基于CKF的WSN目标定位跟踪技术研究

发布时间：2018-01-12 18:43

本文关键词：基于CKF的WSN目标定位跟踪技术研究　出处：《西南交通大学》2015年硕士论文　论文类型：学位论文

【摘要】：目标定位跟踪技术是无线传感器网络的关键技术之一。现有WSN目标定位跟踪算法存在精度不高、能耗过大、计算复杂性过高等缺点,如何提高定位跟踪精度、降低计算复杂性是当前国内外研究的热点。WSN节点定位技术是目标跟踪技术的基础,只有当WSN的所有节点定位出自身位置,才能利用WSN有效地进行目标跟踪。为此,本文重点针对基于CKF的WSN节点定位算法和目标跟踪算法展开了深入的研究。首先,本文全面分析和总结了静止WSN和移动WSN目标定位跟踪技术的相关国内外研究现状,分析了定位算法和目标跟踪算法的性能评价指标,为本文的后续研究奠定了扎实基础。其次,详细对比分析了扩展卡尔曼滤波、无迹卡尔曼滤波、粒子滤波和容积卡尔曼滤波四种非线性滤波算法,仿真比较了四种算法的一维非线性估计精度,并通过仿真分析了UKF和CKF算法,结果表明：在三维以下,UKF算法优于CKF；三维及以上,CKF算法优于UKF。然后,针对无线传感器网络节点定位技术,为提高定位精度、降低计算复杂性,提出了一种基于CKF的无线传感器网络分布式定位算法,同时在考虑节点移动性的基础上,提出了基于CKF的移动无线传感器网络分布式定位算法。仿真结果表明：基于CKF的WSN分布式定位算法的定位精度与UKF算法相当,高于极大似然估计定位法,计算复杂性低于UKF算法；基于CKF的MWSN定位算法的定位精度高于WSN定位算法。接着,介绍了匀速运动、匀加速运动和恒速转弯三种目标跟踪模型,研究了基于卡尔曼滤波的交互式多模型算法,提出了一种基于CKF的无线传感器网络目标跟踪算法,并通过仿真实验验证了该算法的有效性。最后,总结本文开展的研究工作,并指出未来的研究方向。
[Abstract]:Target tracking technology is one of the key technologies in wireless sensor networks. The existing WSN algorithm of target tracking accuracy is not high, the energy consumption is too large, the computational complexity is too high shortcomings, how to improve the tracking accuracy, reduce the computational complexity of.WSN node localization technology is the current hot research at home and abroad is the basis of target tracking, only when all node localization WSN out of their own position, in order to effectively use WSN to track the target. Therefore, this paper focuses on the WSN localization algorithm and target tracking algorithm based on CKF is researched. Firstly, this paper analyzes and summarizes the tracking technology of static WSN and mobile target positioning WSN related analysis at home and abroad. The performance evaluation index of localization algorithm and target tracking algorithm, which lays a solid foundation for the follow-up research. Secondly, with the analysis The extended Calman filter, unscented particle filter and Calman filter, Calman filter volume four nonlinear filtering algorithm, simulation comparison of four algorithms in a one-dimensional nonlinear estimation accuracy are analyzed by simulation of UKF and CKF algorithm, the results show that: in the following three, UKF algorithm is better than CKF; three and above, the CKF algorithm is better than UKF. then, according to the wireless sensor network node positioning technology, to improve the positioning precision, reduce the computational complexity, proposes a distributed localization algorithm in wireless sensor network based on CKF, at the same time, considering the node mobility, the mobile wireless sensor network distributed localization algorithm based on CKF. The simulation results show that the positioning accuracy and UKF algorithm WSN distributed localization algorithm CKF is based on the above estimation method and the maximum likelihood, the computational complexity is lower than that of the UKF algorithm based on MWS CKF; The positioning accuracy of N positioning algorithm than WSN localization algorithm. Then, introduces the uniform motion, uniform acceleration and constant turn three target tracking model, study the interactive multiple model algorithm based on Calman filter, proposes an algorithm of wireless sensor networks target tracking based on CKF, and verify the effectiveness of the algorithm through the simulation experiment. Finally, summarize the research work carried out in this article, and pointed out the direction of future research.

【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN929.5;TP212.9

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