摘要
针对多个相干信号源入射极化敏感阵列的问题,提出一种能够高效解多个相干信号源的波达方向(Destination of Arrival,DOA)估计方法,并通过移动平台和正交偶极子阵列的协同作用,减少对观测次数的需求,从而提高相干信号DOA估计的效率和精度。该算法利用由多对正交双偶极子组成的阵列接收到的数据,在极化域内进行平滑处理,恢复信号源协方差矩阵的秩。由于极化阵列具有较强的极化敏感性,因此在极化域内的平滑能够有效减小信号间的相关性,帮助恢复协方差矩阵的秩;通过移动平台使阵列产生运动,针对移动后的不同阵列,进行极化平滑后的接收信号协方差矩阵的计算。通过类似空间平滑的原理,计算出这些阵列的平均阵列输出协方差矩阵,在此过程中,信号的协方差矩阵得以恢复为满秩;采用多重信号分类算法(Multiple Signal Classification Algorithm,MUSIC)对恢复后的协方差矩阵进行DOA估计,从而获取多个信号源的方向信息。通过联合在极化域和平滑时域中的解相干技术,该算法将运动平台解相干所需的观测次数缩减至原来的一半,从而显著提高了相干信号DOA估计的效率。仿真结果表明,所提算法在多个相干信号源的DOA估计中,能够有效降低由于信号相干性引起的估计误差,显著提升估计精度。仿真结果验证了该方法的有效性。
To address the issue of multiple coherent signal sources incident on a polarization-sensitive array,an efficient direction of arrival(DOA)estimation method that decorrelates multiple coherent signal sources is proposed.By utilizing the cooperative effect of a moving platform and an orthogonal dipole array,the method reduces the required number of observations,thereby improving the efficiency and accuracy of DOA estimation for coherent signals.The algorithm first smooths the data received in the polarization domain by an array composed of multiple pairs of orthogonal dipoles and restores the rank of the signal source covariance matrix.Smoothing in the polarization domain effectively reduces the correlation between signals because of the strong polarization sensitivity of the array,which helps recover the rank of the covariance matrix.By moving the platform to induce motion into the arrays,the covariance matrix of the received signals was calculated for each moving array after polarization smoothing.Using a method similar to spatial smoothing,the average covariance matrix of these arrays was computed,to restore the signal covariance matrix to full rank.The multiple signal classification(MUSIC)algorithm was applied to the recovered covariance matrix for DOA estimation,thereby obtaining the direction information of multiple signal sources.By jointly resolving decorrelation in the polarization domain and smoothing in the time domain,the algorithm reduces the number of observations required for decorrelation by the moving platform to half the original number,thereby significantly improving the efficiency of DOA estimation for coherent signals.Simulation results demonstrated that the proposed algorithm effectively reduces the estimation errors caused by signal coherence from multiple coherent signal sources in DOA estimation,thereby significantly improving estimation accuracy.The simulation results validated the effectiveness of the proposed method.In conclusion,the proposed method successfully improves the efficiency and accuracy of DOA estimation for multiple coherent signal sources by leveraging joint decorrelation in the polarization domain and time domain smoothing.
作者
刘瑞
郭沐然
孙昭乾
LIU Rui;GUO Muran;SUN Zhaoqian(Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology,College of Information and Communication Engineering,Harbin Engineering University,Harbin,Heilongjiang 150001,China;Beijing Institute of Telemetry Technology,Beijing,100000,China)
出处
《信号处理》
北大核心
2025年第7期1219-1228,共10页
Journal of Signal Processing
基金
国家自然科学基金(62001136)。
关键词
解相干
极化平滑
移动阵列
decoherence
polarization smoothing
moving array
