不完全测量系统鲁棒SGQKF的传递对准滤波器设计和稳定性分析

针对复杂环境下运载体观测信息不完全测量并且存在随机干扰不确定的传递对准问题,研究了不完全测量随机不确定系统的鲁棒稀疏网格求积分(H_∞-SGQKF)的高斯逼近滤波算法。基于非线性离散系统的最优贝叶斯滤波框架和间断观测滤波算法以及不确定性扰动噪声下的H_∞范数的鲁棒SGQKF算法,给出了不完全测量的稀疏网格求积分的高斯逼近滤波算法;通过非线性系统随机稳定性理论,分析并给出了系统估计误差和估计误差方差有界的充分条件,同时给出了系统稳定的不完全测量时的丢包率临界值,证明间断观测条件下的不完全测量H_∞-SGQKF算法是稳定的。通过传递对准仿真试验和某型激光捷联式惯性导航系统的跑车试验对该算法进行了验证。结果表明,该方法比未采用鲁棒的不完全测量的稀疏网格求积分滤波的传递对准精度有所提高,说明不完全测量的鲁棒稀疏网格求积分滤波算法是正确的、稳定的,并且具有鲁棒性能。

Design and stability analysis of robust SGQKF transfer alignment filter for incomplete measurement system with stochastic disturbance

A transfer alignment method based on H∞-SGQKF is developed for the nonlinear systems with intermittent measurements and uncertain stochastic perturbations.A novel Gaussian robust filter with intermittent measurements (H∞-SGQKF) is proposed through presenting Gaussian approximate posterior probability density function (PDF) by embedding the Gaussian approximate filter into the robust mechanism of H∞ suboptimal filter.Using the direct method of Lyapunov,we prove that,under some conditions,the proposed filter is an exponential observer,i.e.,the dynamics of the estimation error is exponentially stability,and the error covariance matrices are nominal and robust convergent by providing the existence of a super-threshold value for the intermittent measurement probability.At last,a transfer alignment method based on the proposed filter is presented,and the ground vehicle test of missile-board SINS and a numerical example show that the obtained estimator has good estimation performance.