Robust recursive total least squares passive location algorithm

被引:0
|
作者
Wu, Hao [1 ]
Chen, Shuxin [1 ]
Zhang, Hengyang [1 ]
Zhang, Yihang [1 ]
Ni, Juan [2 ]
机构
[1] College of Information and Navigation, Air Force Engineering University, Xi'an,710077, China
[2] Unit 94303, Weifang,261051, China
关键词
Statistics - Method of moments;
D O I
10.11817/j.issn.1672-7207.2015.03.017
中图分类号
学科分类号
摘要
To solve the problem that airborne passive location is susceptible to outliers, a robust recursive total least squares (RRTLS) airborne passive location algorithm was proposed based on the angle information. The airborne passive location model was established and the recursive total least squares(RTLS) solution was obtained. The RTLS solution was transformed into the weighted pattern, and robust TLS extreme value criterion was formulated. Then, the equivalent weight function was founded, which made the algorithm distinguish the outliers automatically, and the effects from outliers were reduced by the weight-reduction and the singular points elimination. The results show that with the increase of error, the value of the influence function in the RRTLS algorithm decreases, and the algorithm has high anti-outliers ability. When there are outliers, the results on the RLS and RTLS location are not reliable. On the other hand, the RRTLS algorithm performs an ideal estimation with good robustness. ©, 2015, Central South University of Technology. All right reserved.
引用
收藏
页码:886 / 893
相关论文
共 50 条
  • [1] A robust recursive least squares passive location algorithm
    Wu, Hao
    Chen, Shuxin
    Hou, Zhiqiang
    Zhang, Hengyang
    Journal of Computational Information Systems, 2013, 9 (04): : 1263 - 1270
  • [2] Robust structured total least squares algorithm for passive location
    Wu, Hao
    Chen, Shuxin
    Zhang, Yihang
    Zhang, Hengyang
    Ni, Juan
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2015, 26 (05) : 946 - 953
  • [3] Robust structured total least squares algorithm for passive location
    Hao Wu
    Shuxin Chen
    Yihang Zhang
    Hengyang Zhang
    Juan Ni
    Journal of Systems Engineering and Electronics, 2015, 26 (05) : 946 - 953
  • [4] A Robust and Regularized Algorithm for Recursive Total Least Squares Estimation
    Koide, Hugo
    Vayssettes, Jeremy
    Mercere, Guillaume
    IEEE CONTROL SYSTEMS LETTERS, 2024, 8 : 1006 - 1011
  • [5] A robust recursive least squares algorithm
    Chansarkar, MM
    Desai, UB
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1997, 45 (07) : 1726 - 1735
  • [6] Robust recursive partial least squares algorithm
    College of Mechanical and Vehicle Engineering, Hunan Univ, Changsha, Hunan 410082, China
    不详
    Hunan Daxue Xuebao, 2009, 9 (42-46):
  • [7] Robust recursive least squares adaptive beamforming algorithm
    Song, X
    Wang, J
    Wang, H
    IEEE INTERNATIONAL SYMPOSIUM ON COMMUNICATIONS AND INFORMATION TECHNOLOGIES 2004 (ISCIT 2004), PROCEEDINGS, VOLS 1 AND 2: SMART INFO-MEDIA SYSTEMS, 2004, : 238 - 241
  • [8] A Fast Robust Recursive Least-Squares Algorithm
    Rey Vega, Leonardo
    Rey, Hernan
    Benesty, Jacob
    Tressens, Sara
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (03) : 1209 - 1216
  • [9] A robust fast recursive least squares adaptive algorithm
    Benesty, J
    Gänsler, T
    2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS: VOL I: SPEECH PROCESSING 1; VOL II: SPEECH PROCESSING 2 IND TECHNOL TRACK DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS NEURALNETWORKS FOR SIGNAL PROCESSING; VOL III: IMAGE & MULTIDIMENSIONAL SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING - VOL IV: SIGNAL PROCESSING FOR COMMUNICATIONS; VOL V: SIGNAL PROCESSING EDUCATION SENSOR ARRAY & MULTICHANNEL SIGNAL PROCESSING AUDIO & ELECTROACOUSTICS; VOL VI: SIGNAL PROCESSING THEORY & METHODS STUDENT FORUM, 2001, : 3785 - 3788
  • [10] A recursive total least squares algorithm for deconvolution problems
    Vandaele, P
    Moonen, M
    PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6, 1998, : 1401 - 1404