出了結(jié)合粒子群優(yōu)化(Particle Swarm Optimization,PSO)及LM迭代(PSO-based LM,PSO-LM)等三種統(tǒng)一時(shí)間基準(zhǔn)的異步TOA定位方法。三種方法都可實(shí)現(xiàn)對(duì)目標(biāo)位置和周期的高精度估計(jì)。第五章研究了運(yùn)動(dòng)多站共視條件下TDOA定位解算方法。針對(duì)傳統(tǒng)迭代方法運(yùn)算量大存在收斂問題以及解析方法噪聲門限高的缺陷,在分析了著名的兩步最小二乘方法性能受限原因的基礎(chǔ)上,提出了基于定位誤差修正的TDOA解析定位方法,從理論上證明了該定位解算方法的統(tǒng)計(jì)有效性,并對(duì)該解析方法作了理論偏差分析。在分析了兩步最小二乘定位方法在觀測(cè)器誤差條件下的理論偏差的基礎(chǔ)上,將該解析定位方法推廣至有傳感器位置誤差條件下的TDOA定位、TDOA/TDOA變化率定位問題中,表明該解析定位方法具有良好的拓展性,通過仿真對(duì)比了多種TDOA定位方法和本文方法的定位性能,驗(yàn)證了該解析定位方法的有效性。
[Abstract]:The passive location technology using the motion observation station to obtain the location information of non cooperative radiant sources is widely used in military and civil fields. The modern passive location system is developing in the direction of high precision and network, trying to use the minimum load cost to locate the radiation source with high precision. Based on the signal arrival time (Time of Arriva) L, TOA) and time difference (Time Difference of Arrival, TDOA) and other time-domain observation positioning systems. In theory, a single observation station only needs a single channel receiving to complete the measurement of TOA or TDOA, and is adaptable to the modulation type of the source signal, and can minimize the requirement of the positioning system to the load. It is a high precision passive determination. This paper focuses on the positioning principle, positioning method and performance analysis of a single motion observation station and multiple observation stations based on the time domain measurement. The main research contents include: the second chapter studies the single and multiple motion observation stations. The passive location model of time measurement is made. Firstly, the periodic characteristics of the radiant source signal are needed for the non cooperative radiant source based on the non co visual condition which can not be detected at the same time by the single station or the moving multi station. Then the TOA location model of the single station is established based on the periodic characteristics of the radiation source, and the TOA is also analyzed. Finally, the observability based on this model is analyzed. Based on the periodic characteristics of the radiant source, two kinds of multi station non conforming TOA positioning models are established, including the multi time datum asynchronous TOA model with the TOA as the time benchmark, and the construction of all TOA measurements. The unified time benchmarking asynchronous TOA positioning model is established, and the observability of the two models is analyzed. The unified time reference asynchronous TOA positioning model and the fuzzy problem of model parameter identification produced by the large station spacing are analyzed. The third chapter studies the TOA positioning problem of the single station based on the periodic characteristics, and is given a representation of the structure of the TOA structure. Under the model parameters of information, the conditional cramamore lower limit (Conditional Cramer-rao Lower Bound, C_CRLB) for the TOA positioning of a single station is derived. From the angle of joint estimation of the position and period of the target, a batch processing method based on the Gauss Newton (Gaussian Newton, GN) iteration of the target location and periodic joint estimation is proposed. Kalman Filter (Kalman Filter, KF) combined with the joint filtering method of Gauss mixing (Gaussian Mixture, GM) technology, two methods can reach joint estimation in the C_CRLB. fourth chapter, which can reach joint estimation in the lower noise, and study the problem of different step TOA positioning under the multi station non conforming condition based on periodic characteristics. In view of the asynchronous TOA positioning problem, a Lewen Berg Marquardt (Leverberg-Marquardt, LM) iterative method is proposed. The positioning method can be used to achieve high precision estimation of the cycle by using multi station TOA observations. In view of the uncommon asynchronous TOA fixed position problem of the unified time benchmark for moving multi station non co visual asynchronous TOA, the model brought about by the oversize of the station spacing is fully considered. The problem of parameter identification is fuzzy. Considering the grid of target location, a mixed sort estimation method (Time Delay Compensated Order, TDCO) based on the time delay compensation of multi observation station TOA measurement sequence is proposed from the angle of improving the period estimation. From the angle of joint estimation of target and period, the multiple starting LM superposition based on grid partition is proposed. Grid-based Multiple Intialization LM (GB-LM); from the angle of calculation, three unified time benchmarking methods are proposed, which combine particle swarm optimization (Particle Swarm Optimization, PSO) and LM iterations (PSO-based LM). The three methods can all achieve high precision estimation of the position and cycle of the target. Fifth In this paper, the method of TDOA location calculation under the condition of multi station common sight is studied. In view of the shortcomings of the traditional iterative method with large amount of convergence and the high noise threshold of the analytical method, based on the analysis of the reasons for the performance limitation of the famous two step least squares method, a TDOA analytical positioning method based on the correction of location error is proposed. The statistical validity of the method is proved theoretically and the theoretical deviation of the analytical method is analyzed. On the basis of the analysis of the theoretical deviation of the two step least squares location method under the observer error condition, the analytic positioning method is extended to the TDOA location under the condition of the sensor position error and the TDOA/TDOA change rate. The location problem shows that the analytical location method has good expansibility. The localization performance of various TDOA positioning methods and this method is compared through simulation, and the effectiveness of the analytical location method is verified.

【學(xué)位授予單位】：國(guó)防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TN95
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本文編號(hào)：1892089