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EMVS互质面阵张量波束成形

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相比于标量传感器均匀阵列,电磁矢量传感器(electromagnetic vector sensor,EMVS)稀疏阵列能够在降低系统软硬件成本的同时感知更大范围、更高维度的空间信号信息,并通过精尖波束扫描实现信源测向性能的综合提升.然而,传统基于矩阵信号建模的波束成形算法难以利用EMVS接收信号的多维结构化信息,且存在由阵元稀疏排布所引入的虚峰干扰问题.为了应对上述挑战,提出了面向EMVS互质面阵的张量波束成形算法,有效利用了空域互质采样的波束分布特性和张量信号处理的优势实现指向性张量波束扫描测向.具体而言,将EMVS互质面阵中稀疏均匀子面阵的接收信号表示为一对涵盖多维度空间电磁信息的高维张量,并从张量信号空域滤波的准则出发,设计面向稀疏均匀子面阵的张量化最小方差无畸变响应优化问题.为了克服由上述优化问题中张量内积项所造成的传统求解方法失效难题,提出通过张量权重的canonical polyadic分解,将原始张量化最小方差无畸变响应优化问题转换为对应波达方向信息维度与极化状态信息维度的子问题,并基于各子问题的局部最优解设计交替迭代求解方法,以获得张量权重的全局最优解.进而,基于张量空间的质数分解唯一性分析,理论证明一对满足互质阵元排布的稀疏均匀子面阵所对应的虚峰具有互不重叠特性,并提出张量波束功率的互质合成处理方法,以此构造具备精尖主瓣且虚峰抵消的张量波束功率图,从而实现多信源空间方位的精准估计.仿真结果验证了所提EMVS互质面阵张量波束成形算法的有效性.
Tensor Beamforming for EMVS Coprime Planar Array
Compared to conventional uniform scalar sensor arrays,electromagnetic vector sensor(EMVS)sparse arrays can obtain multi-spatial electromagnetic information with reduced system costs,and the precise beam scanning offers im-proved direction-of-arrival(DOA)estimation performance.However,traditional matrix-based beamforming methods fail to exploit the structural characteristics of the signals received by an EMVS array,and cannot suppress the ambiguous sid-elobes produced by a sparse sensor deployment.To cope with these issues,a tensor beamforming algorithm is proposed for an EMVS coprime planar array,where the coprime beam distribution and tensor processing are incorporated for accurate beam scanning.In particular,the multi-spatial electromagnetic signals received at the coprime subarrays are represented by a pair of tensors.The principle of tensor signal filtering was investigated,and tensor minimum-variance distortionless re-sponse optimization problems for a pair of tensor weights were designed.However,the tensor weight optimization prob-lems could not be solved by conventional approaches.To overcome this challenge,the tensor weights were respectively de-composed via canonical polyadic decomposition,such that the original problems could be decomposed into interconnected sub-problems corresponding to the dimensions of the DOA and polarization information.Based on the local optimums of the sub-problems,the globally optimal tensor beamformer weights could be obtained through alternative optimization.Fur-thermore,based on the prime factorization theorem in the tensorial domain,the beam distribution property of the sparse subarrays was theoretically analyzed.The results were used as the basis for a coprime synthesis method to suppress ambigu-ous sidelobes.A tensor beam power pattern with a sharp mainlobe and suppressed sidelobes could be formulated to achieve an accurate DOA estimation.Simulation results demonstrated the effectiveness of the proposed algorithm.

electromagnetic vector sensorcoprime planar arraytensor beamformingcoprime synthesisdirection-of-arrival estimation

郑航、周成伟、王勇、史治国

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浙江大学信息与电子工程学院,浙江杭州 310027

浙江省协同感知与自主无人系统重点实验室,浙江杭州 310015

浙江大学国际联合创新中心,浙江海宁 314400

电磁矢量传感器 互质面阵 张量波束成形 互质合成 信源测向

国家自然科学基金国家自然科学基金国家自然科学基金浙江省自然科学基金浙江大学教育基金会启真人才基金杭州未来科技城5G开放实验平台

62271444U21A2045661901413LZ23F010007

2024

10.16798/j.issn.1003-0530.2024.02.003

信号处理
中国电子学会

信号处理

CSTPCD北大核心
影响因子：1.502
ISSN：1003-0530
年,卷(期)：2024.40(2)
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