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中文摘要：
在移动传感器网络中，观测器与目标的相对位置对目标的定位性能有重要的影响。为了提高目标的定位精度，提出了一种观测器运动轨迹的优化算法。算法把目标均方位置误差作为优化对象，使用扩展卡尔曼滤波器估计目标的位置。算法以目标和观测器的方位分布关系为基础，减小了观测器最优位置的搜索范围。仿真结果表明，使用多个观测器进行目标定位，滤波收敛速度快，定位误差小。最后给出了单个和多个观测器的“最优”运动规则。
英文摘要：
In the mobile sensor network, the relative position of observer and target is an important factor which significantly affects the localization performance of target. In order to improve the localization accuracy of target, optimization algorithm of observer trajectory is proposed. It is based on minimizing the filtered mean square （MS） position error. It estimates the target position utilizing an extended Kalman filter （EKF）. It decreases the uncertain region of observer optimization position, based on the observer and target bearing distributing relationships. Simulation results show that the convergence rate, utilizing more observations moving to estimate the target localization, is more quicker than using one observer, and the localization error becomes less. Finally, the most general moving rule of one and more observers is given.
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