电子学报2025，Vol.53Issue(10)：3529-3539,11.DOI:10.12263/DZXB.20250490
基于几何代数的电磁矢量传感器阵列抗强干扰参数估计算法
Joint DOA and Polarization Estimation of Unequal Power Sources for Electromagnetic Vector-Sensor Array Based on Geometric Algebra
摘要
Abstract
With the widespread application of drone swarms in civilian fields,it is crucial for drones effective regula-tion to obtain some key state parameters of drone swarms such as spatial angles and signal polarization which are acquired by utilizing joint direction of arrival(DOA)and polarization estimation based on electromagnetic vector sensor arrays(EMVA).However,in simultaneous detection of non-cooperative multi unmanned aerial vehicles(UAVs)of drone swarms in a com-plex electromagnetic environment,the joint DOA and polarization estimation performance of traditional methods on real UAVs signal sources with weak power usually deteriorates when interference signal with high power impinge on an EMVA.Therefore,a joint DOA and polarization estimation method with invariant property of noise subspace(IPNS)based on geo-metric algebra of Euclidean 3-space(G3)model is proposed.Firstly,the impact of the coexistence of strong and weak signals on the performance of parameter estimation of traditional subspace methods based on G3 is studied by using expected spec-trum of multiple signal classification method based on geometric algebra of Euclidean 3-space framework(G3-MUSIC).Then the invariant property of G3 noise subspace of array covariance matrix is theoretically proved.The performance of joint DOA and polarization estimation on real targets with weak power is improved by utilizing the characteristic of the meth-od that the eigenvalues of G3 noise subspace remain unchanged when the incident signal power is increased.Simultaneously,by theoretically deriving the impact of changes in virtual source polarization parameters on the invariance of the noise sub-space of the array covariance matrix based on G3,it is proved that 4-dimensional spectral peak search is not required by the proposed method which realizes joint DOA and polarization estimation only by 2-dimensional spectral peak search.It is veri-fied by simulation that the weak signals cannot be distinguished by the traditional methods as the power of strong interference signals increases.At the same time,simulation verified that when high power signals impinge on an EMVA,the proposed method outperforms the traditional methods in terms of different signal-to-noise ratios,power ratios between strong and weak signals,and noise correlations.Compared with the traditional methods based on invariant noise subspace,the signal to noise ratio threshold of direction finding of the weak source was reduced by more than 3 dB,the accuracy of joint DOA and polarization estimation was enhanced by 88.7%,and the calculation amount was reduced by more than 97.11%.The pro-posed method can be used for obtaining locations of multiple UAVs and polarization parameters of signals emitted by multi-ple UAVs in non-cooperative drone swarms in complex electromagnetic environments,especially in circumstance of inter-ference with high power,and has potential application value in scenarios such as anti-interference for mobile wireless com-munication based on UAVs platforms.关键词
信号参数估计/抗强干扰/电磁矢量传感器/几何代数/不变噪声子空间/无人机蜂群Key words
parameter estimation of sources/resisting intensive interference/electromagnetic vector sensor/geomet-ric algebra/invariant property of noise subspace/drone swarms分类
信息技术与安全科学引用本文复制引用
王通,刘尚合,陈东伟,金梦哲,方庆园..基于几何代数的电磁矢量传感器阵列抗强干扰参数估计算法[J].电子学报,2025,53(10):3529-3539,11.基金项目
国家自然科学基金(No.61801309) （No.61801309）
国家重点实验室开放课题(No.JCKYS2022DC07) National Natural Science Foundation of China(No.61801309) （No.JCKYS2022DC07）
Opening Foundation of Na-tional Key Laboratory(No.JCKYS2022DC07) （No.JCKYS2022DC07）
