【摘要】：基于自組織傳感器網(wǎng)絡(luò)的目標(biāo)跟蹤技術(shù)無論在軍事還是民用上都有著很大的應(yīng)用價值,其主要任務(wù)是在噪聲空間中分布位置分散的傳感器節(jié)點,各節(jié)點對目標(biāo)信息進(jìn)行分析、交換、匯總,協(xié)同實現(xiàn)對目標(biāo)的跟蹤監(jiān)測。如何在資源有限的情況下,合理地部署和管理傳感器節(jié)點,使得目標(biāo)區(qū)域沒有監(jiān)測盲區(qū),并且讓傳感器組網(wǎng)能夠在恰當(dāng)?shù)臅r間點上對進(jìn)入監(jiān)測范圍的每一個目標(biāo)指派對應(yīng)的傳感器進(jìn)行穩(wěn)定有效的跟蹤是自組織網(wǎng)絡(luò)設(shè)計的主要問題。本文根據(jù)自組織網(wǎng)絡(luò)協(xié)同探測功能執(zhí)行順序,對相關(guān)內(nèi)容進(jìn)行了研究:組網(wǎng)中的傳感器需要有科學(xué)的部署算法對其進(jìn)行調(diào)動,在一定約束條件下,將組網(wǎng)監(jiān)測范圍覆蓋整個監(jiān)測區(qū)域,優(yōu)化節(jié)點拓?fù)浣Y(jié)構(gòu),并根據(jù)節(jié)點分布狀態(tài)分派合適的傳感器對其進(jìn)行跟蹤監(jiān)測,以達(dá)到任務(wù)性能最優(yōu);完成傳感器部署任務(wù)后,需要在噪聲環(huán)境中根據(jù)空間位置分散的移動傳感器或者固定傳感器獲得的傳感器數(shù)據(jù),設(shè)計合適的算法估計分析目標(biāo)的運動參數(shù);節(jié)點間通信是自組織網(wǎng)絡(luò)能量主要消耗源,需要設(shè)計合理的算法簡化節(jié)點間通信機(jī)制,同時還要提高組網(wǎng)對運動方向突變的目標(biāo)的跟蹤能力。本文的工作主要從這三個方面進(jìn)行展開,主要內(nèi)容如下:一、提出了應(yīng)用于自組織網(wǎng)絡(luò)的優(yōu)化部署算法。部署算法中,每個節(jié)點根據(jù)局部監(jiān)測區(qū)域節(jié)點密度和能量剩余情況,決定組網(wǎng)執(zhí)行對等結(jié)構(gòu)模式或能量排序模式,自主選擇節(jié)能移動路徑,改善節(jié)點拓?fù)浣Y(jié)構(gòu),提升監(jiān)測范圍覆蓋率,同時使得系統(tǒng)運行的持續(xù)時間更長久。二、對廣泛應(yīng)用的偽線性運動參數(shù)估計算法進(jìn)行了改進(jìn)。本文基于偽線性偏差補(bǔ)償估計算法,構(gòu)建輔助變量加權(quán)矩陣,減小了原算法的誤差協(xié)方差矩陣,同時確保算法結(jié)果的收斂性。三、研究了一種分布式的二元量化變分算法,通過使用變分算法壓縮在節(jié)點之間交換的數(shù)據(jù),減少數(shù)據(jù)量,降低組網(wǎng)通信能耗。同時,二元量化變分算法具有良好的獨立參數(shù)特性來確保跟蹤性能穩(wěn)定性,能夠?qū)哂熊壽E突變的目標(biāo)進(jìn)行有效跟蹤。
[Abstract]:The target tracking technology based on self-organizing sensor network has great application value in both military and civil fields. Its main task is to distribute the sensor nodes scattered in the noise space, and each node analyzes the target information. Exchange, summarize, and cooperate to achieve target tracking and monitoring. How to reasonably deploy and manage sensor nodes with limited resources, so that there are no monitoring blind areas in the target area, And it is the main problem in the design of ad hoc network that the sensor network can track the sensor assigned to every target entering the monitoring range at the right time. In this paper, according to the execution order of the cooperative detection function of the ad hoc network, the related contents are studied: the sensors in the network need to be mobilized by scientific deployment algorithm, and under certain constraints, The network monitoring area covers the whole monitoring area, and the topology of the nodes is optimized, and the appropriate sensors are assigned according to the distributed state of the nodes to track and monitor them, in order to achieve the optimal performance of the task, and after the sensor deployment task is completed, It is necessary to design a suitable algorithm to estimate the motion parameters of the target in noise environment according to the sensor data obtained by the spacial distributed moving sensor or the fixed sensor, and the communication between nodes is the main energy consumption source of the ad hoc network. It is necessary to design a reasonable algorithm to simplify the communication mechanism between nodes and to improve the ability of the network to track the moving direction sudden change target. The main contents of this paper are as follows: 1. An optimal deployment algorithm for ad hoc networks is proposed. In the deployment algorithm, each node decides to implement the peer-to-peer structure mode or the energy ranking mode according to the local monitoring of the regional node density and energy surplus, and independently chooses the energy-saving mobile path to improve the node topology. Increase the coverage of the monitoring range and make the system run longer. Secondly, the widely used pseudolinear motion parameter estimation algorithm is improved. Based on the pseudo-linear offset compensation algorithm, the auxiliary variable weighting matrix is constructed to reduce the error covariance matrix of the original algorithm and to ensure the convergence of the algorithm results. Thirdly, a distributed binary quantization variational algorithm is studied. By using the variational algorithm to compress the data exchanged between nodes, the amount of data is reduced and the communication energy consumption is reduced. At the same time, the binary quantization variational algorithm has good independent parameter characteristics to ensure the stability of tracking performance, and can effectively track the target with trajectory mutation.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN929.5;TP212.9

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本文編號：2282447