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
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
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
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
基金supported by the National Natural Science Foundation of China (61102106)the Fundamental Research Funds for the Central Universities (HEUCF1208 HEUCF100801)
文摘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.
基金This work was supported by the innovation project of Science and Technology Commission of the Central Military Commission。
文摘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.
文摘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.
文摘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.