Abstract: The sensor scheduling problem for a target-tracking sensor network is studied.The scheduling objective is designed considering tracking accuracy of each target and the overall tracking performance from the systematic viewpoint.The extended Kalman filter is adopted for target tracking and accuracy calculating.A mixed integral model is founded for this scheduling problem，the scale of which is too large to solve using traditional optimal methods.Thus a new genetic algorithm based on a local solution space jumping mechanism is designed to solve the model.Experimental results show that the presented algorithm performs well on this problem.

摘要： 对面向移动目标跟踪任务的传感器网络调度方法进行了研究。从单任务跟踪精度和总体任务完成情况两方面设计调度指标，采用扩展卡尔曼滤波器实现目标跟踪并计算跟踪精度，进而建立了该问题的混合整数调度模型。针对模型复杂度较高的特征，提出一种基于局部解空间跳出机制的改进型遗传算法并进行求解。仿真结果表明该算法针对该问题具有较高的求解性能。