TY - GEN
T1 - Efficient Localization Algorithm for Spatially Displaced Electromagnetic Vector Sensor
AU - Li, Wenqiao
AU - Xie, Jian
AU - Wang, Qiuping
AU - Wang, Yuexian
AU - Yang, Xin
AU - Qu, Jiaqing
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Electromagnetic vector sensors (EMVS) have promising application potential in array signal processing. but the performance of the existing algorithms might be degraded by the mutual coupling and near-field effects in practical EMVS arrays. To address this problem, a novel closed-form localization algorithm is proposed for a spatially displaced EMVS. First, the six-component EMVS is divided into dipole and loop triads, which are displaced. Then, based on the eigenstructure of the augmented EMVS signal model, direction and polarization parameters are obtained from the two triads successively. Finally, the range parameters are calculated by an exact trigonometric geometric expression. Compared with the traditional methods, the proposed algorithm is computationally more efficient and avoids the bias introduced by quadric approximation. Moreover, the spacing between the two triads can be extended by more than a half wavelength. And the spacing of this size could decrease the mutual coupling effect. Simulation results make evidence that the proposed algorithm for multiple near-field sources parameter estimation are both the efficient and effective.
AB - Electromagnetic vector sensors (EMVS) have promising application potential in array signal processing. but the performance of the existing algorithms might be degraded by the mutual coupling and near-field effects in practical EMVS arrays. To address this problem, a novel closed-form localization algorithm is proposed for a spatially displaced EMVS. First, the six-component EMVS is divided into dipole and loop triads, which are displaced. Then, based on the eigenstructure of the augmented EMVS signal model, direction and polarization parameters are obtained from the two triads successively. Finally, the range parameters are calculated by an exact trigonometric geometric expression. Compared with the traditional methods, the proposed algorithm is computationally more efficient and avoids the bias introduced by quadric approximation. Moreover, the spacing between the two triads can be extended by more than a half wavelength. And the spacing of this size could decrease the mutual coupling effect. Simulation results make evidence that the proposed algorithm for multiple near-field sources parameter estimation are both the efficient and effective.
KW - array signal processing
KW - direction-of-arrival estimation
KW - electromagnetic vector sensors
KW - near-field source localization
KW - polarization
UR - http://www.scopus.com/inward/record.url?scp=85080964445&partnerID=8YFLogxK
U2 - 10.1109/ICUS48101.2019.8996001
DO - 10.1109/ICUS48101.2019.8996001
M3 - 会议稿件
AN - SCOPUS:85080964445
T3 - Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
SP - 961
EP - 966
BT - Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Y2 - 17 October 2019 through 19 October 2019
ER -