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Direction finding of coexisted independent and coherent signals using electromagnetic vector sensor 被引量:3
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作者 Ming Diao Chunlian An 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第4期481-487,共7页
The existing direction of arrival (DOA) estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction findin... The existing direction of arrival (DOA) estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction finding method using an L-shape electromagnetic vector sensors array is proposed. According to this method, the DOAs of the independent signals and the coherent signals are estimated separately, so that the array aperture can be exploited sufficiently. Firstly, the DOAs of the independent signals are estimated by the estimation of signal parameters via rotational invariance techniques, and the influence of the co- herent signals can be eliminated by utilizing the property of the coherent signals. Then the data covariance matrix containing the information of the coherent signals only is obtained by exploiting the Toeplitz property of the independent signals, and an improved polarimetric angular smoothing technique is proposed to de-correlate the coherent signals. This new method is more practical in actual signal environment than common DOA estimation algorithms and can expand the array aperture. Simulation results are presented to show the estimating performance of the proposed method. 展开更多
关键词 direction finding electromagnetic vector sensor polarimetric angular smoothing estimation of signal parameters viarotational invariance technique Toeplitz property.
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Joint 2D-DOA and polarization estimation for sparse nonuniform rectangular array composed of spatially spread electromagnetic vector sensor 被引量:2
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作者 MA Huihui TAO Haihong 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2020年第6期1116-1127,共12页
In this paper,a sparse nonuniform rectangular array based on spatially spread electromagnetic vector sensor(SNRASSEMVS)is introduced,and a method for estimating 2D-direction of arrival(DOA)and polarization is devised.... In this paper,a sparse nonuniform rectangular array based on spatially spread electromagnetic vector sensor(SNRASSEMVS)is introduced,and a method for estimating 2D-direction of arrival(DOA)and polarization is devised.Firstly,according to the special structure of the sparse nonuniform rectangular array(SNRA),a set of accurate but ambiguous direction-cosine estimates can be obtained.Then the steering vector of spatially spread electromagnetic vector sensor(SSEMVS)can be extracted from the array manifold to obtain the coarse but unambiguous direction-cosine estimates.Finally,the disambiguation approach can be used to get the final accurate estimates of 2DDOA and polarization.Compared with some existing methods,the SNRA configuration extends the spatial aperture and refines the parameters estimation accuracy without adding any redundant antennas,as well as reduces the mutual coupling effect.Moreover,the proposed algorithm resolves multiple sources without the priori knowledge of signal information,suffers no ambiguity in the estimation of the Poynting vector,and pairs the x-axis direction cosine with the y-axis direction cosine automatically.Simulation results are given to verify the effectiveness and superiority of the proposed algorithm. 展开更多
关键词 sparse nonuniform rectangular array(SNRA) spatially spread electromagnetic vector sensor(SSEMVS) directioncosine polarization mutual coupling
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2D-DOA for a Monostatic ULA EMVS-MIMO Radar Based on RC-ESPRIT
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作者 Jianlong Wang Junpeng Shi +1 位作者 Fangqing Wen Shuyun Shi 《Journal of Beijing Institute of Technology》 2025年第4期362-372,共11页
Electromagnetic vector sensor(EMVS)embedded multiple-input multiple-output(MIMO)radar is an emerging technology that enables two-dimensional(2D)direction of arrival(DOA)estimation.In this paper,we proposed a low-compl... Electromagnetic vector sensor(EMVS)embedded multiple-input multiple-output(MIMO)radar is an emerging technology that enables two-dimensional(2D)direction of arrival(DOA)estimation.In this paper,we proposed a low-complexity estimation of signal parameters via rotational invariance techniques(ESPRIT)algorithm for uniform linear array(ULA)EMVSMIMO radar at a monostatic,enabling rapid estimation of 2D target angles.Initially,by employing a selection matrix,complexity reduction is applied to the array data,thereby eliminating redundancy in the array data.Subsequently,leveraging the rotation invariance propagator method(PM)algorithm,obtain the estimation of the elevation angle,but due to array sparsity,this estimation exhibits ambiguity.Then,the vector cross-product(VCP)technique is employed to achieve unambiguous 2D-DOA estimation.Finally,the aforementioned estimates are synthesized to obtain highresolution,unambiguous elevation angle estimation.The proposed algorithm is applicable to largescale and spare EMVS-MIMO radar systems and provides higher estimation accuracy compared to existing ESPRIT algorithms.The effectiveness of the algorithm is verified through matrix laboratory(MATLAB)simulations. 展开更多
关键词 electromagnetic vector sensors sparse array DOA estimation reduced complexity propagator method
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Attitude estimation for spacecraft docking based on EMVS array via PARAFAC algorithm
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作者 LIU Bingqi CHEN Guangdong +1 位作者 LIU Zhuhang SONG He 《Journal of Systems Engineering and Electronics》 2025年第3期623-633,共11页
A spacecraft attitude estimation method based on electromagnetic vector sensors(EMVS)array is proposed,which employs the orthogonally constrained parallel factor(PARAFAC)algorithm and makes use of measurements of the ... A spacecraft attitude estimation method based on electromagnetic vector sensors(EMVS)array is proposed,which employs the orthogonally constrained parallel factor(PARAFAC)algorithm and makes use of measurements of the two-dimensional direction-of-arrival(2D-DOA)and polarization angles,aiming to address the issues of incomplete,asynchronous,and inaccurate third-party reference used for attitude estimation in spacecraft docking missions by employing the electromagnetic wave’s three-dimensional(3D)wave structure as a complete third-party reference.Comparative analysis with state-ofthe-art algorithms shows significant improvements in estimation accuracy and computational efficiency with this algorithm.Numerical simulations have verified the effectiveness and superiority of this method.A high-precision,reliable,and cost-effective method for rapid spacecraft attitude estimation is provided in this paper. 展开更多
关键词 parallel factor(PARAFAC)analysis electromagnetic vector sensors attitude estimation state of polarization spacecraft docking
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基于降维变换的低复杂度双基地EMVS-MIMO雷达高分辨多维参数估计 被引量:1
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作者 谢前朋 杜奕航 +3 位作者 孙兵 闫华 潘小义 赵锋 《系统工程与电子技术》 EI CSCD 北大核心 2024年第6期1899-1907,共9页
针对当前算法在实现双基地电磁矢量传感器多输入多输出(electromagnetic vector sensors multiple input multiple output,EMVS-MIMO)雷达的多维参数估计时计算代价较高的问题,通过利用降维变换技术来实现低复杂度的角度参数和极化参数... 针对当前算法在实现双基地电磁矢量传感器多输入多输出(electromagnetic vector sensors multiple input multiple output,EMVS-MIMO)雷达的多维参数估计时计算代价较高的问题,通过利用降维变换技术来实现低复杂度的角度参数和极化参数求解。针对阵列接收数据维度较大问题,通过设计相应的波束空间变换矩阵来实现对阵列接收数据的降维处理。针对算法本身的较高计算复杂度问题,采用低计算复杂度的平行因子分解算法。所提算法能够精确地实现对发射因子矩阵和接收因子矩阵的求解。同时,通过新的旋转不变关系构建新的估计信号参数,可以实现对发射/接收俯仰角的求解。进一步,发射/接收方位角、发射/接收极化角和发射/接收极化相位差的估计可以通过发射/接收空间响应矩阵的重构来实现。仿真实验结果表明,所提算法在降低计算复杂度的同时能够保持优越的多维参数估计性能。 展开更多
关键词 双基地电磁矢量传感器多输入多输出(electromagnetic vector sensors multiple input multiple output EMVS-MIMO)雷达 多维参数估计 波束空间变换 平行因子分解算法
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