APPLICATION OF THE NORMALIZED LMS ALGORITHM TO MSLC.

被引：0
|
作者：
Nitzberg, Ramon [1 ]
机构：
[1] GE, Advanced Technical Programs, Section, Syracuse, NY, USA, GE, Advanced Technical Programs Section, Syracuse, NY, USA
来源：
IEEE Transactions on Aerospace and Electronic Systems | 1985年 / AES-21卷 / 01期
关键词：
MATHEMATICAL TECHNIQUES - Least Squares Approximations - RADAR - SONAR;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
For some conditions, the convergence time of the conventional LMS algorithm is longer than the radar dwell time so that the MSLC technique does not cancel jammers. The convergence time depends upon the power and angular locations of the jammers. The normalized LMS technique can decrease convergence times by several orders of magnitude. It causes the convergence time to be essentially independent of the jammer powers and decreases the convergence time dependence upon location. The derivation of an exact first moment analysis of the weights for the normalized LMS algorithm is given.
引用
收藏
页码：79 / 91
相关论文
共 50 条
  • [41] FEATURE NORMALIZED LMS ALGORITHMS
    Yazdanpanah, Hamed
    Apolinario, Jose A., Jr.
    CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2019, : 806 - 809
  • [42] An improved model for the normalized LMS algorithm with Gaussian inputs and large number of coefficients
    Costa, MH
    Bermudez, JCM
    2002 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-IV, PROCEEDINGS, 2002, : 1385 - 1388
  • [43] Control of an electromagnetic suspension vibration isolator based on block normalized LMS algorithm
    Wei, Cui-Can
    Wang, Yong
    Chen, Shao-Qing
    Liang, Qing
    Zhendong yu Chongji/Journal of Vibration and Shock, 2012, 31 (18): : 100 - 103
  • [44] A fully analytical recursive stochastic model to the Normalized Signed Regressor LMS algorithm
    Costa, MH
    Bermudez, JCM
    SEVENTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOL 2, PROCEEDINGS, 2003, : 587 - 590
  • [45] An Efficient Noise Removal Technique Using Modified Error Normalized LMS Algorithm
    C. Venkatesan
    P. Karthigaikumar
    National Academy Science Letters, 2018, 41 : 155 - 159
  • [46] CONVERGENCE AND PERFORMANCE ANALYSIS OF THE NORMALIZED LMS ALGORITHM WITH UNCORRELATED GAUSSIAN DATA - COMMENT
    MORGAN, DR
    IEEE TRANSACTIONS ON INFORMATION THEORY, 1989, 35 (06) : 1299 - 1299
  • [47] A New Algorithm of Normalized LMS Blind Multiuser Dectector Based on Kalman Filter
    Guo, Shao-bin
    Huang, Ping
    Guo, Shao-jing
    2009 5TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-8, 2009, : 2130 - +
  • [48] Partial-Update Normalized Sign LMS Algorithm Employing Sparse Updates
    Kim, Seong-Eun
    Choi, Young-Seok
    Lee, Jae-Woo
    Song, Woo-Jin
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2013, E96A (06) : 1482 - 1487
  • [49] SELECTION OF ORTHONORMAL TRANSFORMS FOR IMPROVING THE PERFORMANCE OF THE TRANSFORM DOMAIN NORMALIZED LMS ALGORITHM
    FARHANGBOROUJENY, B
    GAZOR, S
    IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING, 1992, 139 (05) : 327 - 335
  • [50] An Efficient Noise Removal Technique Using Modified Error Normalized LMS Algorithm
    Venkatesan, C.
    Karthigaikumar, P.
    NATIONAL ACADEMY SCIENCE LETTERS-INDIA, 2018, 41 (03): : 155 - 159
12345