带衰减观测多速率连续系统的分布式融合估计

Distributed fusion estimation for multi-rate continuous-time system with fading measurements

针对多速率连续系统,考虑不同传感器多速率采样和数据传输过程中造成的衰减观测现象,本文提出了多传感器的状态融合估计算法。将连续系统在状态估计更新时刻进行离散化,进而采用提升技术,通过状态增广,建立观测采样点的状态空间模型。利用射影理论,基于建立的观测采样点的状态空间模型,提出单传感器局部最优状态估值器。采用按矩阵加权分布式次优融合估计算法,提出多传感器融合估值器。对车辆悬挂系统和飞行器发动机系统算例进行仿真分析,验证所提估计算法的有效性。

For multi-rate continuous system,a multi-sensor fusion estimation algorithm is proposed,considering the multi-rate sampling of different sensors and the phenomenon of fading measurements caused by data transmission.The continuous system is discretized at the state estimation updating instants.Through state augmentation,the state space model at the measurement sampling instants is established by using the lifting technique.Secondly,a local optimal state estimator for single sensor is proposed based on the established model by applying the projection theory.The multi-sensor fusion estimator is given by using suboptimal matrix-weighted distributed fusion estimation algorithm.The effectiveness of the proposed estimation algorithm is verified by simulation analysis of a vehicle suspension system and a aircraft engine model.