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首页> 外文期刊>Aerospace and Electronic Systems, IEEE Transactions on >Adaptive node scheduling under accuracy constraint forwireless sensor nodes with multiple bearings-only sensing units
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Adaptive node scheduling under accuracy constraint forwireless sensor nodes with multiple bearings-only sensing units

机译：具有多个纯方位传感单元的无线传感器节点在精度约束下的自适应节点调度

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摘要

Wireless sensor networks (WSNs) are highly suitable for target tracking. In such networks, node scheduling is critical in terms of energy consumption and tracking accuracy. A WSN consisting of nodes with multiple bearings-only sensing units is considered in this study and an adaptive approach for the scheduling of such a network is presented. The proposed method continually determines the minimum number of measurements each node should perform in order to keep the tracking error below a certain limit. An extended Kalman filter (EKF) is utilized for target tracking. Tracking accuracy is formulated based on the nonlinear A-optimality measure. The node scheduling problem is reformulated as a linear binary mixed integer programming problem and solved in an online manner. Simulation results show that the proposed method results in less rms position error than the nearest node selection method, especially at the beginning of tracking when there is more uncertainty about the target state. With the same amount of energy consumption, the number of divergent tracks in this method is much fewer in comparison with those of the nearest node selection method.
机译：无线传感器网络（WSN）非常适合目标跟踪。在这样的网络中，节点调度在能耗和跟踪精度方面至关重要。在这项研究中考虑了由具有多个仅轴承感测单元的节点组成的WSN，并提出了一种用于此类网络调度的自适应方法。所提出的方法连续确定每个节点应执行的最小测量次数，以将跟踪误差保持在一定限度以下。扩展卡尔曼滤波器（EKF）用于目标跟踪。跟踪精度是基于非线性A最优度量制定的。将节点调度问题重新表述为线性二进制混合整数规划问题，并以在线方式解决。仿真结果表明，与最近的节点选择方法相比，该方法产生的均方根位置误差更小，尤其是在跟踪开始时目标状态的不确定性更大时。在能量消耗相同的情况下，与最近的节点选择方法相比，此方法中的发散轨道数要少得多。

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