基于能量优化的无线传感器网络动态分簇目标跟踪

发布时间：2019-04-11 08:58

【摘要】：针对无线传感器网络动态分簇目标跟踪中的数据碰撞与簇首选择过程导致能耗过高问题,提出一种基于能量优化的无线传感器网络动态分簇方法。首先,构建时分竞选传输模型,主动避免动态簇内数据碰撞,降低节点能耗;然后,基于能量信息与跟踪质量,提出能量均衡的最远节点调度策略,优化簇头节点调度;最后,根据加权质心定位算法,完成目标跟踪任务。实验结果表明:在节点随机部署的环境下,所提方法对于非线性运动目标的平均跟踪精度为0.65 m,与多目标跟踪动态簇员选择方法(DCMS)相当,比分布式事件定位动态分簇目标跟踪算法(DELTA)提高了45.8%;能量消耗方面,与DCMS和DELTA相比,所提方法的动态跟踪簇能量消耗有效降低了61.1%,延长了网络寿命。
[Abstract]:In order to solve the problem of high energy consumption caused by data collision and cluster head selection in dynamic clustering target tracking for wireless sensor networks, a dynamic clustering method for wireless sensor networks based on energy optimization is proposed. Firstly, a time-division campaign transmission model is constructed to avoid dynamic intra-cluster data collision and reduce node energy consumption. Secondly, based on energy information and tracking quality, the farthest node scheduling strategy with energy balance is proposed to optimize cluster head node scheduling. Finally, according to the weighted centroid localization algorithm, the target tracking task is completed. The experimental results show that the average tracking accuracy of the proposed method for nonlinear moving objects is 0.65 m in the environment of random deployment of nodes, which is comparable to the dynamic cluster member selection method (DCMS) for multi-target tracking. The dynamic clustering target tracking algorithm (DELTA) improved by 45.8%. In terms of energy consumption, compared with DCMS and DELTA, the proposed method effectively reduces the energy consumption of dynamic tracking clusters by 61.1% and prolongs the network life.
【作者单位】：广东工业大学自动化学院;
【基金】：国家自然科学基金资助项目(21376091) 广东省科技计划项目(2015A030401089)~~
【分类号】：TN929.5;TP212.9

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