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为使目标跟踪系统的精度和能量消耗达到最佳平衡,节点选择策略在基于无线传感网络的目标跟踪系统中起着关键的作用。文章将节点选择归类为数学中的背包问题,同时通过预测信息熵及能量消耗,提出一个创新性的目标方程去判定该节点是否需要参与定位。通过自适应调整背包问题中的价值阈值的节点选择策略决定背包问题中的总容量,也就是参与运算的节点数。在计算效率上我们通过贪婪竞争策略减少不合适的候选节点,同时采用遗传算法去解决随后出现的约束性优化问题。仿真结果证明该算法可以提供更高的跟踪精度以及更少的系统能量消耗。
In order to achieve the best balance between the accuracy and energy consumption of the target tracking system, the node selection strategy plays a key role in the target tracking system based on wireless sensor networks. The article classifies the node selection as the knapsack problem in mathematics. At the same time, by proposing the information entropy and energy consumption, an innovative objective equation is proposed to determine whether the node needs to be involved in the localization. The total capacity in the knapsack problem is determined by the node selection strategy that adaptively adjusts the value threshold in the knapsack problem, that is, the number of nodes participating in the operation. In computational efficiency, we reduce the unsuitable candidate nodes by the greedy competition strategy, and use genetic algorithm to solve the subsequent constrained optimization problem. Simulation results show that the algorithm can provide higher tracking accuracy and less system energy consumption.