Joint DOA and Frequency Estimation for Linear Array with Compressed Sensing PARAFAC Framework

2017 ◽  
Vol 26 (09) ◽  
pp. 1750136 ◽  
Author(s):  
Shu Li ◽  
Zezhou Sun ◽  
Xiaofei Zhang ◽  
Weiyang Chen ◽  
Dazhuan Xu
Keyword(s):  
Compressed Sensing ◽  
Frequency Estimation ◽  
Estimation Algorithm ◽  
Linear Arrays ◽  
Propagator Method ◽  
Joint Direction ◽  
Parallel Factor ◽  
Esprit Algorithm ◽  
Spatial Sparsity ◽  
Better Than

In this paper, a joint direction of arrival (DOA) and frequency estimation algorithm of narrow-band signals is proposed via compressed sensing (CS) parallel factor (PARAFAC) framework. The proposed algorithm constructs the data model into a PARAFAC model, and compresses it to a smaller one. Then trilinear alternating least-squares (TALS) algorithm is exploited to estimate the compressed parameter matrices, and finally the joint DOA and frequency estimation is obtained via the spatial sparsity and the frequency sparsity. Due to compression, the proposed algorithm has lower computational complexity than the conventional PARAFAC algorithm, and saves more memory capacity for practical application. The DOA and frequency estimation performance of the proposed algorithm is very close to that of the conventional PARAFAC algorithm, and better than those of the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm and the propagator method (PM). Furthermore, the proposed algorithm can achieve automatically paired DOA and frequency estimation. Besides, it is applicable for nonuniform linear arrays. Effectiveness of the proposed algorithm is assessed by simulations.

scholarly journals Improved ESPRIT Method for Joint Direction-of-Arrival and Frequency Estimation Using Multiple-Delay Output

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Wang Xudong ◽  
Xiaofei Zhang ◽  
Jianfeng Li ◽  
Jinchao Bai
Keyword(s):  
Antenna Arrays ◽  
Frequency Estimation ◽  
Direction Of Arrival ◽  
Joint Angles ◽  
Linear Arrays ◽  
Estimation Performance ◽  
Multiple Delay ◽  
Joint Direction ◽  
Esprit Algorithm ◽  
Linear Antenna Arrays

An automatic pairing joint direction-of-arrival (DOA) and frequency estimation is presented to overcome the unsatisfactory performances of estimation of signal parameter via rotational invariance techniques- (ESPRIT-) like algorithm of Wang (2010), which requires an additional pairing. By using multiple-delay output of a uniform linear antenna arrays (ULA), the proposed algorithm can estimate joint angles and frequencies with an improved ESPRIT. Compared with Wang’s ESPRIT algorithm, the angle estimation performance of the proposed algorithm is greatly improved. The frequency estimation performance of the proposed algorithm is same with that of Wang’s ESPRIT algorithm. Furthermore, the proposed algorithm can obtain automatic pairing DOA and frequency parameters, and it has a comparative computational complexity in contrast to Wang’s ESPRIT algorithm. By the way, this proposed algorithm can also work well for nonuniform linear arrays. The useful behavior of this proposed algorithm is verified by simulations.

Modified Propagator Method for 2-Dimensional DOA Estimation in Monostatic MIMO Radar with L-Shaped Array

2013 ◽  
Vol 846-847 ◽  
pp. 1171-1175
Author(s):  
Xin Li ◽  
Ding Jie Xu ◽  
Xiao Meng Wang
Keyword(s):  
Doa Estimation ◽  
Mimo Radar ◽  
Complex Matrix ◽  
Linear Arrays ◽  
Complex Eigenvalues ◽  
Propagator Method ◽  
The Matrix ◽  
Esprit Algorithm ◽  
Influence Of Noise ◽  
Better Than

A modified propagator method based on L-shaped array for 2-Dimensional (2-D) direction of arrival (DOA) estimation in monostatic MIMO radar is proposed. A cross-correlation matrix, which can eliminate the influence of noise, is constructed by the received data from the two orthogonal uniform linear arrays (ULAs) at x-axis and z-axis. Then the matrix can be utilized to estimate signal subspace of 2-D DOA through propagator method. At last, the elevation and azimuth angles of the 2-D DOA is automatically paired by the complex eigenvalues of a low-order complex matrix. The 2-D DOA estimation performance of the proposed method is better than conventional propagator method and ESPRIT algorithm. Simulation results verify the effectiveness of the proposed method.

scholarly journals Joint 2D-DOA and Frequency Estimation for L-Shaped Array Using Iterative Least Squares Method

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Ling-yun Xu ◽  
Xiao-fei Zhang ◽  
Zong-ze Xu ◽  
Miao Yu
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Frequency Estimation ◽  
Spectral Peak ◽  
Propagator Method ◽  
Esprit Algorithm ◽  
Delay Matrix

We introduce an iterative least squares method (ILS) for estimating the 2D-DOA and frequency based on L-shaped array. The ILS iteratively finds direction matrix and delay matrix, then 2D-DOA and frequency can be obtained by the least squares method. Without spectral peak searching and pairing, this algorithm works well and pairs the parameters automatically. Moreover, our algorithm has better performance than conventional ESPRIT algorithm and propagator method. The useful behavior of the proposed algorithm is verified by simulations.

scholarly journals Compressed Sensing PARALIND Decomposition-Based Coherent Angle Estimation for Uniform Rectangular Array

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Wu Wei ◽  
Xu Le ◽  
Zhang Xiaofei ◽  
Li Jianfeng
Keyword(s):  
Compressed Sensing ◽  
Data Storage ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Smoothing ◽  
Rectangular Array ◽  
Propagator Method ◽  
Coherent Sources ◽  
2D Doa Estimation ◽  
Uniform Rectangular Array

In this paper, the topic of coherent two-dimensional direction of arrival (2D-DOA) estimation is investigated. Our study jointly utilizes the compressed sensing (CS) technique and the parallel profiles with linear dependencies (PARALIND) model and presents a 2D-DOA estimation algorithm for coherent sources with the uniform rectangular array. Compared to the traditional PARALIND decomposition, the proposed algorithm owns lower computational complexity and smaller data storage capacity due to the process of compression. Besides, the proposed algorithm can obtain autopaired azimuth angles and elevation angles and can achieve the same estimation performance as the traditional PARALIND, which outperforms some familiar algorithms presented for coherent sources such as the forward backward spatial smoothing-estimating signal parameters via rotational invariance techniques (FBSS-ESPRIT) and forward backward spatial smoothing-propagator method (FBSS-PM). Extensive simulations are provided to validate the effectiveness of the proposed CS-PARALIND algorithm.

Compressed Sensing Trilinear Model-Based Angle Estimation for Bistatic MIMO Radar

2013 ◽  
Vol 347-350 ◽  
pp. 1033-1038 ◽  
Author(s):  
Xiao Fei Zhang ◽  
Jian Feng Li ◽  
Ming Zhou ◽  
De Ben
Keyword(s):  
Compressed Sensing ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Mimo Radar ◽  
Estimation Problem ◽  
Angle Estimation ◽  
Model Based ◽  
Trilinear Model ◽  
Input Multiple Output ◽  
Esprit Algorithm

In this paper, we address the transmit angle and receive angle estimation problem for a bistatic multiple-input multiple-output (MIMO) radar. This paper links MIMO radar angle estimation problem to the compressed sensing trilinear model. Exploiting this link, it derives a compressed sensing trilinear model-based angle estimation algorithm, which can obtain automatically paired two-dimensional angle estimation. The proposed algorithm requires no spectral peak searching or pair matching, and it has better angle estimation performance than conventional algorithms including estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. Simulation results illustrate performance of the algorithm.

scholarly journals Harmonic Frequency Estimation Algorithm based on ESPRIT and MSWF in Power System

2015 ◽  
Vol 9 (1) ◽  
pp. 518-523 ◽  
Author(s):  
Sun Xiangwen ◽  
Cao Zhe ◽  
Tian Wei
Keyword(s):  
Power System ◽  
Simulation Experiment ◽  
Frequency Estimation ◽  
Wiener Filter ◽  
Estimation Algorithm ◽  
Frequency Resolution ◽  
Harmonic Frequency ◽  
Fast Estimation ◽  
Multistage Wiener Filter ◽  
Esprit Algorithm

This paper points out the deficiency in the current harmonic frequency estimation algorithm in power system. In order to improve the accuracy of detection and reduce the computational complexity, the study combined the ESPRIT algorithm with multistage Wiener filter (MSWF) recurrence to achieve fast estimation of harmonic frequency. Theoretical analysis and simulation experiment show that the algorithm had relatively low requirement for the amount of data, and demonstrated good frequency resolution characteristics and anti-jamming capability, which made it ideally suitable for harmonic analysis in power system.

Two-Dimensional DOA Estimation for Planar Array Using a Successive Propagator Method

2019 ◽  
Vol 28 (10) ◽  
pp. 1950161 ◽  
Author(s):  
Weiyang Chen ◽  
Xiaofei Zhang ◽  
Chi Jiang
Keyword(s):  
Computational Cost ◽  
Doa Estimation ◽  
Rotational Invariance ◽  
Eigenvalue Decomposition ◽  
Invariance Property ◽  
Two Dimensional ◽  
Propagator Method ◽  
Planar Array ◽  
Esprit Algorithm ◽  
Better Than

We consider the problem of two-dimensional (2D) direction of arrival (DOA) estimation for planar array, and propose a successive propagator method (PM)-based algorithm. The rotational invariance property of the propagator matrix is exploited to obtain the initial angle estimations, while the accurate estimates can be achieved through successive one-dimensional and local spectrum-peak searches. The proposed algorithm can obtain automatically paired 2D-DOA estimations, and it requires no eigenvalue decomposition of the covariance matrix of received data, which remarkably reduces the computational cost compared with traditional 2D-PM algorithm. In addition, the DOA estimation performance of the proposed algorithm is better than estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm and PM algorithm, and is close to 2D-PM algorithm which requires 2D spectrum-peak search. Numerical simulations demonstrate the effectiveness and improvement of the proposed algorithm.

scholarly journals The influence of different PAST-based subspace trackers on DaPT parameter estimation

2012 ◽  
Vol 10 ◽  
pp. 153-158
Author(s):  
M. Lechtenberg ◽  
J. Götze
Keyword(s):  
Parameter Estimation ◽  
Frequency Estimation ◽  
Estimation Algorithm ◽  
Time Varying ◽  
The Past ◽  
Vector Decomposition ◽  
Parameter Estimation Algorithm ◽  
Varying Environments ◽  
Esprit Algorithm ◽  
Subspace Separation

Abstract. In the context of parameter estimation, subspace-based methods like ESPRIT have become common. They require a subspace separation e.g. based on eigenvalue/-vector decomposition. In time-varying environments, this can be done by subspace trackers. One class of these is based on the PAST algorithm. Our non-linear parameter estimation algorithm DaPT builds on-top of the ESPRIT algorithm. Evaluation of the different variants of the PAST algorithm shows which variant of the PAST algorithm is worthwhile in the context of frequency estimation.

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