基于改进LMS的引信回波自适应滤波算法

张洪鹏; 刘星; 兀伟; 王秉政

doi:10.15892/j.cnki.djzdxb.2023.02.015

弹箭与制导学报 >

2023 , Vol. 43 >Issue 2: 88 - 93

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2023.02.015

基于改进LMS的引信回波自适应滤波算法

张洪鹏 ¹ ,
刘星 ¹ ,
兀伟 ¹ ,
王秉政 ²

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¹ 西安工业大学电子信息工程学院,陕西西安 710021
² 西北工业集团有限公司,陕西西安 710043

刘星(1975—),男,研高工,博士研究生,研究方向:目标探测与识别。

张洪鹏(1995—),男,硕士研究生,研究方向:无线电探测。

收稿日期: 2022-09-24

网络出版日期: 2025-02-24

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Adaptive Filtering Algorithm of Fuze Echo Based on Improved LMS

ZHANG Hongpeng ¹ ,
LIU Xing ¹ ,
WU Wei ¹ ,
WANG Bingzheng ²

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¹ School of Electronic Information Engineering, Xi’an Technological University, Xi’an 710021, Shaanxi, China
² Northwest Industries Group Co., Ltd., Xi’an 710043, Shaanxi, China

Received date: 2022-09-24

Online published: 2025-02-24

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摘要

针对无线电引信回波在信号处理过程中易被噪声覆盖的问题,引入步长补偿因子和反馈控制的思想,提出一种基于改进最小均方(LMS)算法的引信回波自适应滤波算法。该算法在正态函数的基础上引入步长补偿因子共同约束步长取值,提高算法的收敛速度;采用当前误差信号与前一时刻误差信号的互相关值动态调整算法参数,实现对不相关噪声的抑制;同时结合步长归一化处理,增大步长的选择范围,使算法收敛速度更快,稳定程度更高。仿真实验结果表明:该算法可以有效降低噪声对引信回波信号的影响,且与原有算法相比在收敛速度和稳态误差上具有较好性能。

关键词： 引信回波信号; 自适应滤波算法; 补偿因子; 归一化; 收敛速度; 稳态误差

本文引用格式

张洪鹏 , 刘星 , 兀伟 , 王秉政 . 基于改进LMS的引信回波自适应滤波算法[J]. 弹箭与制导学报, 2023 , 43(2) : 88 -93 . DOI: 10.15892/j.cnki.djzdxb.2023.02.015

Abstract

Aiming at the problem that radio fuze echo is easily covered by noise during signal processing, the idea of step compensation factor and feedback control is introduced, and an adaptive filtering algorithm of fuze echo is proposed based on improved LMS. Based on the normal function, the compensation factor is introduced to jointly restrict the step size, so as to improve convergence speed of the algorithm. The correlation value between current error signal and previous error signal is used to dynamically adjust algorithm parameters to suppress the uncorrelated noise, at the same time, combined with step normalization, the selection range of step size is increased to make the algorithm converge faster and more stable. Simulation results show that the algorithm can effectively reduce the influence of noise on the echo signal of fuze, which has better performance in convergence speed and steady-state error compared with original algorithm.

Key words： fuze echo signal; adaptive filtering algorithm; compensation factor; normalization; convergence rate; steady-state error

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