粒子滤波的噪声相关下单步延迟无序量测更新算法

Update algorithm on one-step-lag out-of-sequence measurement with correlated noise based on particle filtering

在目标跟踪系统中,因通信延迟等原因会出现传感器量测无序地到达融合中心的现象,将这些量测称为无序量测(OOSM)。针对过程噪声、量测噪声相关的非线性系统中出现的无序量测问题,在现有算法基础上,提出了一种可处理单步延迟无序量测的新算法。在前向预测滤波框架下,对系统方程去相关化,并利用粒子滤波(PF)进行状态估计。仿真结果验证了算法的有效性。

In target tracking system,sensor measurements may arrive at the fusion center out of sequence because of communication delays,and these measurements are called out-of-sequence measurement（OOSM）.On the basis of existing algorithm,a new algorithm is proposed,which can solve one-step-lag OOSM problem occur in process noise and the measurement noise correlated in nonlinear system.By combing the framework of the forward prediction filtering,wipe off the correlation,and use particle filtering to estimate the state.Simulation results verify the effectiveness of the proposed algorithm.