一种不等式状态约束最优滤波算法

针对非线性系统中较难处理的不等式状态约束滤波问题,提出了一种新的约束无迹卡尔曼滤波算法.该算法利用最大似然法则推导出滤波均方误差函数,将不等式约束条件转化为惩罚函数加入到误差函数中,使用自适应步长法快速搜索最优解.通过理论分析,证明了约束滤波解是误差函数的严格局部最小值,具有最小滤波均方误差.对具有航路约束的电子导航模型进行了仿真,结果表明,该算法具有较高的跟踪精度.

Approach for optimal filtering of the nonlinear system with inequality constraints

According to state estimation for the nonlinear system with intractable inequality constraints, a novel constrained unscented kalman filter (CUKF) is proposed. The objective function is derived by using the maximum probability method, inequality constraints are treated skillfully as a penalty function, and the optimum constrained solution can be solved iteratively using the adaptively step length method. Through theoretical analyses, the constrained solution is the rigorous local minimizer of the objective function. A target tracking example based on digital navigation is presented to illustrate the efficacy of the CUKF. Simulation results show that the CUKF has a better filtering accuracy.