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Journal of Projectiles, Rockets, Missiles and Guidance >

2017 , Vol. 37 >Issue 3: 93 - 96

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2017.03.024

CORRELATION TECHNOLOGY

An Adaptive Filtering Algorithm Based on Gradient-norm in Non-Gaussian Environment

  • FENG Ziang ,
  • HU Guoping ,
  • KUANG Xubin ,
  • ZHOU Hao
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  • 1 Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China
    2 No.93861 Unit, Shaanxi Sanyuan 710000, China

Received date: 2016-05-20

  Online published: 2025-05-28

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Abstract

Conventional least mean square (LMS) algorithms meet declines of performance in non-Gaussian environment. A new variable step-size normalized least mean p-norm algorithm based on gradient-norm is proposed. The new algorithm assumes that the non-Gaussian noise satisfies alpha stable distribution, and the step size is adaptively adjusted by the relationship between mean square departure (MSD) and the gradient-norm. Through the relationship, the convergence rate is accelerated and the steady state error is decreased at the same time. The performance of the proposed algorithm is confirmed by theoretical derivation. Simulation results show that the proposed method has faster convergence rate, smaller steady state error and better performance of anti-saltation in non-Gaussian environment.

Key words： a-stable distribution; adaptive filtering; gradient norm; normalized least mean p-normalgorithm

Cite this article

FENG Ziang , HU Guoping , KUANG Xubin , ZHOU Hao . An Adaptive Filtering Algorithm Based on Gradient-norm in Non-Gaussian Environment[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2017 , 37(3) : 93 -96 . DOI: 10.15892/j.cnki.djzdxb.2017.03.024

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