空天预警研究学报2026，Vol.40Issue(2)：91-94,4.DOI:10.3969/j.issn.2097-180X.2026.02.003
面向RCS序列周期估计的高斯过程优化Lomb-Scargle算法
Lomb-Scargle algorithm optimized by Gaussian process for RCS sequence period estimation
摘要
Abstract
Aiming at the problem of non-uniform sampling time of radar cross section(RCS)sequence caused by the limitation of tracking resources in phased array radar,this paper proposes a period estimation meth-od using a Lomb-Scargle algorithm optimized by Gaussian process.In this method,the Lomb-Scargle algorithm is first adopted to process the non-uniform sampling sequence and obtain robust periodic initial value;then,a Gauss-ian process model including the periodic kernel is constructed,and finally,this initial value is taken as the starting point to iteratively optimize the period and other hyperparameters through the log-likelihood function.Simulation results demonstrate that,under conditions of a low proportion of observation duration and a low signal-to-noise ra-tio,the proposed method achieves fewer root mean square error than traditional trigonometric function fitting,sig-nificantly improving the period estimation accuracy of non-uniformly sampled RCS sequences.关键词
目标识别/RCS序列/周期估计/Lomb-Scargle算法/高斯过程Key words
target recognition/radar cross section(RCS)sequence/period estimation/Lomb-Scargle algo-rithm/Gaussian process分类
信息技术与安全科学引用本文复制引用
秦晓东,白小二,韩文俊,俞建国..面向RCS序列周期估计的高斯过程优化Lomb-Scargle算法[J].空天预警研究学报,2026,40(2):91-94,4.
