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研究线性随机离散系统卡尔曼滤波(KF)中预测误差方差P(K|K)的递归特性,在此基础上,提出基于滤波的监控策略优化问题,对问题的各种形态进行研究,并提出相应的解决方案.首先,针对监控策略优化中存在的带约束双目标优化问题,提出一种可变种群遗传算法;然后,研究从滤波处理的角度提炼出滤波过程中的监控策略优化以及各种形态下的优化方案.相应的理论分析和仿真实验对于高精滤波估计中测量方案的拟定,具有重要的实用价值与指导意义.
The recursive properties of prediction error variance P (K | K) in linear stochastic discrete-time system Kalman filter (KF) are studied. Based on this, the optimization problem based on filtering is proposed, and the various forms of the problem are studied. The corresponding solution is proposed.Firstly, a variable population genetic algorithm is proposed for the constrained dual-objective optimization problem existing in the monitoring strategy optimization. Then, the optimization of the monitoring strategy in the filtering process is studied from the perspective of the filtering process, The optimization scheme in the form of the corresponding theoretical analysis and simulation experiments for the high precision filter estimation measurement program has important practical value and guiding significance.