本文選題：無線傳感器網(wǎng)絡(luò)　切入點：節(jié)點定位　出處：《南京航空航天大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：作為無線傳感器網(wǎng)絡(luò)關(guān)鍵技術(shù)之一,節(jié)點定位是眾多應(yīng)用的基礎(chǔ)與核心技術(shù),在無線傳感器網(wǎng)絡(luò)的監(jiān)測活動中的作用至關(guān)重要�；赥DOA測距的節(jié)點定位算法目前較為廣泛使用,此類算法有兩個主要誤差源:非視距導(dǎo)致的TDOA測距誤差以及非線性方程解的誤差。本課題研究機場飛行區(qū)內(nèi)特種車輛的定位問題。飛行區(qū)地面部分包括跑道、滑行道、停機坪等,由于大量飛機、特種車輛的存在,此區(qū)域NLOS誤差嚴(yán)重且誤差模型無法確定。在基于TDOA的無線定位算法中,為了有效抑制NLOS造成的TDOA測距誤差,本文針對卡爾曼濾波算法進行了改進。通過研究誤差特性,針對較大NLOS誤差會導(dǎo)致后續(xù)估計值均受嚴(yán)重影響引入新息閾值,而針對NLOS誤差不可避免的特性引入修正系數(shù),進而改進卡爾曼濾波迭代過程,以獲得更準(zhǔn)確的估計值。通過仿真與原始卡爾曼濾波算法以及部分改進算法進行了對比,證實了本文算法的有效性。其次,在基于TDOA的無線傳感器網(wǎng)絡(luò)定位算法中,最小二乘算法復(fù)雜度低,但抗非視距誤差能力較弱。Taylor級數(shù)展開算法能夠通過迭代求精有效抑制NLOS誤差,但受初始估計值影響較大。本文針對兩種算法缺點及機場特種車定位特性,將兩種算法進行了混合。首先利用最小二乘算法獲得初始估計位置,然后并取該估計域質(zhì)心作為Taylor算法初始值進行迭代求精。通過仿真與最小二乘法及Taylor算法進行了對比,結(jié)果表明改進算法具有更高的定位精度。
[Abstract]:As one of the key technologies of wireless sensor networks, node localization is the foundation and core technology of many applications, play an important role in monitoring the activities of wireless sensor networks. The node localization algorithm based on TDOA is currently used widely, this kind of algorithm has two main error sources: non line of sight caused by the error of TDOA algorithm and nonlinear equations solution the problem of positioning error. This paper studies the airport flight area special vehicles. The flight area includes ground runway, taxiway, apron, due to a large number of aircraft, special vehicle, this area is serious and the error model of NLOS error can not be determined. Based on the TDOA wireless location algorithm, in order to effectively suppress the ranging error of TDOA NLOS, the Calman filter method. Through the study of the characteristics of error for large NLOS error will lead to subsequent estimates Are affected by the introduction of new information and according to the characteristics of NLOS error threshold, inevitably the correction coefficient, and then improved Calman filter iterative process, in order to get more accurate estimation values. By simulation with the original Calman filtering algorithm and some improved algorithms were compared to show the effectiveness of the algorithm. Secondly, based on the location of TDOA the wireless sensor network algorithm, least squares algorithm with low complexity, but the NLOS error mitigation capability of.Taylor series expansion algorithm can effectively restrain the NLOS errors through iterative refinement, but the initial estimate value. Aiming at the influence of two kinds of special vehicle positioning algorithm shortcomings and airport characteristics, the two algorithms are firstly mixed. Least squares algorithm to obtain the initial position estimate, and then the estimation of domain of centroid iterative refinement as the initial value of Taylor algorithm by simulation. Compared with the least square method and the Taylor algorithm, the results show that the improved algorithm has higher positioning accuracy.

【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP212.9;TN929.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 梁韻基;周興社;於志文;倪紅波;;普適環(huán)境室內(nèi)定位系統(tǒng)研究[J];計算機科學(xué);2010年03期

，

本文編號：1585533