机载有源无源传感器稳健融合方法

摘要

Many conditions are difficult to meet the requirements of central filtering in the inforrnation fusion of airborne active and passive sensors.For example, under normal circumstance, the process noise is not accurate or unknown.In this paper, several robust Kalman filters are presented.The proposed methods focus on data fusion when the noise information in the motion equation or the measurement equation is unknown or not accurate.If only noise information in the process equation is unknown, the proposed adaptive filtering could use, the observational information to make real-time cstimation of the noise in motion equation.If the noises in movement equation and observation equation are not accurate, the Hinfinite filtering is used to estimate noise error variance.%在机载有源无源情报融合处理中,很多条件很难满足中心式滤波的要求,比如一般情况下过程噪声是不正确的,或者不知道的.给出了几种稳健的Kalman滤波,这些方法主要针对运动方程或者观测方程中噪声信息未知或者噪声信息不准确的情况下,对数据进行融合.如果只是过程的信息未知,提出的自适应滤波,即是用观测信息对运动方程的噪声进行实时估计;如果运动方程和观测方程的噪声不准确,则可以采用H∞滤波进行噪声误差方差估计.