Energy efficient fast predictor for WSN-based target tracking
Energy efficient fast predictor for WSN-based target tracking
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DOI：
10.1007/s12243-014-0430-y
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发表时间：
2014-03
期刊：
影响因子：
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通讯作者：
M. Mirsadeghi;A. Mahani
中科院分区：
文献类型：
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作者：
M. Mirsadeghi;A. Mahani
传感器节点一旦部署在网络区域，其电源更换一般是困难的。因此，节能是无线传感器网络中目标跟踪最重要的问题之一。为了减少能量消耗，延长网络生命周期，移动对象周围的节点需要负责感知目标。通过对目标位置的准确预测，可以减少目标跟踪中参与节点的数量。本文提出了一种基于位置预测的快速、节能、高精度的目标跟踪方案。与其他预报器相比，该预测器的漏检率很低，特别是在随机路点移动模型中，在暂停时间后，方向、速度和加速度这三个主要参数会发生变化。预测器的准确性直接影响到漏检率，从而大大降低了能耗。此外，提出了一种新的节点选择准则，通过唤醒目标周围最少的节点来跟踪目标。仿真结果表明，与扩展卡尔曼滤波(EKF)和无迹卡尔曼滤波(UKF)预测器相比，本文提出的预测器具有更低的能量消耗和更低的复杂度。
Power source replacement of the sensor nodes, which are once deployed in the network area, is generally difficult. So, energy saving is one of the most important issues for object tracking in wireless sensor networks. To reduce the consumed energy and prolong the network lifetime, the nodes surrounding the mobile object should be responsible for sensing the target. The number of participant nodes in target tracking can be reduced by an accurate prediction of the object location. In this paper, we present a fast energy efficient with high-accuracy target tracking scheme which is based on location prediction. The missing rate of proposed predictor is very low in comparison with other predictors especially in a random waypoint mobility model in which after pause time, the three main parameters direction, velocity and, acceleration would be changed. The accuracy of predictor has a direct effect on missing rate and so strongly reduces the consumed energy. Additionally, a new node selection criterion is proposed in which minimum nodes surrounding the object are wakened and track the object. Simulation results show that our proposed predictor has low consumed energy and complexity in comparison with Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) predictors.