摘要
提出了具有一般相关量测噪声的线性系统的平滑估计算法 ,该算法是在系统正向和逆向滤波估计结果的基础上 ,利用线性无偏最小方差估计获得的 .由于量测噪声的相关性 ,使得其后验均值不一定等于其先验均值 ,而它的后验均值又无法通过计算得到 ,因而提出的算法是一个次优算法 .在正、逆向滤波结果已知时 ,所提出的算法计算量小 ,易于实现 .仿真实例说明 ,该算法的估计结果要优于正、逆向滤波估计结果 ,以及量测噪声不相关的Kalman平滑估计结果 .
Based on the forward and backward filtering estimates a smoothing algorithm is developed for linear systems with general correlated measurement noises by using the linear unbiased minimum variance estimation formula. Because of the correlation of the measurment noises the posterior mean of the noise is not always equal to its prior one and can’t be calculated. Hence, the proposed algorithm is suboptimal. When the forward and backward filtering results are known, the proposed algorithm has low computional complexity and can be realized easily. Through a simulation example it is indicated that the result of the proposed smoothing algorithm is better than that of the forward, backward filtering or Kalman smoothing algorithm, where the measurement noises are assumed to be uncorrelated.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2000年第9期1-4,37,共5页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目! (696740 0 9)
关键词
相关噪声
正向滤波
线性系统
平滑估计算法
correlated noise
forward filtering
backward filtering
smoothing
fusion
linear unbiased minimum variance estimation
