| 最小二乘滤波及其在INS/双星系统中的应用 |
| |
| 引用本文： | 赵龙,陈哲. 最小二乘滤波及其在INS/双星系统中的应用[J]. 压电与声光, 2006, 28(4): 483-485 |
| |
| 作者姓名： | 赵龙 陈哲 |
| |
| 作者单位： | 北京航空航天大学,自动化科学与电气工程学院,北京,100083 |
| |
| 摘 要： | 为了克服传统Kalman滤波在实际应用中存在的局限性,研究了基于状态估计的最小二乘滤波。该方法将传统的最小二乘估计与状态估计问题有机结合,对系统噪声和量测噪声的统计特性不敏感。利用实测的激光捷联惯导系统/双星(LSINS/DS)组合数据对最小二乘滤波和传统Kalman滤波进行仿真比较,结果表明,在噪声统计特性未知的情况下,最小二乘滤波的精度更高、收敛速度更快、鲁棒性更强。
|
| 关 键 词： | 组合导航系统 惯导系统 双星系统 最小二乘滤波 |
| 文章编号： | 1004-2474(2006)04-0483-03 |
| 收稿时间： | 2004-12-10 |
| 修稿时间： | 2004-12-10 |
Least Square Filtering and Its Application in INS/DS Integrated System |
| |
| ZHAO Long,CHEN Zhe. Least Square Filtering and Its Application in INS/DS Integrated System[J]. Piezoelectrics & Acoustooptics, 2006, 28(4): 483-485 |
| |
| Authors: | ZHAO Long CHEN Zhe |
| |
| Affiliation: | School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China |
| |
| Abstract: | To overcome the limitation of conventional Kalman filtering(CKF) in engineering application,a least square filtering(LSF) based on the state estimation is studied.LSF combined conventional least square estimation with the state estimation problem,and is without the requirement of noise statistics information.The two methods were compared using practical measuring data in laser strapdown inertial navigation system(LSINS)/DS integrated system.The simulating results shows that compared with CKF,LSF has better estimation accuracy when noise statistics information is unknown,and the convergence performance of LSF is faster,robustness is better. |
| |
| Keywords: | integrated navigation inertial navigation system double-star system least square filtering |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
