scholarly journals Computationally Efficient Direction-of-Arrival Estimation Algorithms for a Cubic Coprime Array

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 136
Author(s):  
Pan Gong ◽  
Xixin Chen
Keyword(s):  
Covariance Matrix ◽  
Lower Boundary ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Signal Classification ◽  
Computationally Efficient ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Multiple Signal

In this paper, we investigate the problem of direction-of-arrival (DOA) estimation for massive multi-input multi-output (MIMO) radar, and propose a total array-based multiple signals classification (TA-MUSIC) algorithm for two-dimensional direction-of-arrival (DOA) estimation with a coprime cubic array (CCA). Unlike the conventional multiple signal classification (MUSIC) algorithm, the TA-MUSIC algorithm employs not only the auto-covariance matrix but also the mutual covariance matrix by stacking the received signals of two sub cubic arrays so that full degrees of freedom (DOFs) can be utilized. We verified that the phase ambiguity problem can be eliminated by employing the coprime property. Moreover, to achieve lower complexity, we explored the estimation of signal parameters via the rotational invariance technique (ESPRIT)-based multiple signal classification (E-MUSIC) algorithm, which uses a successive scheme to be computationally efficient. The Cramer–Rao bound (CRB) was taken as a theoretical benchmark for the lower boundary of the unbiased estimate. Finally, numerical simulations were conducted in order to demonstrate the effectiveness and superiority of the proposed algorithms.

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.

MULTIPLE SIGNAL CLASSIFICATION FOR GRAVITATIONAL WAVE BURST SEARCH

2013 ◽  
Vol 23 ◽  
pp. 74-81
Author(s):  
JUNWEI CAO ◽  
ZHENGQI HE
Keyword(s):  
Gravitational Wave ◽  
Doa Estimation ◽  
Signal Classification ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Wave Characteristics ◽  
Multiple Signal ◽  
Promising Tool ◽  
Arbitrary Position ◽  
Noise Covariance

This work is mainly focused on the application of the multiple signal classification (MUSIC) algorithm for gravitational wave burst search. This algorithm extracts important gravitational wave characteristics from signals coming from detectors with arbitrary position, orientation and noise covariance. In this paper, the MUSIC algorithm is described in detail along with the necessary adjustments required for gravitational wave burst search. The algorithm's performance is measured using simulated signals and noise. MUSIC is compared with the Q-transform for signal triggering and with Bayesian analysis for direction of arrival (DOA) estimation, using the Ω-pipeline. Experimental results show that MUSIC has a lower resolution but is faster. MUSIC is a promising tool for real-time gravitational wave search for multi-messenger astronomy.

scholarly journals Two-Dimensional Direction-of-Arrival Estimation for Trilinear Decomposition-Based Monostatic Cross MIMO Radar

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Fangqing Wen ◽  
Gong Zhang
Keyword(s):  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Mimo Radar ◽  
Eigenvalue Decomposition ◽  
Two Dimensional ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Trilinear Decomposition ◽  
Signal Covariance Matrix

A low complexity monostatic cross multiple-in multiple-out (MIMO) radar scheme is proposed in this paper. The minimum-redundancy linear array (MRLA) is introduced in the cross radar to improve the efficiency of the array elements. The two-dimensional direction-of-arrival (DOA) estimation problem links to the trilinear model, which automatically pairs the estimated two-dimensional angles, requiring neither eigenvalue decomposition of received signal covariance matrix nor spectral peak searching. The proposed scheme performs better than the uniform linear arrays (ULA) configuration under the same conditions, and the proposed algorithm has less computational complexity than that of multiple signal classification (MUSIC) algorithm. Simulation results show the effectiveness of our scheme.

scholarly journals Direction-of-Arrival Estimation of Electromagnetic Wave Impinging on Spherical Antenna Array in the Presence of Mutual Coupling Using a Multiple Signal Classification Method

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2651
Author(s):  
Oluwole John Famoriji ◽  
Thokozani Shongwe
Keyword(s):  
Electromagnetic Wave ◽  
Fourier Series ◽  
Antenna Array ◽  
Mutual Coupling ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Signal Classification ◽  
Multiple Signal Classification ◽  
Multiple Signal ◽  
Spherical Antenna

A spherical antenna array (SAA) is the configuration of choice in obtaining an antenna array with isotropic characteristics. An SAA has the capacity to receive an electromagnetic wave (EM) with equal intensity irrespective of the direction-of-arrival (DoA) and polarization. Therefore, the DoA estimation of electromagnetic (EM) waves impinging on an SAA with unknown mutual coupling needs to be considered. In the spherical domain, the traditional multiple signal classification algorithm (SH-MUSIC) is faced with a computational complexity problem. This paper presents a one-dimensional MUSIC method (1D-MUSIC) for the estimation of the azimuth and elevation angles. An intermediate mapping matrix that exists between Fourier series and the spherical harmonic function is designed, and the Fourier series Vandermonde structure is used for the realization of the polynomial rooting technique. This mapping matrix can be computed prior to the DoA estimation, and it is only a function of the array configuration. Based on the mapping matrix, the 2-D angle search is transformed into two 1-D angle findings. Employing the features of the Fourier series, two root polynomials are designed for the estimation of the elevation and azimuth angles, spontaneously. The developed method avoids the 2-D spectral search, and angles are paired in automation. Both numerical simulation results, and results from experimental measured data (i.e., with mutual coupling effect incorporated), show the validity, potency, and potential practical application of the developed algorithm.

scholarly journals The iterative search approach DOA estimation of monostatic L-shaped array MIMO radar

2018 ◽  
Vol 12 (2) ◽  
pp. 101-109
Author(s):  
Guan Jishi ◽  
Shi Yaowu ◽  
Deng Lifei ◽  
Zhu Lanxiang ◽  
Shi Hongwei
Keyword(s):  
Doa Estimation ◽  
Mimo Radar ◽  
Classification Algorithm ◽  
Signal Classification ◽  
Two Dimensional ◽  
Iterative Search ◽  
Multiple Signal Classification ◽  
Multiple Signal ◽  
Searching Method ◽  
Search Approach

In the DOA estimation of monostatic L-shaped array MIMO radar, Multiple Signal Classification algorithm is efficient. But the peak searching process of Multiple Signal Classification algorithm needs large amount of spectrum calculation. Focusing on the spectrum peak searching process of Multiple Signal Classification, an iterative search approach to reduce the calculation amount is proposed. The first- and second-order derivatives of Multiple Signal Classification spectrum functions are achieved and the calculation amount is analyzed. Two-dimensional Newton iteration methods are applied with multisearching threads and derivation information. The searching approach can greatly reduce the computational complexity of Multiple Signal Classification spectrum peak searching. The total calculation amount of the first and second derivatives is about 15 times of the spectrum function. However, in the two-dimensional searching, especially in the high accuracy processes, the amount of searched points can be reduced by ten hundreds times, and the computation is much lower than the common spectrum peak searching method. The simulation results show that when the search thread number reaches 100, the searching process can effectively achieve the entire spectrum peak and get the correct DOA estimation.

A Root-MUSIC Algorithm for Angle Estimation in Bistatic MIMO Radar

2013 ◽  
Vol 756-759 ◽  
pp. 4031-4035
Author(s):  
Jia Wei Liu ◽  
Ren Zheng Cao ◽  
Xiao Fei Zhang
Keyword(s):  
Doa Estimation ◽  
Mimo Radar ◽  
Signal Classification ◽  
Music Algorithm ◽  
Angle Estimation ◽  
Multiple Signal Classification ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Roots Of Polynomials ◽  
Load Simulation

This paper discusses the problem of direction of departure (DOD) and direction of arrival (DOA) estimation using the root multiple signal classification (MUSIC) algorithm in a bistatic multiple input and multiple output (MIMO) radar. The proposed algorithm gets the estimation of DOA and DOD via computing the roots of polynomials and it avoids the spectral peak searching in the conventional MUSIC algorithm. Thus the Root-MUSIC algorithm has much lower computational load. Simulation results illustrate our proposed algorithm has better angle estimation performance than the conventional algorithms.

scholarly journals The PARAFAC-MUSIC Algorithm for DOA Estimation with Doppler Frequency in a MIMO Radar System

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Nan Wang ◽  
Wenguang Wang ◽  
Fan Zhang ◽  
Yunneng Yuan
Keyword(s):  
Doppler Frequency ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Radar System ◽  
Signal Classification ◽  
Moving Targets ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Parallel Factor ◽  
Simulation Results

The PARAFAC-MUSIC algorithm is proposed to estimate the direction-of-arrival (DOA) of the targets with Doppler frequency in a monostatic MIMO radar system in this paper. To estimate the Doppler frequency, the PARAFAC (parallel factor) algorithm is firstly utilized in the proposed algorithm, and after the compensation of Doppler frequency, MUSIC (multiple signal classification) algorithm is applied to estimate the DOA. By these two steps, the DOA of moving targets can be estimated successfully. Simulation results show that the proposed PARAFAC-MUSIC algorithm has a higher accuracy than the PARAFAC algorithm and the MUSIC algorithm in DOA estimation.

Direction of Arrival Estimation with Compact Array Antennas

2009 ◽  
pp. 201-216
Author(s):  
Eddy Taillefer ◽  
Jun Cheng ◽  
Takashi Ohira
Keyword(s):  
Single Port ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Signal Classification ◽  
Direction Of Arrival Estimation ◽  
Multiple Signal Classification ◽  
Array Antennas ◽  
Power Pattern ◽  
Parasitic Array ◽  
Compact Array

This chapter presents direction of arrival (DoA) estimation with a compact array antenna using methods based on reactance switching. The compact array is the single-port electronically steerable parasitic array radiator (Espar) antenna. The antenna beam pattern is controlled though parasitic elements loaded with reactances. DoA estimation using an Espar antenna is proposed with the power pattern cross correlation (PPCC), reactance-domain (RD) multiple signal classification (MUSIC), and, RD estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms. The three methods exploit the reactance diversity provided by an Espar antenna to correlate different antenna output signals measured at different times and for different reactance values. The authors hope that this chapter allows the researchers to appreciate the issues that may be encountered in the implementation of direction-finding application with a single-port compact array like the Espar antenna.

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