学术
摘 要:
针对多尺度带乘性噪声系统，在多尺度最优滤波融合的基础上。进行状态最优固定域平滑算法的研究。通过推广得到的平滑算法需要大量的局部传感器参数，而分布式多尺度滤波融合后不能保留这些信息。针对这一弊端对算法进行改进。推导出仅使用融合后的一步预测及滤波值的平滑算法。该算法在线性最小方差意义下是最优的。计算机仿真验证了算法的可行性。[著者文摘]
文章出处:
《中国海洋大学学报》-2008年38卷1期 -139-142页
栏目信息:
分 类 号:
文献标识码:
A
文章编号:
1672-5174（2008）01-139-04
Optimal State Smoothing Algorithm for Multiscale Systems with Multiplicative Noise
CHU Dong-Sheng, YU Chun-Xiao, WU Hao-Gang （College of Engineering, Ocean University of China, Qingdao 266100, China）
Abstract:
Based on multiscale optimal filtering fusion, an optimal state fixed-interval smoothing algorithm is developed for systems with multiplicative noise. The smoothing algorithm obtained by generalization requires a great many local sensors＇ parameters while the information cannot be reserved through distributed multiscale filtering fusion. In order to solve this defect, this paper proposes a smoothing algorithmonly using one-step prediction and filtering value. The algorithm is optimalin the sense of linear minimum-variance. The feasibility of the algorithmis shown by computer simulations.[著者文摘]
Key words:
mtiscale; systems withmultiplicative noise; optimal filtering fusion; fixed-interval smoothing
基金资助:
国家自然科学基金数学天元基金（A0324676）资助
更多>>免费文章
cqvip.com