Enhanced Root-MUSIC Algorithm Based on Matrix Reconstruction for Frequency Estimation

Zhu, Ying‐Jie; Zhang, Wuxiong; Yi, Huang; Xu, Hui

doi:10.3390/s23041829

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…Hence, with the proposed method it is more possible to obtain accurate position estimation than with MUSIC, ISF, SSF and the clustering algorithm. The definition of RMSE for position estimation is expressed as Equation (36).…”

Section: Simulation Resultsmentioning

confidence: 99%

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Self-Position Determination Based on Array Signal Subspace Fitting under Multipath Environments

Cao,

Li,

Tang

et al. 2023

Sensors

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A vehicle’s position can be estimated with array receiving signal data without the help of satellite navigation. However, traditional array self-position determination methods are faced with the risk of failure under multipath environments. To deal with this problem, an array signal subspace fitting method is proposed for suppressing the multipath effect. Firstly, all signal incidence angles are estimated with enhanced spatial smoothing and root multiple signal classification (Root-MUSIC). Then, non-line-of-sight (NLOS) components are distinguished from multipath signals using a K-means clustering algorithm. Finally, the signal subspace fitting (SSF) function with a P matrix is established to reduce the NLOS components in multipath signals. Meanwhile, based on the initial clustering estimation, the search area can be significantly reduced, which can lead to less computational complexity. Compared with the C-matrix, oblique projection, initial signal fitting (ISF), multiple signal classification (MUSIC) and signal subspace fitting (SSF), the simulated experiments indicate that the proposed method has better NLOS component suppression performance, less computational complexity and more accurate positioning precision. A numerical analysis shows that the complexity of the proposed method has been reduced by at least 7.64dB. A cumulative distribution function (CDF) analysis demonstrates that the estimation accuracy of the proposed method is increased by 3.10dB compared with the clustering algorithm and 11.77dB compared with MUSIC, ISF and SSF under multipath environments.

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Section: Simulation Resultsmentioning

confidence: 99%

“…Similar to Equation ( 4), R ESS l can be the eigenvalue decomposed into a noise subspace U n1 l . Since the noise subspace is orthogonal to the array manifold [36], we can get the 2(K−1)-degree polynomial…”

Section: Doa Estimation Of Multipath Signalsmentioning

confidence: 99%

Self-Position Determination Based on Array Signal Subspace Fitting under Multipath Environments

Cao,

Li,

Tang

et al. 2023

Sensors

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“…By utilizing the Root-MUSIC [ 32 ] idea, we use polynomial rooting instead of spectral peak search. Let

, and

.…”

Section: Traditional Based Joint Aoa and Toa Algorithmmentioning

confidence: 99%

Low-Complexity Joint Angle of Arrival and Time of Arrival Estimation of Multipath Signal in UWB System

Deng

Tang

et al. 2023

Sensors

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In an ultra-wideband (UWB) system, the two-dimensional (2D) multiple signal classification (MUSIC) algorithms based on high-precision 2D spectral peak search can jointly estimate the time of arrival (TOA) and angle of arrival (AOA). However, the computational complexity of 2D-MUSIC is very high, and the corresponding data model is only based on the dual antennas. To solve these problems, a low-complexity algorithm for joint AOA and TOA estimation of the multipath ultra-wideband signal is proposed. Firstly, the dual antenna sensing data model is extended to the antenna array case. Then, based on the array-sensing data model, the proposed algorithm transforms the 2D spectral peak search of 2D-MUSIC into a secondary optimization problem to extract the estimation of AOA via only 1D search. Finally, the acquired AOA estimations are brought back, and the TOA estimations are also obtained through a 1D search. Moreover, in the case of an unknown transmitted signal waveform, the proposed method can still distinguish the main path signal based on the time difference of arrival of different paths, which shows wider applications. The simulation results show that the proposed algorithm outperforms the Root-MUSIC algorithm and the estimation of signal parameters using the rotational invariance techniques (ESPRIT) algorithm, and keeps the same estimation accuracy but with greatly reduced computational complexity compared to the 2D-MUSIC algorithm.

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Research on sound source location technology of microphone array

Wang,

Cai,

et al. 2024

2024 9th International Conference on Signal and Image Processing (ICSIP)

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Enhanced Root-MUSIC Algorithm Based on Matrix Reconstruction for Frequency Estimation

Cited by 3 publications

References 23 publications

Self-Position Determination Based on Array Signal Subspace Fitting under Multipath Environments

Self-Position Determination Based on Array Signal Subspace Fitting under Multipath Environments

Low-Complexity Joint Angle of Arrival and Time of Arrival Estimation of Multipath Signal in UWB System

Research on sound source location technology of microphone array

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