Joint 4-D DOA and polarization estimation based on linear tripole arrays

Electromagnetic (EM) vector sensor arrays can track both the polarisation and direction of arrival (DOA) parameters of the impinging signals. For crossed-dipole linear arrays, due to inherent limitation of the structure, it can only track one DOA parameter and two polarisation parameters. This problem could be solved by extending the geometry to a two-dimensional (2-D) rectangular array so that both the azimuth and elevation angles of the signal can be estimated. In this paper, instead of extending the array to a higher dimension, we replace the crossed-dipoles by tripoles and construct a linear tripole array. It will be shown that such a structure can estimate the 2-D DOA and 2-D polarisation information effectively and a dimension-reduction based MUSIC algorithm is developed so that the 4-D estimation problem can be simplified to two separate 2-D estimation problems, significantly reducing the computational complexity of the solution

Beamforming and Direction of Arrival Estimation Based on Vector Sensor Arrays

Array signal processing is a technique linked closely to radar and sonar systems. In communication, the antenna array in these systems is applied to cancel the interference, suppress the background noise and track the target sources based on signals'parameters. Most of existing work ignores the polarisation status of the impinging signals and is mainly focused on their direction parameters. To have a better performance in array processing, polarized signals can be considered in array signal processing and their property can be exploited by employing various electromagnetic vector sensor arrays. In this thesis, firstly, a full quaternion-valued model for polarized array processing is proposed based on the Capon beamformer. This new beamformer uses crossed-dipole array and considers the desired signal as quaternion-valued. Two scenarios are dealt with, where the beamformer works at a normal environment without data model errors or with model errors under the worst-case constraint. After that, an algorithm to solve the joint DOA and polarisation estimation problem is proposed. The algorithm applies the rank reduction method to use two 2-D searches instead of a 4-D search to estimate the joint parameters. Moreover, an analysis is given to introduce the difference using crossed-dipole sensor array and tripole sensor array, which indicates that linear crossed-dipole sensor array has an ambiguity problem in the estimation work and the linear tripole sensor array avoid this problem effectively. At last, we study the problem of DOA estimation for a mixture of single signal transmission (SST) signals and duel signal transmission (DST) signals. Two solutions are proposed: the first is a two-step method to estimate the parameters of SST and DST signals separately; the second one is a unified one-step method to estimate SST and DST signals together, without treating them separately in the estimation process

Study of four-dimensional DOA and polarisation estimation with crossed-dipole and tripole arrays

Electromagnetic (EM) vector sensor arrays can track both the polarisation and direction of arrival (DOA) of the impinging signals. For linear crossed-dipole arrays, as shown by our analysis, due to inherent limitation of the structure, it can only track one DOA parameter and two polarisation parameters. For full four-dimensional (4-D, 2 DOA and 2 polarization parameters) estimation, we could extend the linear crossed-dipole array to the planar case. In this paper, instead of extending the array geometry, we replace the crossed-dipoles by tripoles and construct a linear tripole array. It is proved that such a structure can estimate the 2-D DOA and 2-D polarisation information effectively in general and a dimension-reduction based MUSIC algorithm is developed so that the 4-D estimation problem can be simplified into two separate 2-D estimation problems, significantly reducing the computational complexity of the solution. The Cramr-Rao Bound (CRB) is also derived as a reference for algorithm performance. A brief comparison between the planar crossed-dipole array and the linear tripole array is performed at last, showing that although the planar structure has a better performance, it is achieved at the cost of increased physical size

Direction finding for a mixture of single-transmission and dual-transmission signals

Currently, most of existing research in direction of arrival (DOA) estimation is focused on single signal transmission (SST) based signal. However, to make full use of the degree of freedom provided by the system in the polarisation domain, the dual signal transmission (DST) model has been adopted more and more widely in wireless communications. In this work, a DOA estimation method for a mixture of SST and DST signals (referred to as the mixed signal transmission (MST) model) is proposed. To our best knowledge, this is the first time to study the DOA estimation problem for such an MST model. There are two steps in the proposed method, which deals with the two kinds of signals separately. The performance of the proposed method is compared with the Cramér-Rao Bound (CRB) based on computer simulations

Joint DOA and polarisation estimation with crossed-dipole and tripole sensor arrays

Electromagnetic vector sensor arrays can track both the polarisation and direction of arrival (DOA) of the impinging signals. For linear crossed-dipole arrays, as shown by our analysis, due to inherent limitation of the structure, it can only track one DOA parameter and two polarisation parameters. For full four-dimensional (4-D, 2 DOA and 2 polarization parameters) estimation, we could extend the linear crossed-dipole array to the planar case. In this paper, instead of extending the array geometry, we replace the crossed-dipoles by tripoles and construct a linear tripole array. Detailed proof shows that such a structure can estimate the 2-D DOA and 2-D polarisation information effectively in general. A brief comparison between the planar crossed-dipole array and the linear tripole array is performed at last, showing that although the planar structure has a better performance, it is achieved at the cost of increased physical size

Crossed-dipole arrays for asynchronous DS-CDMA systems

Published versio

Simultaneous Source Localization and Polarization Estimation via Non-Orthogonal Joint Diagonalization with Vector-Sensors

Joint estimation of direction-of-arrival (DOA) and polarization with electromagnetic vector-sensors (EMVS) is considered in the framework of complex-valued non-orthogonal joint diagonalization (CNJD). Two new CNJD algorithms are presented, which propose to tackle the high dimensional optimization problem in CNJD via a sequence of simple sub-optimization problems, by using LU or LQ decompositions of the target matrices as well as the Jacobi-type scheme. Furthermore, based on the above CNJD algorithms we present a novel strategy to exploit the multi-dimensional structure present in the second-order statistics of EMVS outputs for simultaneous DOA and polarization estimation. Simulations are provided to compare the proposed strategy with existing tensorial or joint diagonalization based methods

Direction of arrival estimation based on a mixed signal transmission model employing a linear tripole array

Direction of arrival (DOA) estimation is an important topic in array signal processing. Currently, most research activities are focused on the single signal transmission (SST) type of signals, i.e. only one physical signal is used to carry the information from a transmitter to a receiver with a given polarisation setting. However, to make full use of the degrees of freedom in spatial domain, signals based on the dual signal transmission (DST) model are more and more widely used, i.e., two signals with different polarisations carrying different information are employed for communication between the transmitter and the receiver. But there is rarely any work on DOA estimation of DST signals. Motivated by such a problem, the paper proposes two methods for DOA estimation of signals based on a mixed signal transmission (MST) model, i.e., a mixture of SST and DST signals. The first method provides a two-step solution and estimate the DOA of the SST signals first and then the DST signals second. The second method estimates the DOA of all signals in one step. Moreover, CRB (Cramér-Rao Bound) for the estimation model is derived to evaluate the performance the proposed methods

Joint DOA, range, and polarization estimation for rectilinear sources with a COLD array

In this paper, a novel localization method for near-field (NF) rectilinear or strictly noncircular sources with a symmetric uniform linear array of rgb0,0,0cocentered orthogonal loop and dipole (COLD) antennas is proposed. Based on the rank reduction (RARE) principle, the multiple parameters including direction of arrival (DOA), range and polarization parameters are separated. Furthermore, a closed-form solution for polarization parameters and noncircular phases is also provided. The deterministic Cramer-Rao bound (CRB) of the estimation problem under consideration is also derived as a benchmark. Numerical simulations are provided to demonstrate the effectiveness of the proposed method