scholarly journals Adaptive Sparse Cyclic Coordinate Descent for Sparse Frequency Estimation

Signals ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 189-200
Author(s):  
Yuneisy E. Garcia Guzman ◽  
Michael Lunglmayr
Keyword(s):  
Frequency Estimation ◽  
Coordinate Descent ◽  
Signal Classification ◽  
Original Formulation ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
The Mean ◽  
Simulation Results ◽  
Frequency Grid ◽  
Cyclic Coordinate Descent

The frequency estimation of multiple complex sinusoids in the presence of noise is important for many signal processing applications. As already discussed in the literature, this problem can be reformulated as a sparse representation problem. In this letter, such a formulation is derived and an algorithm based on sparse cyclic coordinate descent (SCCD) for estimating the frequency parameters is proposed. The algorithm adaptively reduces the size of the used frequency grid, which eases the computational burden. Simulation results revealed that the proposed algorithm achieves similar performance to the original formulation and the Root-multiple signal classification (MUSIC) algorithm in terms of the mean square error (MSE), with significantly less complexity.

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.

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>

Harmonic Estimation Algorithm for Power System Based on Improved MUISC and Linear Neural Networks

2015 ◽  
Vol 9 (1) ◽  
pp. 445-451 ◽  
Author(s):  
Sun Ligong Ligong ◽  
Sun Xiangwen ◽  
Xiang Fei
Keyword(s):  
Neural Network ◽  
Power System ◽  
Frequency Estimation ◽  
Wiener Filter ◽  
Estimation Algorithm ◽  
Estimation Accuracy ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Harmonic Phase ◽  
Linear Neural Network

The paper proposes harmonic estimation algorithm for power system based on Multiple Signal Classification (MUSIC) and linear neural network because of the insufficiency of harmonic frequency estimation algorithm. The conventional MUSIC algorithm has the advantage of higher estimation accuracy, while the disadvantage is that the computational complexity is high and it cannot estimate the harmonic phase and amplitude. In the paper, a new harmonic estimation algorithm for power system is constructed with combining the MUSIC algorithm, the multistage Wiener filter (MSWF) and linear neural network. Theoretic analysis and simulation experiments show that the requirement to data is relatively low, and has good harmonic estimation accuracy and reliability.

Harmonic Frequency Estimation Based on Modified-MUSIC Algorithm in Power System

2015 ◽  
Vol 9 (1) ◽  
pp. 38-42 ◽  
Author(s):  
Xiangwen Sun ◽  
Ligong Sun
Keyword(s):  
Frequency Estimation ◽  
Estimation Method ◽  
Super Resolution ◽  
Small Data ◽  
Music Algorithm ◽  
Harmonic Frequency ◽  
Multiple Signal Classification ◽  
Analysis Techniques ◽  
Resolution Algorithm ◽  
Data Length

This paper presents a new harmonics frequency estimation method. Unlike the conventional harmonic frequency estimation method (fast Fourier transform), the new algorithm is based on spectrum analysis techniques often used to estimate the direction of angle; the most popular is the multiple signal classification (MUSIC) algorithm. The drawbacks of MUSIC algorithm are concluded. Improved-MUSIC approximation algorithm is introduced and compared with FFT based on algorithm for harmonic frequency estimation. Theoretical analysis and simulations show this algorithm is a super- resolution algorithm with small data length.

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.

Sign in / Sign up

Export Citation Format

Share Document