摘要
预先或在线获取系统噪声的统计特性，往往是有效设计一个估计器或控制器的先决条件．早期关于噪声辨识的工作主要针对平稳或统计特性缓变的噪声过程．本文提出一种混合系统噪声辨识新算法，该算法将新息滤波与交互式多模型算法结合起来，前者降低了权概率系数对量测噪声的敏感程度，而后者则是基于混合系统模态的马尔可夫链过程实现多模型的动态交互与动态切换．仿真结果证明了本文新算法的有效性．
Correct knowledge of noise statistics is essential for an estimator or controller tohave reliable performance. In practice,however,they are usually not known perfectly. Early effortson noise identification are mostly limited to stationary noise or noise with slowly-varying statisticsonly. We present a new noise identification algorithm for hybrid system. The new algorithm combines the innovation filtering and the interacting multiple model algorithm. The former decreasesthe sensitivity of probabilitic weightings to measurement noise and the later implement dynamic interaction and dynamic changing of multiple modes based on the Markovian chain process of thesystem models. Simulation results show the effectiveness of the new algorithm.
出处
《电子学报》
EI
CAS
CSCD
北大核心
1997年第5期95-98,共4页
Acta Electronica Sinica
基金
国家自然科学基金
关键词
噪声辨识
新息滤波
交互式
多模型算法
Noise indentification, Innovation filtering, Interacting multiple mode algorithm
