2D DOA Estimation of UCA Correlative Interferometer Based on One Dimensional Sorting Lookup Table-Two Dimensional Linear Interpolation Algorithm

An improved scan conversion algorithm for ultrasound compound scanning is proposed. In this algorithm, the input data in the spatial domain is sampled by the concentric square raster sampling (CSRS) method, and the display pixel data are filled by one-dimensional linear interpolation. The reconstruction error of the proposed algorithm is much smaller than that of other algorithms, because only one-dimensional, rather than two-dimensional, interpolation is involved. This algorithm greatly simplifies implementation of a real-time digital scan converter (DSC) for spatial compounding of ultrasound images.

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A FPC-ROOT Algorithm for 2D-DOA Estimation in Sparse Array

International Journal of Antennas and Propagation ◽

10.1155/2016/5951717 ◽

2016 ◽

Vol 2016 ◽

pp. 1-6

Author(s):

Wenhao Zeng ◽

Hongtao Li ◽

Xiaohua Zhu ◽

Chaoyu Wang

Keyword(s):

Null Space ◽

Matrix Completion ◽

Doa Estimation ◽

Two Dimensional ◽

Polynomial Roots ◽

Sparse Array ◽

Autocorrelation Matrix ◽

Proposed Model ◽

The Matrix ◽

2D Doa Estimation

To improve the performance of two-dimensional direction-of-arrival (2D DOA) estimation in sparse array, this paper presents a Fixed Point Continuation Polynomial Roots (FPC-ROOT) algorithm. Firstly, a signal model for DOA estimation is established based on matrix completion and it can be proved that the proposed model meets Null Space Property (NSP). Secondly, left and right singular vectors of received signals matrix are achieved using the matrix completion algorithm. Finally, 2D DOA estimation can be acquired through solving the polynomial roots. The proposed algorithm can achieve high accuracy of 2D DOA estimation in sparse array, without solving autocorrelation matrix of received signals and scanning of two-dimensional spectral peak. Besides, it decreases the number of antennas and lowers computational complexity and meanwhile avoids the angle ambiguity problem. Computer simulations demonstrate that the proposed FPC-ROOT algorithm can obtain the 2D DOA estimation precisely in sparse array.

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Two-Dimensional DOA Estimation for Monostatic MIMO Radar with Electromagnetic Vector Received Sensors

International Journal of Antennas and Propagation ◽

10.1155/2016/2952539 ◽

2016 ◽

Vol 2016 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Guimei Zheng ◽

Jun Tang

Keyword(s):

Electromagnetic Field ◽

Estimation Method ◽

Estimation Algorithm ◽

Doa Estimation ◽

Field Vector ◽

Cross Product ◽

Mimo Radar ◽

Two Dimensional ◽

Array Configuration ◽

2D Doa Estimation

We study two-dimensional direction of arrival (2D-DOA) estimation problem of monostatic MIMO radar with the receiving array which consists of electromagnetic vector sensors (EMVSs). The proposed angle estimation algorithm can be applied to the arbitrary and unknown array configuration, which can be summarized as follows. Firstly, EMVSs in the receiver of a monostatic MIMO radar are used to measure all six electromagnetic-field components of an incident wavefield. The vector sensor array with the six unknown electromagnetic-field components is divided into six spatially identical subarrays. Secondly, ESPRIT is utilized to estimate the rotational invariant factors (RIFs). Parts of the RIFs are picked up to restore the source’s electromagnetic-field vector. Last, a vector cross product operation is performed between electric field and magnetic field to obtain the Pointing vector, which can offer the 2D-DOA estimation. Prior knowledge of array elements’ positions and angle searching procedure are not necessary for the proposed 2D-DOA estimation method. Simulation results prove the validity of the proposed method.

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Two-Dimensional Direction of Arrival (DOA) Estimation for Rectangular Array via Compressive Sensing Trilinear Model

International Journal of Antennas and Propagation ◽

10.1155/2015/297572 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 4

Author(s):

Huaxin Yu ◽

Xiaofeng Qiu ◽

Xiaofei Zhang ◽

Chenghua Wang ◽

Gang Yang

Keyword(s):

Compressive Sensing ◽

Direction Of Arrival ◽

Estimation Algorithm ◽

Doa Estimation ◽

Two Dimensional ◽

Rectangular Array ◽

Angle Estimation ◽

Estimation Performance ◽

Trilinear Model ◽

2D Doa Estimation

We investigate the topic of two-dimensional direction of arrival (2D-DOA) estimation for rectangular array. This paper links angle estimation problem to compressive sensing trilinear model and derives a compressive sensing trilinear model-based angle estimation algorithm which can obtain the paired 2D-DOA estimation. The proposed algorithm not only requires no spectral peak searching but also has better angle estimation performance than estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. Furthermore, the proposed algorithm has close angle estimation performance to trilinear decomposition. The proposed algorithm can be regarded as a combination of trilinear model and compressive sensing theory, and it brings much lower computational complexity and much smaller demand for storage capacity. Numerical simulations present the effectiveness of our approach.

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Two-Dimensional DOA Estimation for Uniform Rectangular Array Using Reduced-Dimension Propagator Method

International Journal of Antennas and Propagation ◽

10.1155/2015/485351 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 8

Author(s):

Ming Zhou ◽

Xiaofei Zhang ◽

Xiaofeng Qiu ◽

Chenghua Wang

Keyword(s):

Estimation Error ◽

Doa Estimation ◽

Eigenvalue Decomposition ◽

Two Dimensional ◽

Rectangular Array ◽

Angle Estimation ◽

Propagator Method ◽

Reduced Dimension ◽

2D Doa Estimation ◽

Uniform Rectangular Array

A novel algorithm is proposed for two-dimensional direction of arrival (2D-DOA) estimation with uniform rectangular array using reduced-dimension propagator method (RD-PM). The proposed algorithm requires no eigenvalue decomposition of the covariance matrix of the receive data and simplifies two-dimensional global searching in two-dimensional PM (2D-PM) to one-dimensional local searching. The complexity of the proposed algorithm is much lower than that of 2D-PM. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm and conventional PM algorithms, also very close to 2D-PM. The angle estimation error and Cramér-Rao bound (CRB) are derived in this paper. Furthermore, the proposed algorithm can achieve automatically paired 2D-DOA estimation. The simulation results verify the effectiveness of the algorithm.

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Reduced-Dimension Noncircular-Capon Algorithm for DOA Estimation of Noncircular Signals

International Journal of Antennas and Propagation ◽

10.1155/2015/348636 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Weihua Lv ◽

Huapu Sun ◽

Xiaofei Zhang ◽

Dazhuan Xu

Keyword(s):

Computational Cost ◽

Doa Estimation ◽

Two Dimensional ◽

Angle Estimation ◽

One Dimensional ◽

Reduced Dimension ◽

Noncircular Signals ◽

Simulation Results ◽

High Computational Cost ◽

Better Than

The problem of the direction of arrival (DOA) estimation for the noncircular (NC) signals, which have been widely used in communications, is investigated. A reduced-dimension NC-Capon algorithm is proposed hereby for the DOA estimation of noncircular signals. The proposed algorithm, which only requires one-dimensional search, can avoid the high computational cost within the two-dimensional NC-Capon algorithm. The angle estimation performance of the proposed algorithm is much better than that of the conventional Capon algorithm and very close to that of the two-dimensional NC-Capon algorithm, which has a much higher complexity than the proposed algorithm. Furthermore, the proposed algorithm can be applied to arbitrary arrays and works well without estimating the noncircular phases. The simulation results verify the effectiveness and improvement of the proposed algorithm.

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An Example of Two-Dimensional Interpolation Using a Linear Combination of Bicubic B-Splines

International Journal of Electronics and Telecommunications ◽

10.2478/v10177-011-0039-2 ◽

2011 ◽

Vol 57 (3) ◽

pp. 293-299

Author(s):

Stanisław Rosłoniec

Keyword(s):

Linear Combination ◽

Short Description ◽

Two Dimensional ◽

Interpolation Algorithm ◽

Rectangular Grid ◽

B Spline ◽

One Dimensional ◽

The Real ◽

B Splines

An Example of Two-Dimensional Interpolation Using a Linear Combination of Bicubic B-Splines The paper describes how a linear combination of bicubic B-splines can be effectively used in a two-dimensional interpolation. It is assumed that values of a function to be interpolated are evaluated at the uniformly located nodes of a corresponding rectangular grid. All formulae of importance have been derived step by step and are presented in a form convenient for computer implementations. To ensure clarity of considerations a short description of one-dimensional B-spline is also given in Appendix 1. The usefulness of the presented interpolation algorithm has been confirmed by the real engineering example of applications.

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Simulation and Implementation of 2D DOA Estimation in Wireless Location

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.195-196.661 ◽

2012 ◽

Vol 195-196 ◽

pp. 661-665

Author(s):

Ping Tan ◽

Zhi Yao Zhou ◽

Yu Feng Zhang ◽

Ye Luo ◽

Hong Ma

Keyword(s):

High Resolution ◽

Unitary Transformation ◽

Measurement Data ◽

Doa Estimation ◽

High Accuracy ◽

Two Dimensional ◽

Circular Array ◽

Music Algorithm ◽

Wireless Location ◽

2D Doa Estimation

It is needed to realize high resolution two dimensional (2D) direction of arrivals (DOA) estimation in determining the location of the mobile with high accuracy. In this paper, the problem of estimating the 2D DOA using uniform circular array (UCA) is investigated. Performance of 2D DOA estimation based on the real-valued unitary transformation MUSIC algorithm for UCA is presented, especially focusing on DOA estimation of multiple correlated signals.Then the validations of Unitary Transformation MUSIC algorithm are performed based on the measurement data in a wireless location system.

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Two-Dimensional DOA Estimation Using One-Dimensional Search for Spherical Arrays

Chinese Journal of Electronics ◽

10.1049/cje.2019.08.009 ◽

2019 ◽

Vol 28 (6) ◽

pp. 1259-1264

Author(s):

Qinghua Huang ◽

Jiajun Feng ◽

Yong Fang

Keyword(s):

Doa Estimation ◽

Two Dimensional ◽

One Dimensional ◽

Spherical Arrays

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Computationally Efficient Ambiguity-Free Two-Dimensional DOA Estimation Method for Coprime Planar Array: RD-Root-MUSIC Algorithm

Mathematical Problems in Engineering ◽

10.1155/2020/2794387 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Luo Chen ◽

Changbo Ye ◽

Baobao Li

Keyword(s):

Degrees Of Freedom ◽

Estimation Method ◽

Doa Estimation ◽

Estimation Accuracy ◽

Two Dimensional ◽

Computationally Efficient ◽

Music Algorithm ◽

Estimation Algorithms ◽

Planar Array ◽

2D Doa Estimation

While the two-dimensional (2D) spectral peak search suffers from expensive computational burden in direction of arrival (DOA) estimation, we propose a reduced-dimensional root-MUSIC (RD-Root-MUSIC) algorithm for 2D DOA estimation with coprime planar array (CPA), which is computationally efficient and ambiguity-free. Different from the conventional 2D DOA estimation algorithms based on subarray decomposition, we exploit the received data of the two subarrays jointly by mapping CPA to the full array of the CPA (FCPA), which contributes to the enhanced degrees of freedom (DOFs) and improved estimation performance. In addition, due to the ambiguity-free characteristic of the FCPA, the extra ambiguity elimination operation can be avoided. Furthermore, we convert the 2D spectral search process into 1D polynomial rooting via reduced-dimension transformation, which substantially reduces the computational complexity while preserving the estimation accuracy. Finally, numerical simulations demonstrate the superiority of the proposed algorithm.

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