针对事件触发无线传感器网络环境下实现目标跟踪会产生的量测矩阵不确定的问题,提出了一种高斯渐近滤波框架下的目标跟踪方法.首先,从网络节能角度出发,通过一种事件触发采样机制对传感器量测信息进行了有效的筛选.其次,采用高斯渐近扩展信息滤波方法融合收集到的传感器量测信息,得到移动目标的状态估计.再次,通过"渐近"的量测更新方法,有效地减少了线性化误差的影响,从而提高了目标跟踪系统的跟踪精度.最后,用仿真示例证明,相对于EIF方法,PEIF方法具有更高的跟踪精度.%Aiming at the uncertain problem of the measurement matrix generated by the target tracking in WSNs , it proposes a target tracking method under Gaussian progressive filter framework .It selects effectively the sensor measurement information from the aspect of network energy -efficient based on an event -triggered sampling mechanism .Using Gaussian progressive extended information filtering ( PEIF ) method , it fuses the collected measurement information , obtains the state estimation of the moving target .The"progressive"measurement up-date method can effectively reduce the impact of the linearization error , and improve the tracking accuracy of the target tracking system .Finally, a simulation example shows that the PEIF method has higher tracking accuracy than the EIF method .
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