两种卡尔曼一致滤波算法的研究

摘要

This paper mainly introduces two consensus filtering algorithms:kalman-consensus filtering algorithm and simpli-fied kalman-consensus filtering algorithm.we compare the estimation performance of the two algorithms by numerical simula-tions,and further study the influence of the iteration step-size,then propose scheme of improvement.%近年来，随着分布式多智能体系统的迅速发展，多智能体一致性问题已经成为控制领域的热点问题。主要介绍了两种一致性滤波算法：卡尔曼一致滤波算法和简化卡尔曼一致滤波算法；应用数值仿真对比分析了两种算法的估计性能，进一步研究了迭代步长对估计误差的影响，并且提出了改善方案。