信号处理2025，Vol.41Issue(7)：1229-1240,12.DOI:10.12466/xhcl.2025.07.008
一种基于粒子群优化的新型ELoran信号天地波分离算法
A Novel ELoran Signal Sky-Ground Waves Separation Algorithm Based on Particle Swarm Optimization
摘要
Abstract
The enhanced Loran(ELoran)system,an advancement of the Loran-C navigation system,plays a critical role in high-precision positioning and timing through accurate signal period recognition.However,in practical applica-tions,conventional signal period recognition methods are susceptible to errors caused by skywave interference and noise,which degrade positioning accuracy.To address this limitation,this study first employed a spectrum division ap-proach with an adaptive window width to extract delay and amplitude information for both skywave and groundwave components.By adjusting the window width,the proposed method can obtain relatively accurate delay and amplitude in-formation under varying signal-to-noise ratio(SNR)and skywave-groundwave strength conditions.The particle swarm optimization(PSO)algorithm is employed to refine the IFFT time-delay estimation results.By simulating the dynamic behavior of a particle swarm,the PSO algorithm effectively searches for the optimal delay estimation,thereby signifi-cantly reducing estimation errors.This approach addresses the issue of significant delay estimation errors in traditional spectrum division methods under low SNR conditions,where susceptibility to noise is pronounced.Simulation results demonstrate that the proposed algorithm accurately estimates groundwave delay across a range of SNR levels,delay dif-ferences,and amplitude ratios,with an error less than 0.5 μs,significantly outperforming traditional IFFT and MUSIC algorithms.Finally,a skywave suppression algorithm was implemented to attenuate the amplitude of the skywave,thereby minimizing its interference with the groundwave signal and enhancing the overall performance of the IFFT.Simulation results indicate that the algorithm achieves over 90%accuracy in groundwave time-delay estimation for SNRs above 0 dB.Further analysis reveals that the algorithm not only enables the separation of sky wave and ground wave under the conditions of strong sky wave and low signal-to-noise ratio but also addresses the error limitations inher-ent in traditional methods.This advancement offers a novel approach for high-precision positioning and decoding of ELoran signals.关键词
增强型罗兰导航/频谱相除/天地波识别/粒子群优化Key words
ELoran/spectral division/sky-ground wave identification/particle swarm optimization分类
信息技术与安全科学引用本文复制引用
邢哲,徐颖,曾凌川..一种基于粒子群优化的新型ELoran信号天地波分离算法[J].信号处理,2025,41(7):1229-1240,12.基金项目
中国科学院青年创新促进会(E33314010D)Youth Innovation Promotion Association(E33314010D) （E33314010D）
