【摘要】：在車聯(lián)網(wǎng)定位中,GPS(Global Positioning System)信號(hào)長(zhǎng)時(shí)間較差甚至中斷會(huì)導(dǎo)致GPS定位結(jié)果不可靠甚至不可用,無(wú)法為相對(duì)定位算法提供可靠的精確初始坐標(biāo).針對(duì)這一問(wèn)題,該文對(duì)車輛相對(duì)位置坐標(biāo)估計(jì)方法展開(kāi)研究,結(jié)合TOA(Time of Arrival)測(cè)距技術(shù),將相對(duì)位置坐標(biāo)估計(jì)問(wèn)題轉(zhuǎn)化為非線性規(guī)劃問(wèn)題.為減小非線性規(guī)劃問(wèn)題中初始坐標(biāo)對(duì)算法結(jié)果的影響,將外部罰函數(shù)法與Powell算法結(jié)合,利用外部罰函數(shù)法"能夠從非可行解出發(fā)逐步逼近可行域"的特點(diǎn)優(yōu)化最優(yōu)化方法,解決算法對(duì)初始坐標(biāo)的敏感特性;利用Powell算法能夠"逼近局部最優(yōu)解"的特點(diǎn)作為最優(yōu)化求解方法,用于求解目標(biāo)函數(shù)最優(yōu)解.提出一種不依賴于精確初始坐標(biāo)的相對(duì)定位(Exact Initial Coordinate Free Relative Localization,EICFRL)算法,實(shí)現(xiàn)車聯(lián)網(wǎng)高精度相對(duì)定位.在算法驗(yàn)證中,該文采用兩種TOA節(jié)點(diǎn)部署方案,分別為單點(diǎn)部署方案和基于幾何約束的多點(diǎn)部署方案.在多點(diǎn)部署方案中,利用車輛固有形狀屬性,形成基于車型的幾何約束,增加非線性規(guī)劃問(wèn)題可行域限制.為驗(yàn)證該文算法可行性及有效性,該文在仿真實(shí)驗(yàn)中設(shè)置不同測(cè)距誤差、連通性、車輛數(shù)目等條件,并在實(shí)際環(huán)境中實(shí)驗(yàn)驗(yàn)證,將該算法結(jié)果與Powell算法、LM(Levenberg-Marquard)算法、CRLB(Cramer-Rao Lower Bound)進(jìn)行對(duì)比.實(shí)驗(yàn)結(jié)果顯示,該文算法定位精度提高超過(guò)50%.當(dāng)使用多點(diǎn)部署方案時(shí),算法定位誤差進(jìn)一步減小約為30%(仿真環(huán)境)和23%(實(shí)測(cè)環(huán)境).
[Abstract]:Long time poor or even interrupted (Global Positioning System) signals in networked vehicle positioning may lead to unreliable or even unusable GPS positioning results, which can not provide reliable initial coordinates for relative positioning algorithms. In order to solve this problem, this paper studies the method of vehicle relative position coordinate estimation. Combining with TOA (Time of Arrival) ranging technology, the problem of relative position coordinate estimation is transformed into a nonlinear programming problem. In order to reduce the influence of initial coordinates on the results of nonlinear programming problems, the external penalty function method is combined with the Powell algorithm to optimize the optimization method using the characteristic that the external penalty function method "can approach the feasible region step by step from the infeasible solution". The sensitivity of the algorithm to the initial coordinates is solved, and the Powell algorithm is used to solve the optimal solution of the objective function by making use of the characteristic that the local optimal solution can be approximated by the Powell algorithm. An algorithm of relative positioning (Exact Initial Coordinate Free Relative localization EICFRL, which does not depend on the exact initial coordinates, is proposed to realize the high precision relative positioning in the vehicle network. In the algorithm verification, two kinds of TOA node deployment schemes are adopted, one is single-point deployment scheme and the other is multi-point deployment scheme based on geometric constraints. In the multi-point deployment scheme, the inherent shape attributes of the vehicle are used to form the geometric constraints based on the vehicle model, which increases the limitation of the feasible region of the nonlinear programming problem. In order to verify the feasibility and effectiveness of the proposed algorithm, different ranging errors, connectivity and vehicle number are set up in the simulation experiment. The results of the algorithm are compared with that of the Powell algorithm, LM (Levenberg-Marquard) algorithm (Cramer-Rao Lower Bound). The experimental results show that the accuracy of the algorithm is improved by more than 50%. When the multi-point deployment scheme is used, the location error of the algorithm is further reduced to about 30% (simulation environment) and 23% (measured environment).
【作者單位】： 北京科技大學(xué)計(jì)算機(jī)與通信工程學(xué)院;北京科技大學(xué)融合網(wǎng)絡(luò)與泛在業(yè)務(wù)工程技術(shù)研究中心;
【基金】：國(guó)家自然科學(xué)基金(61304257) 北京市自然科學(xué)基金(4152036) 中央高�；究蒲袠I(yè)務(wù)費(fèi)(FRF-TP-15-026A2)資助 北京科技大學(xué)與臺(tái)北科技大學(xué)學(xué)術(shù)合作專題研究計(jì)劃經(jīng)費(fèi)輔助~~
【分類號(hào)】：U495

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