scholarly journals Two-Dimensional Direction-of-Arrivals Estimation Based on One-Dimensional Search Using Rank Deficiency Principle

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Feng-Gang Yan ◽  
Zhi-Kun Chen ◽  
Ming-Jian Sun ◽  
Yi Shen ◽  
Ming Jin
Keyword(s):  
Computational Complexity ◽  
Signal Classification ◽  
Two Dimensional ◽  
Music Algorithm ◽  
Signal Parameter ◽  
Rank Deficiency ◽  
Multiple Signal Classification ◽  
One Dimensional ◽  
Pair Matching ◽  
Improved Accuracy

A novel efficient method for two-dimensional (2D) direction-of-arrivals (DOAs) estimation is proposed to reduce the computational complexity of conventional 2D multiple signal classification (2D-MUSIC) algorithm with uniform rectangular arrays (URAs). By introducing two electrical DOAs, the formula of 2D-MUSIC is transformed into a new one-dimensional (1D) quadratic optimal problem. This 1D quadratic optimal problem is further proved equivalent to finding the conditions of noise subspace rank deficiency (NSRD), which can be solved by an efficient 1D spectral search, leading to a novel NSRD-MUSIC estimator accordingly. Unlike 2D-MUSIC with exhaustive 2D search, the proposed technique requires only an efficient 1D one. Compared with the estimation of signal parameter via rotation invariance techniques (ESPRIT), NSRD-MUSIC has a significantly improved accuracy. Moreover, the new algorithm requires no pair matching. Numerical simulations are conducted to verify the efficiency of the new estimator.

scholarly journals Bearing and Range Estimation Algorithm for Buried Object in Underwater Acoustics

2009 ◽  
Vol 2009 ◽  
pp. 1-4
Author(s):  
Dong Han ◽  
Caroline Fossati ◽  
Salah Bourennane ◽  
Zineb Saidi
Keyword(s):  
Underwater Acoustics ◽  
Classical Model ◽  
Acoustic Scattering ◽  
Estimation Algorithm ◽  
Signal Classification ◽  
Music Algorithm ◽  
Range Estimation ◽  
Multiple Signal Classification ◽  
Buried Objects ◽  
Buried Object

A new algorithm which associates (Multiple Signal Classification) MUSIC with acoustic scattering model for bearing and range estimation is proposed. This algorithm takes into account the reflection and the refraction of wave in the interface of water-sediment in underwater acoustics. A new directional vector, which contains the Direction-Of-Arrival (DOA) of objects and objects-sensors distances, is used in MUSIC algorithm instead of classical model. The influence of the depth of buried objects is discussed. Finally, the numerical results are given in the case of buried cylindrical shells.

scholarly journals Polarization and DOA Estimation Based on Dual-Polarized Conformal Array

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Chao Liu ◽  
Shuai Xiang ◽  
Liangfeng Xu ◽  
Zhengfei Fang
Keyword(s):  
Doa Estimation ◽  
Signal Classification ◽  
Orthogonal Polarization ◽  
Coherent Signals ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Polarization Signal ◽  
Conformal Array ◽  
Dual Polarized ◽  
Cramer Rao Bound

A dual-polarized multiple signal classification (DP-MUSIC) algorithm is presented to estimate the arrival directions and polarizations for a dual-polarized conformal array. Each polarization signal is decomposed into two orthogonal polarization components, which are considered to be a pair of coherent signals coming from the same direction but different polarization. The polarization parameters are modeled as the equivalent coherence coefficients of the orthogonal polarization components. Then, the method of decoherence can be used to decouple the information of polarization states and signal angles. After that, the direction of arrival (DOA) and polarization parameters can be estimated by the DP-MUSIC algorithm. Moreover, the angles of incident direction are re-estimated, which greatly improves the accuracy of DOA estimation. The Cramer–Rao bound (CRB) is derived and the effectiveness of the proposed algorithm is verified by Monte Carlo simulations.

scholarly journals Direction of Arrival Using Uniform Circular Array based on 2-D MUSIC Algorithm

2018 ◽  
Vol 12 (1) ◽  
pp. 30
Author(s):  
Mohammed Amine Ihedrane ◽  
Seddik Bri
Keyword(s):  
Dielectric Permittivity ◽  
Patch Antenna ◽  
Direction Of Arrival ◽  
Dielectric Substrate ◽  
Signal Classification ◽  
Circular Array ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Linear Arrays ◽  
Circular Arrays

<p>This study presents the conception, simulation, realisation and characterisation of a patch antenna for Wi-Fi. The antenna is designed at the frequency of 2.45 GHz; the dielectric substrate used is FR4_epoxy which has a dielectric permittivity of 4.4.this patch antenna is used to estimate the direction of arrival (DOA) using 2-D Multiple Signal Classification (2-D MUSIC) the case of the proposed  uniform circular arrays (UCA). The comparison between Uniform circular arrays and Uniform Linear arrays (ULA) demonstrate that the proposed structure give better angles resolutions compared to ULAs.</p>

Research on a New Array-Manifold of Single Vector Hydrophone

2014 ◽  
Vol 955-959 ◽  
pp. 899-910
Author(s):  
Bo Le Ma ◽  
Jing Fang Cheng ◽  
Chao Ran Zhang
Keyword(s):  
Signal Processing ◽  
Minimum Variance ◽  
Signal Classification ◽  
Beam Forming ◽  
Noise Power ◽  
Complex Data ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Minimum Variance Distortionless Response ◽  
Vector Hydrophone

For the purpose of improving the signal processing of single vector hydrophone, this paper combined two velocity signals as two complex data, so as to change array-manifold of single vector hydrophone. Taking two-dimension single vector hydrophone as an example, this paper compared the capability of signal processing of new array-manifold single vector hydrophone with old one from conventional beam-forming(CBF) ,minimum variance distortionless response (MVDR) and multiple signal classification (MUSIC). As for CBF, the analysis indicates, the capability of spatial filtering of new array-manifold could improve 0.51db and the HPBW of new array-manifold will be smaller than old array-manifold. When the noise power is 0, the HPBW of new array-manifold will be narrower than old array-manifold 19.26°. As for MVDR, the capability of signal processing of new array-manifold is the same as old array-manifold. In MUSIC algorithm, the value measuring angle resolution shows the superiority of the new array-manifold- angle resolution. Simulation and measured data proved the better performance of the method presented by this paper.

A Dynamic Sub-Array Divided Technique for Spherical Conformal Array Antenna Using K-Means Algorithm

2014 ◽  
Vol 926-930 ◽  
pp. 2884-2888 ◽  
Author(s):  
Jin Yan Tang ◽  
Yue Lei Xie ◽  
Cheng Cheng Peng
Keyword(s):  
Direction Of Arrival ◽  
Array Antenna ◽  
Signal Classification ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Conformal Array ◽  
Multiple Signal

In this paper, a sub-array divided technique using K-means algorithm for spherical conformal array is proposed. All elements of spherical conformal array can be divided into a few sub-arrays by employing the K-means algorithm, and the standard multiple signal classification (MUSIC) algorithm is applied to estimate signals Direction-of-arrival (DOA) on these sub-arrays. Simulations of estimating DOA on a rotational spherical conformal array have been made and the results show that the resolution of DOA is improved by our method compare to existing methods.

Study of High Resolution DOA Estimation Based on Vector-Hydrophone

2014 ◽  
Vol 926-930 ◽  
pp. 1795-1799
Author(s):  
Hao Zhou ◽  
Zhi Jie Huo
Keyword(s):  
Doa Estimation ◽  
Spatial Spectrum ◽  
Classification Algorithm ◽  
Signal Classification ◽  
Two Dimensional ◽  
Multiple Signal Classification ◽  
Variance Matrix ◽  
Multiple Signal ◽  
Vector Hydrophone ◽  
Eigen Decomposition

Vector-hydrophone can simultaneously measure acoustic pressure and orthogonal components of the particle velocity. The 180o ambiguity in DOA estimation can be eliminated using information obtained by vector hydrophone array. Multiple signal classification algorithm is a method that takes the eigen-decomposition of data co-variance matrix to obtain the estimation of signal spatial spectrum. The two-dimensional DOA of acoustic sources is estimated based on multiple signal classification algorithm using the vector-hydrophone uniform linear array. Simulation results show that better DOA resolution performance can be obtained from vector hydrophones. Furthermore, the paper takes the de-correlation of correlated sources using spatial smoothness technology to obtain perfect performance of two-dimensional DOA estimation.

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