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计算机系统应用英文版:2023,32(6):181-188
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复杂阵地的合成导向矢量最大似然测高
(西安理工大学 自动化与信息工程学院, 西安 710048)
Synthesized Vector Maximum Likelihood Altimeter for Complex Positions
(School of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China)
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Received:December 03, 2022    Revised:January 06, 2023
中文摘要: 雷达在目标低仰角测高时存在严重的多径效应, 复杂阵地使多径回波产生无规律反射, 造成幅度与相位发生不同程度的畸变. 本文引入扰动多径模型, 解决经典多径模型与复杂阵地的多径回波反射不匹配问题, 研究基于扰动模型的合成导向矢量最大似然(synthesized vector maximum likelihood, SVML)测高方法. 该方法引入扰动参数表征复杂阵地的多径回波现象, 利用基于稀疏贝叶斯学习的扰动多径 (perturbational multipath sparse Bayesian learning, PSBL) 算法得到扰动参数, 应用于SVML算法, 提高了米波雷达在复杂阵地下的测高性能.
Abstract:There is a serious multipath effect when the radar measures the target at a low elevation angle. The complex position makes the multipath echo produce irregular reflection, which results in different degrees of amplitude and phase distortion. In this study, a perturbational multipath model is introduced to solve the mismatch between the classical multipath model and the multipath echo reflection of the complex positions, and a height measurement method of the synthesized vector maximum likelihood (SVML) based on the perturbational model is studied. Perturbation parameters are introduced to characterize multipath echo phenomena of complex positions and are obtained by the perturbational multipath sparse Bayesian learning (PSBL) algorithm. The obtained parameters are applied to the SVML algorithm, which improves the height measurement performance of VHF radars in complex positions.
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基金项目:国家自然科学基金(61671375)
引用文本:
刘高辉,沈玲慧.复杂阵地的合成导向矢量最大似然测高.计算机系统应用,2023,32(6):181-188
LIU Gao-Hui,SHEN Ling-Hui.Synthesized Vector Maximum Likelihood Altimeter for Complex Positions.COMPUTER SYSTEMS APPLICATIONS,2023,32(6):181-188