An Enumerative NonLinear Programming approach to direction finding with a general spatially spread electromagnetic vector sensor array

Authors:
Yang Li;Jian Qiu Zhang
Affiliations:
Department of Electronic Engineering, Fudan University, Shanghai 200433, PR China;Department of Electronic Engineering, Fudan University, Shanghai 200433, PR China
Venue:
Signal Processing
Year:
2013

Citing 18
Cited 0

A Multilinear Singular Value Decomposition

SIAM Journal on Matrix Analysis and Applications
Singular value decomposition of quaternion matrices: a new tool for vector-sensor signal processing

Signal Processing
Cross-product algorithms for source tracking using an EM vector sensor

ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05
Direction-of-arrival estimation via twofold mode-projection

Signal Processing
Quad-quaternion music for DOA estimation using electromagnetic vector sensors

EURASIP Journal on Advances in Signal Processing
Classical and Modern Direction-of-Arrival Estimation

Classical and Modern Direction-of-Arrival Estimation
Direction finding via biquaternion matrix diagonalization with vector-sensors

Signal Processing
Higher-Order SVD-Based Subspace Estimation to Improve the Parameter Estimation Accuracy in Multidimensional Harmonic Retrieval Problems

IEEE Transactions on Signal Processing - Part II
Estimating directions of arrival of completely and incompletelypolarized signals with electromagnetic vector sensors

IEEE Transactions on Signal Processing
“Vector Cross-Product Direction-Finding” With an Electromagnetic Vector-Sensor of Six Orthogonally Oriented But Spatially Noncollocating Dipoles/Loops

IEEE Transactions on Signal Processing
Vector-sensor array processing for electromagnetic sourcelocalization

IEEE Transactions on Signal Processing
ESPRIT-based 2-D direction finding with a sparse uniform array ofelectromagnetic vector sensors

IEEE Transactions on Signal Processing
Closed-form eigenstructure-based direction finding using arbitrarybut identical subarrays on a sparse uniform Cartesian array grid

IEEE Transactions on Signal Processing
Parallel factor analysis in sensor array processing

IEEE Transactions on Signal Processing
Source localization using vector sensor array in a multipath environment

IEEE Transactions on Signal Processing
MUSIC Algorithm for Vector-Sensors Array Using Biquaternions

IEEE Transactions on Signal Processing
Quaternion-MUSIC for vector-sensor array processing

IEEE Transactions on Signal Processing
Sparse Sensing With Co-Prime Samplers and Arrays

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.08

Visualization

Abstract

In this paper, the geometry of a general spatially spread electromagnetic vector sensor (SSEMVS) array is firstly presented. This array has a special cross product structure of the array manifold vector. The g parameters are then defined to uniquely characterize the cross product. With g parameters, the identifiability analysis of the cross product vector based direction finding algorithms of the general SSEMVS array is carried out. The analysis shows that the array has to be carefully designed to avoid ambiguity directions. Finally, a cross-product based Enumerative NonLinear Programming (ENLP) algorithm for the direction of arrival (DOA) estimation with the general SSEMVS array is proposed. The algorithm finds the optimum estimation of DOA in least square sense. Extensive simulations show that the proposed algorithm outperforms existing algorithms, and can approach the CRB effectively.