Polarization Sensitive Array Research Articles

Auxiliary polarization sensitive array (APSA) and performance analysis

In this paper, an auxiliary polarization sensitive array(APSA) model is proposed, which can reduce the cost of receiving polarization information and further improve the performance of the filter. On the basis of a single polarized linear array, a partial array element is selected to transform into an orthogonal dipole array element, so that the array has the ability to receive polarization information. At the same time a new steering vector and received signal model are constructed. Received signal is filtered based on that, and the filtering capability and performance of the array are analysed in detail. The computer simulation shows that the proposed array model can effectively improve the filtering performance of the traditional array. The simplified structure can effectively reduce the cost of the traditional polarization sensitive array on the premise of guaranteeing the signal to noise ratio of the receiving letter.

Two-Dimensional DOA Estimation for Polarization Sensitive Array Consisted of Spatially Spread Crossed-Dipole

This paper studies the problem of 2-D direction of arrival (DOA) estimation with polarization sensitive array (PSA), in which polarized vector sensor is consisted of spatially spread crossed-dipole (SSCD). It is well known that crossed-dipole vector sensor can obtain all the polarization information including HH, HV, VH, and VV. Consequently, it is one of the most popularly polarized vector sensor. Unfortunately, in the existing works, it is difficult to effectively solve the problem of DOA estimation with SSCD array. Motivated by this, this paper presents a sparse rectangular SSCD-PSA to solve this problem. First, the ESPRIT algorithm is adopted to calculate the high accuracy but ambiguous direction cosine estimation. Second, the polarization information in the data covariance matrix is incorporated into incident source to form a block sparse signal model, and then, the block orthogonal matching pursuit is used to get a coarse reference direction cosine estimation. At last, a finally fine 2-D DOA estimation can be obtained by disambiguation process using the combination of high accuracy but ambiguous and coarse reference direction cosine estimations. The proposed algorithm obtains the 2-D DOA estimation under the lowest components polarized vector sensor and keeps the advantage of low mutual coupling. The simulation results prove the effectiveness and correctness of the proposed algorithm.

RAM-based angle estimation with linear spatially separated polarisation sensitive array

ABSTRACTTwo-dimensional direction of arrival (2D-DOA) and polarisation estimation of multiple incident signals for linear spatially separated polarisation sensitive array (SS-PSA) is investigated with reweighted atomic norm minimisation (RAM) algorithm. Single vector sensor in this paper is composed of spatially separated three dipoles and three loops. Firstly, the received data of the proposed array with single snapshot is converted into the new received data with six virtual snapshots. Each virtual snapshot data is the data sensing by dipoles or loops located in the same direction. Secondly, based on each virtual snapshot data, the complex amplitudes and frequencies of the virtual signals are restored using RAM algorithm. Lastly, 2D-DOA and polarisation angles are derived according to the restored complex amplitudes and frequencies. Simulation results demonstrate that the RAM algorithm used in 2D-DOA and polarisation estimation with SS-PSA exhibits superior performance, which is better compared with polarisation multiple signal classification (PMUSIC) algorithm and rotational invariance techniques (ESPRIT) algorithm.

Polarization Smoothing Generalized MUSIC Algorithm with Polarization Sensitive Array for Low Angle Estimation.

Direction of Arrival (DOA) estimation of low-altitude targets is difficult due to the multipath coherent interference from the ground reflection image of the targets, especially for very high frequency (VHF) radars, which have antennae that are severely restricted in terms of aperture and height. The polarization smoothing generalized multiple signal classification (MUSIC) algorithm, which combines polarization smoothing and generalized MUSIC algorithm for polarization sensitive arrays (PSAs), was proposed to solve this problem in this paper. Firstly, the polarization smoothing pre-processing was exploited to eliminate the coherence between the direct and the specular signals. Secondly, we constructed the generalized MUSIC algorithm for low angle estimation. Finally, based on the geometry information of the symmetry multipath model, the proposed algorithm was introduced to convert the two-dimensional searching into one-dimensional searching, thus reducing the computational burden. Numerical results were provided to verify the effectiveness of the proposed method, showing that the proposed algorithm has significantly improved angle estimation performance in the low-angle area compared with the available methods, especially when the grazing angle is near zero.

Polarization Sensitive Array Based Physical-Layer Security

We propose a comprehensive framework exploiting the polarization sensitive array (PLA) to improve the physical layer security of wireless communications. More specifically, the polarization difference among signals is utilized to improve the secrecy rate of wireless communications, especially when these signals are spatially indistinguishable. We firstly investigate the PLA based secure communications for point-to-point wireless systems from the perspectives of both total power minimization and secrecy rate maximization. We then take a step further to apply the PLA based secure beamforming designs to relaying networks. The secrecy rate maximization for relaying networks is discussed in detail under both the perfect channel state information and the polarization sensitive array pointing error. In the later case, a robust scheme to achieve secure communications for relaying networks is proposed. Simulation results show that the proposed PLA based algorithms achieve lower total power consumption and better security performance compared with the conventional scalar array designs, especially under challenging environments where all received signals at destination are difficult to be distinguished from the spatial domain.

Robust tensor beamforming for polarization sensitive arrays

Robustness is of great importance in array beamforming. With the purpose of improving the robustness of the array beamforming, methods using tensor operations are explored in this paper. Specifically, a higher-dimension tensor decomposition method to construct minimum variance distortionless response model (TD-MVDR) is proposed under the assumption that the polarization sensitive array enjoys the multilinear translation invariant property. Whereafter, the proposed TD-MVDR algorithm is incorporated into the improved conjugate gradient least squares method called TD-ICGLS to obtain a better robustness. Considering that the degradation caused by the presence of the random steering vector mismatches, we derive a diagonal loading model for TD-ICGLS to improve the robustness of it. Moreover, a method for determining the loading level is put forward as the key step for the proposed robust tensor beamformer. Results demonstrate that the proposed diagonal loading TD-ICGLS beamformer yields more robust performance than existing matrix-based solutions, such as global beamforming, while operating in a challenging scenario where the signal-of-interest power approaches the jamming power. Meanwhile, an improvement of the computational complexity in terms of TD-ICGLS is noteworthy.

Polarisation smoothing generalised MUSIC algorithm with PSA monostatic MIMO radar for low angle estimation

The polarisation smoothing generalised multiple signal classification (MUSIC) algorithm for low angle estimation with polarisation sensitive array (PSA) monostatic multiple-input multiple-output (MIMO) radar is proposed. The proposed method takes advantage of the virtual aperture of the MIMO radar and the polarisation diversity of the PSA simultaneously to improve the resolution, which has better performance than generalised MUSIC algorithm when the direct and the reflected signals are out of phase. Simulation results are presented to verify the effectiveness of the proposed method.

Spatial polarimetric time-frequency distribution based DOA estimation: combining ESPRIT with MUSIC

Spatial spectrum estimation technology has always been the focused research project in an array signal processing of High Frequency Surface Wave Radar (HFSWR). This paper takes the polarization sensitive array for the model and combines with time-frequency analysis method for DOA estimation of HFSWR echo signals, which can make full use of the spatial, time-frequency, and polarized domain information of signals. The time-frequency MUSIC and ESPRIT algorithms of integrated polarization information are studied, and the improved algorithm is proposed based on the advantages and disadvantages of both algorithms. The improved algorithm first estimates the azimuth angles of signals roughly with the polarized time-frequency ESPRIT algorithm and then determines a small scope centered on each azimuth. Within the scope, a more accurate DOA-estimated value is got by spectral peak search with MUSIC algorithm, so it can save computation time on the basis of accuracy of the DOA estimation, and their performance is analyzed by computer simulations.

The Spatially Separated Polarization Sensitive FDA-MIMO Radar: A New Antenna Structure for Unambiguous Parameter Estimation

Joint DOA-range-polarization estimation with a novel radar system, i.e., spatially separated polarization sensitive random frequency diverse array based on multiple-input multiple-output (SS-PSRFDA-MIMO) radar, is discussed. The proposed array can obtain not only unambiguous range estimation but also polarization parameter estimation. Firstly, the signal model of SS-PSRFDA-MIMO radar is constructed. Secondly, dimension reduction multiple signal classification (DR-MUSIC) algorithm is extended to parameter estimation with the proposed array. Last, simulations demonstrate the proposed algorithm is effective to estimate parameter, and the performance of proposed array is better than that of polarization sensitive frequency diverse array based on MIMO radar. It is worth mentioning that the Cramér–Rao lower bound (CRLB) of range estimation with the proposed array is much lower than that of PSFDA-MIMO radar.

Successive ESPRIT Algorithm for Joint DOA-Range-Polarization Estimation With Polarization Sensitive FDA-MIMO Radar

Polarization sensitive frequency and frequency diversity array (FDA)-MIMO (PSFDA-MIMO) hybrid radar is an emerging technology. The existing algorithms for parameter estimation with PSFDA-MIMO radar need multiple-dimensional searches, whose computational complexity is high. To reduce the computational complexity, in this paper, a search-free algorithm is proposed to estimate 4-D parameters with PSFDA-MIMO radar. First, direction of arrival (DOA) is estimated with the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm using the rotational invariance of the receiving array. Second, based on the estimated DOA parameter, range estimation is obtained with the ESPRIT algorithm using the rotational invariance of the transmitting array. Finally, polarization parameters are estimated with the ESPRIT algorithm using the rotational invariance of the polarization domain. Thus, the proposed algorithm is termed the successive ESPRIT algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm.

Fast PARAFAC decomposition with application to polarization sensitive array parameter estimations

In tensor theory, the parallel factorization (PARAFAC) decomposition expresses a tensor as the sum of a set of rank-1 tensors. By carrying out this numerical decomposition, mixed sources can be separated or unknown system parameters can be identified, which is the so-called blind source separation or blind identification. In this paper we propose a numerical PARAFAC decomposition algorithm. Compared to traditional algorithms, we speed up the decomposition in several aspects, i.e., search direction by extrapolation, suboptimal step size by Gauss-Newton approximation, and linear search by n steps. The algorithm is applied to polarization sensitive array parameter estimation to show its usefulness. Simulations verify the correctness and performance of the proposed numerical techniques.

High Accuracy and Unambiguous 2D-DOA Estimation With an Uniform Planar Array of “Long” Electric-Dipoles

For the polarization sensitive array considered in the most current literature, the physical length of the electric-dipole is less than 0.1 of a wavelength, and the radiation efficiency of this “short” electric-dipole is too low. Therefore, it is of great practical significance to study the array of “long” electric-dipole (the physical length lies within the range of [0.1, 1] of a wavelength). This paper constructs a sparse uniform planar array composed of the orthogonally oriented and spatially separated “long” tri-electric-dipole and proposes an algorithm to solve the problem of the 2-D direction-of-arrival (2-D-DOA) estimation with the proposed array. It is worth mentioning that the proposed algorithm does not require the prior knowledge of polarization parameters. Moreover, the spatially separated structure of the vector sensor is beneficial to engineering practice. Simulations are conducted to verify the effectiveness of the proposed algorithm.

Real-Valued 2D MUSIC Algorithm Based on Modified Forward/Backward Averaging Using an Arbitrary Centrosymmetric Polarization Sensitive Array.

Two-dimensional multiple signal classification (MUSIC) algorithm based on polarization sensitive array (PSA) has excellent performance. However, it suffers a high computational complexity due to a multitude of complex operations. In this paper, we propose a real-valued two-dimensional MUSIC algorithm based on conjugate centrosymmetric signal model, which is applicable to arbitrary centrosymmetric polarization sensitive array. The modified forward/backward averaging, which can be applied to the PSA, is presented. Hence, the eigen-decomposition analysis process and spectrum function computation are converted into real domain, prominently reducing the computational complexity. Then, the direction-of-arrival (DOA) estimation is decoupled from the polarization parameter estimation so that the four-dimensional spectral peak search process is avoided. The theoretical computational complexity is discussed and the Cramer-Rao bound (CRB) of DOA estimation is derived in this paper. The simulation results indicate that the proposed algorithm achieves superior accuracy in DOA estimation and has low computational complexity.

The Modified Model of Unknown Correlated Noise Fields under the Polarization Sensitive Array

The Modified Model of Unknown Correlated Noise Fields under the Polarization Sensitive Array

A Low-Complexity DOA and Polarization Method of Polarization-Sensitive Array.

This paper proposes a low-complexity method to estimate the direction of arrival and polarization based on the polarization sensitive array (PSA) which is composed of cross-dipoles. We built a half-quaternions model through the Cayley–Dickson form to remove the redundant information. Then, the directions of arrival (DOAs) were estimated via the root-MUSIC algorithm. Finally, the polarizations were estimated by generalized eigenvalue method. Unlike some existing searching algorithms, such as multiple signal classification (MUSIC), this method can avoid the peak searching and maintains high estimation accuracy. Moreover, we use the oblique projection operators to filter out the interference signals which are decoys of the target signal. Simulation results demonstrate the effectiveness and favorable performance of the proposed method.

80-3: A Fast 2D-3D Switchable Display Using a Polymeric Lenticular Lens Array and an Electrically Suppressed Ferroelectric Liquid Crystal

In this article, we demonstrate a compact fast 2D-3D switchable display device which is achieved by a polarization sensitive micro-lens array and an electrically suppressed helix ferroelectric liquid crystal (ESHFLC) cell. The ESHFLC, functioned as a polarization selector, has a high contrast ratio over 3K: 1 of two perpendicular polarization states, under a low applied electric field 1.7 V/µm. In order to get a DC balancing of the ESHFLC, we design two particular driving scheme for 2D and 3D. Due to the fast response of FLC, we are able to switch between the two display modes in microseconds. Thus such an integrated 2D to auto-stereoscopic 3D switchable display with advantages like low power consumption, ultrafast response and good 3D performance can be widely explored and utilized in TV, cell phones and etc.

Trilinear decomposition‐based spatial‐polarisational filter method for deception jamming suppression of radar

This study focuses on the problem of deception jamming suppression for a radar system and an effective spatial-polarisational filter strategy is outlined based on the spatial and polarisational parameter joint estimates. It can make the false target filtered effectively and the desired target remained with an improved signal-to-jammer-noise ratio. In this scheme, the trilinear decomposition model is first employed to obtain paired 2D direction of arrive and polarisation parameter joint estimates of the target and jammer. Then a spatial-polarisational oblique projection filter operator based on the joint estimates is constructed and utilised to project the received mixed return of radar onto to the target echo sublinear space so as to suppress the jamming. Meanwhile, the complexity of the above jamming suppression algorithm is presented and the working flow of a radar system equipped with a polarisation sensitive array for countering the deception jammer is also presented. Simulation results demonstrate the performance of the proposed scheme.

DOA and polarization estimation via signal reconstruction with linear polarization-sensitive arrays

This paper addresses the problem of direction-of-arrival (DOA) and polarization estimation with polarization sensitive arrays (PSA), which has been a hot topic in the area of array signal processing during the past two or three decades. The sparse Bayesian learning (SBL) technique is introduced to exploit the sparsity of the incident signals in space to solve this problem and a new method is proposed by reconstructing the signals from the array outputs first and then exploiting the reconstructed signals to realize parameter estimation. Only 1-D searching and numerical calculations are contained in the proposed method, which makes the proposed method computationally much efficient. Based on a linear array consisting of identically structured sensors, the proposed method can be used with slight modifications in PSA with different polarization structures. It also performs well in the presence of coherent signals or signals with different degrees of polarization. Simulation results are given to demonstrate the parameter estimation precision of the proposed method.

A Fast DOA Estimation Algorithm Based on Polarization MUSIC

A fast DOA estimation algorithm developed from MUSIC, which also benefits from the processing of the signals' polarization information, is presented. Besides performance enhancement in precision and resolution, the proposed algorithm can be exerted on various forms of polarization sensitive arrays, without specific requirement on the array's pattern. Depending on the continuity property of the space spectrum, a huge amount of computation incurred in the calculation of 4-D space spectrum is averted. Performance and computation complexity analysis of the proposed algorithm is discussed and the simulation results are presented. Compared with conventional MUSIC, the proposed algorithm has considerable advantage in aspects of precision and resolution, with a low computation complexity proportional to a conventional 2-D MUSIC.

Low‐angle tracking algorithm using polarisation sensitive array for very‐high frequency radar

Low-angle tracking algorithm using polarisation sensitive array is proposed for very-high frequency radar. First, the receiving signal model is established in multipath environment based on the complex reflection coefficient model. Then the decorrelating efficiency of polarisation smoothing (PS) is presented by analysing the condition number of envelop covariance matrix by PS. After that, the PS-MUSIC algorithm which combines the PS preprocessing and the MUSIC algorithm is established. Its performances, in terms of the signal-to-noise ratio, elevation angle of target and polarisation angle, are evaluated by simulations. The PS-MUSIC algorithm needs only a few snapshots or even a single one. This method can work well in a narrow band system and is not restrained by array configuration. It can also be applied in other scenarios, where multipath effect is serious.