粒子滤波在无线传感器网络目标跟踪中的应用

将粒子滤波（PF）算法应用于无线传感器网络（WSNS）的目标跟踪，并给出了粒子滤波实现的具体步骤。动态组织传感器网络节点成簇，实现了对网络中做匀速直线运动的单个目标的跟踪。分别采用扩展卡尔曼滤波（EKF）、无迹卡尔曼滤波（UKF）和PF算法进行了仿真试验。结果表明，在无线传感器网络目标跟踪领域，PF算法比EKF算法、UKF算法的滤波精度更高，性能更好，并且在实际应用中，由于该算法能够有效解决非线性、非高斯环境中的目标跟踪问题，实现简单而增强了可用性。

Applications of Particle Filter in Wireless Sensor Networks for Target Tracking

Particle filter （PF） algorithm is introduced and applied to target tracking in wireless sensor networks （WSNs） , implementation of PF is deduced by steps. Sensor nodes areorganized into clusters, tracking single target which moves in line at a uniform velocity is implemented. Extended Kalman filter （EKF）, unscented Kalman filter （UKF） and particle filter are applied to tracking target respectively. The tracking results of the simulations show that compared with EKF, UKF, PF has better tracking accuracy and better performance. And in practical application, it can effectively solve target tracking problem in nonlinear and non-Gaussian environment, easy-implementation which make it more feasible to use.