改进的超短基线系统自适应相位差估计器

doi:10.3969/j.issn.1000-1093.2021.07.012

兵工学报 ›› 2021, Vol. 42 ›› Issue (7): 1450-1456.doi: 10.3969/j.issn.1000-1093.2021.07.012

改进的超短基线系统自适应相位差估计器

喻敏¹，丁贤君¹，张晓亮²，祝明思¹

（1.武汉理工大学交通学院, 湖北武汉 430070； 2.中国船舶工业系统工程研究院，北京 100036)

上线日期:2021-07-30
作者简介:喻敏(1978—)，女, 副教授，博士生导师。E-mail: dilysyuwy@163.com；
丁贤君(1993—)，男，硕士研究生。E-mail: xj.ding@qq.com
基金资助:
国家自然科学基金重点国际合作研究项目（51720105011）；国家自然科学基金青年项目（51709211）；某国防科技重点实验室开放基金项目（SSDKKFJJ-2018-02）

Improved Adaptive Phase-difference Estimator for Ultra-short Baseline System

YU Min¹， DING Xianjun¹， ZHANG Xiaoliang²， ZHU Mingsi¹

(1.School of Transportation，Wuhan University of Technology，Wuhan 430070，Hubei, China;2.System Engineering Research Institute of CSSC，Beijing 100036，China)

Online:2021-07-30

摘要/Abstract

摘要： 针对传统的自适应相位差估计器，由于采用最小均方（LMS）算法存在收敛速度和稳态精度之间的矛盾，对基于LMS算法的自适应估计器提出改进方法。提出将最小二乘（RLS）算法应用到自适应相位差估计器中，进一步提高自适应估计器的稳定性。数值仿真和实验数据验证结果表明，所提的LMS算法和RLS算法两种自适应相位差估计器均能提高计算精度和收敛速度，其中RLS算法自适应相位差估计器的稳态精度更高。

关键词: 相位差估计器, 超短基线, 最小二乘算法, 最小均方算法

Abstract: In view of the contradiction between convergence speed and steady-state accuracy of the traditional adaptive phase difference estimator due to the use of the least mean square (LMS) algorithm, an improved method is proposed for the adaptive estimator based on the LMS algorithm. And the recursive least square (RLS) algorithm is proposed to be applied to the adaptive phase difference estimator to further improve the stability of adaptive estimator.Through numerical simulation and experimental data verification, the results show that the two improved adaptive phase-difference estimators of LMS and RLS algorithms can both improve the calculation accuracy and convergence speed, and the latter has a higher steady-state accuracy.

Key words: phase-differenceestimator, ultra-shortbaseline, leastmeansquarealgorithm, recursiveleastsquarealgorithm

中图分类号:

U666.73

喻敏，丁贤君，张晓亮，祝明思. 改进的超短基线系统自适应相位差估计器[J]. 兵工学报, 2021, 42(7): 1450-1456.

YU Min， DING Xianjun， ZHANG Xiaoliang， ZHU Mingsi. Improved Adaptive Phase-difference Estimator for Ultra-short Baseline System[J]. Acta Armamentarii, 2021, 42(7): 1450-1456.

参考文献

［1］惠俊英, 蔡平，马晓民. 自适应陷波滤波器应用研究［J］. 声学学报, 1991，16(1):19-24.
HUI J Y，CAI P， MA X M. Applied study of adaptive notch filter［J］. Acta Acustica, 1991，16(1):19-24. (in Chinese)
［2］梁国龙,赵羽,王逸林.基于自适应Notch滤波器的窄带信号参数估计［C］∥2001年全国水声学学术会议论文集.大同：中国声学学会水声学分会，2001.
LIANG G L，ZHAO Y，WANG Y L. Parameter estimation of narrowband signal based on adaptive notch filter［C］∥Proceedings of 2001 National Conference on Hydroacoustics.Datong：Underwater Acoustics Branch, Acoustical Society of China， 2001.(in Chinese)
［3］梁国龙,杨春,王德俊.频点自跟踪自适应频率估计器性能研究［J］.电子学报,2005,33(7):1204-1208.
LIANG G L，YANG C，WANG D J. Research on properties of frequency auto-tracking adaptive frequency estimator［J］. Acta Electronica Sinica,2005,33(7):1204-1208. (in Chinese)
［4］周一鸣.自适应滤波器的改进设计及其在参数估计中的应用研究［D］.哈尔滨：哈尔滨工程大学, 2015.
ZHOU Y M. Improved design of adaptive filter and its application in parameter estimation［D］. Harbin：Harbin Engineering University,2015. (in Chinese)
［5］张晓亮.长程超短基线定位系统信号处理算法仿真及软件设计［D］.哈尔滨：哈尔滨工程大学,2004.
ZHANG X L. Signal processing algorithm simulation and software design of long range ultra short base line positioning system［D］. Harbin：Harbin Engineering University,2004. (in Chinese)
［6］郭大刚.超短基线定位系统数字信号处理平台的设计与实现［D］.哈尔滨：哈尔滨工程大学，2009.
GUO D G. Design and realization of digital signal processing platform of ultra short base line positioning system［D］. Harbin：Harbin Engineering University,2009. (in Chinese)
［7］付进,梁国龙.多通道自适应陷波滤波器组设计及性能分析［J］. 哈尔滨工程大学学报, 2007, 28(9):80-85，101.
FU J，LIANG G L. Design and performance analysis of multi-channel adaptive notch filter［J］. Journal of Harbin Engineering University, 2007, 28(9):80-85，101. (in Chinese)
［8］ CHEN Y, TIAN J P, LIU Y P. Variable step size LMS algorithm based on modified Sigmoid function［C］∥Proceedings of 2014 International Conference on Audio, Language and Image Processing. Shanghai, China：IEEE, 2014: 627-630.
［9］张园，王辉. 一种改进的变步长LMS自适应滤波算法［J］. 现代雷达, 2008,30（7）：60-62,67.
ZHANG Y, WANG H. An improved LMS adaptive filter algorithm with vaviable step size［J］. Modern Radar, 2008,30（7）：60-62,67. (in Chinese)
［10］苑文学. 基于变步长LMS算法的GPS抗干扰的研究［D］. 天津：中国民航大学，2019.
YUAN W X. Research on the GPS anti-jamming based on variable step LMS algorithm［D］.Tianjin：Civil Avivation University of China, 2019. (in Chinese)
［11］田福庆,罗荣,李克玉,等.基于改进的双曲正切函数变步长LMS算法［J］.系统工程与电子技术, 2012, 34(9):1758-1763.
TIAN F Q, LUO R, LI K Y, et al. New variable step-size LMS algorithm on modified hyperbolic tangent function［J］.Systems Engineering and Electronics，2012, 34(9):1758-1763. (in Chinese)
［12］茹国宝，黄燕，郭英杰，等. 基于对数函数的新变步长LMS算法［J］.武汉大学学报（理学版），2015,61（3）：295-298.
RU G B, HUANG Y, GUO Y J, et al. New variable step size LMS algorithm based on logarithmic function［J］.Journal of Wuhan University (Science Edition)，2015,61（3）：295-298. (in Chinese)
［13］杨逸,曹祥玉,杨群.基于指数函数的归一化变步长LMS算法［J］.计算机工程, 2012, 38(10):134-136.
YANG Y,CAO X Y,YANG Q. Normalization variable step size LMS algorithm based on exponential function［J］. Computer Engineering, 2012, 38(10):134-136. (in Chinese)
［14］管四海, 李智, 黄辉,等. 带零吸收项的变步长l₀范数归一化最小均方误差算法［J］. 兵工学报, 2016,37(11):2170-2175.
GUAN S H,LI Z,HUANG H, et al. Modified zero-attracting l₀-NLMS algorithm［J］.Acta Armamentarii,2016,37(11):2170-2175. (in Chinese)
［15］王宝仁,曹明瑞．基于RLS自适应滤波算法的广义互相关时延估计方法研究［J］．组合机床与自动化加工术,2020(6):27- 31,36.
WANG B R, CAO M R. Research on generalized cross-correlation delay estimation method based on RLS adaptive filtering algorithm［J］. Modular Machine Tool & Automatic Manufacturing Technique, 2020(6):27-31,36. (in Chinese)

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改进的超短基线系统自适应相位差估计器

Improved Adaptive Phase-difference Estimator for Ultra-short Baseline System

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