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
  • [41] Splitting the recursive least-squares algorithm
    Magesacher, T
    Haar, S
    Zukunft, R
    Ödling, P
    Nordström, T
    Börjesson, PO
    ISSPA 2001: SIXTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOLS 1 AND 2, PROCEEDINGS, 2001, : 319 - 322
  • [42] The kernel recursive least-squares algorithm
    Engel, Y
    Mannor, S
    Meir, R
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2004, 52 (08) : 2275 - 2285
  • [43] Recursive Least Squares Dictionary Learning Algorithm
    Skretting, Karl
    Engan, Kjersti
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2010, 58 (04) : 2121 - 2130
  • [44] A Recursive Learning Algorithm for the Least Squares SVM
    Xia, Xiao-Lei
    Ouyang, Mingxing
    PRICAI 2024: TRENDS IN ARTIFICIAL INTELLIGENCE, PT I, 2025, 15281 : 209 - 220
  • [45] Recursive Algorithm of Generalized Least Squares Estimator
    Xu, Wenke
    Liu, Fuxiang
    2010 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2010), VOL 3, 2010, : 487 - 490
  • [46] An extended recursive least-squares algorithm
    Feng, DZ
    Zhang, HQ
    Zhang, XD
    Bao, Z
    SIGNAL PROCESSING, 2001, 81 (05) : 1075 - 1081
  • [47] A robust weighted total least squares algorithm and its geodetic applications
    Bin Wang
    Jiancheng Li
    Chao Liu
    Studia Geophysica et Geodaetica, 2016, 60 : 177 - 194
  • [48] A robust weighted total least squares algorithm and its geodetic applications
    Wang, Bin
    Li, Jiancheng
    Liu, Chao
    STUDIA GEOPHYSICA ET GEODAETICA, 2016, 60 (02) : 177 - 194
  • [49] Signal enhancement using a robust adaptive total least squares algorithm
    Hokkaido Univ, Sapporo, Japan
    J Acoust Soc Jpn E, 6 (285-293):
  • [50] Robust extended recursive least squares identification algorithm for Hammerstein systems with dynamic disturbances
    Dong, Shijian
    Yu, Li
    Zhang, Wen-An
    Chen, Bo
    DIGITAL SIGNAL PROCESSING, 2020, 101