无线传感器网络目标跟踪性能优化及仿真∗

摘要

无线传感器网络中传感器节点相互协同完成感知任务,以传感器量测的信息效用和获取量测的能量消耗来折中地选择参与的节点,但用户对服务质量Qos( Quality of Service)的需求并没有在节点选择时得以体现。为此本文以目标跟踪为应用背景,提出了一种自适应动态协同自组织算法A-DCS,该算法同时完成检测与状态估计任务,首先根据用户设定的检测概率,确定候选节点集合,选择具有最大检测概率的节点为簇首；随之根据给定的状态估计精度,自适应确定参与感知任务的簇成员顺序和个数。统计不同检测概率和状态估计精度时相应的能量消耗,以此作为系统设计时参数设定的依据,从而最大可能地延长网络的生命周期。仿真表明：在跟踪精度和能量消耗两个指标下,该算法优于IDSQ和DCS。 A-DCS也适用于传感器网络系统中的其他估计问题。%Sensors should be selected elaborately to fulfil the sensing task in wireless sensor networks,sensor selec-tion is based on the tradeoff between information utility achieved by the sensor measure and energy overhead to fetch the measure. But the users’ requirements for quality of service( QoS) aren’t yet involved in the process of sensor col-laboration. A novel algorithm named A-DCS( Adaptively Dynamic Collaborative Self-organization) is proposed based on target tracking in this paper. Detection and estimation can be solved at the same tine in this algorithm. Given the threshold of detection probability the set of candidate sensor nodes can be confirmed,the sensor node with the maxi-mum detection probability is selected to be the cluster head. Then the sequence of cluster members participating in the sensing task can be made adaptively according to the given threshold of estimation variable,so the total number of cluster member should be ascertained in our method,and the corresponding energy consumption is given out. Ba-sing on the energy consumption under the condition of different detection probability and estimation accuracy the ap-propriate detection probability and estimation accuracy should be chosen to prolong the lifetime of networks. Simula-tion results demonstrate that this algorithm is superior to IDSQ and DCS in terms of the tracking accuracy and the energy consumption. This method can also be used in the problem of estimation in wireless sensor network.