A Robust Direction of Arrival Estimation Method for Uniform Circular Array

Xu, Zhengqin; Wu, Shiqian; Yu, Zhuliang; Guang, Xingyu

doi:10.3390/s19204427

Cited by 8 publications

(4 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By exploiting the second-order statistics, more degrees of freedom are acquired, which overcomes the Nyquist theorem’s restriction on array apertures [ 36 , 37 , 38 , 39 ]. Meanwhile, when using a circular array, ESPRIT exploits the rotational invariance property to obtain paired two-dimensional DOA estimation without any prior knowledge, which avoids the secondary peak-search and accelerates the process speed [ 40 , 41 , 42 ].…”

Section: Introductionmentioning

confidence: 99%

Acoustic-Based Rolling Bearing Fault Diagnosis Using a Co-Prime Circular Microphone Array

Chen

2023

Sensors

View full text Add to dashboard Cite

This study proposes a high-efficiency method using a co-prime circular microphone array (CPCMA) for the bearing fault diagnosis, and discusses the acoustic characteristics of three fault-type signals at different rotation speeds. Due to the close positions of various bearing components, radiation sounds are seriously mixed, and it is challenging to separate the fault features. Direction-of-arrival (DOA) estimation can be used to suppress noise and directionally enhance sound sources of interest; however, classical array configurations usually require a large number of microphones to achieve high accuracy. To address this, a CPCMA is introduced to raise the array’s degrees of freedom in order to reduce the dependence on the microphone numbers and computation complexity. The estimation of signal parameters via rotational invariance techniques (ESPRIT) applied to a CPCMA can quickly figure out the DOA estimation without any prior knowledge. By using the techniques above, a sound source motion-tracking diagnosis method is proposed according to the movement characteristics of impact sound sources for each fault type. Additionally, more precise frequency spectra are obtained, which are used in combination to determine the fault types and locations.

show abstract

Section: Introductionmentioning

confidence: 99%

Acoustic-Based Rolling Bearing Fault Diagnosis Using a Co-Prime Circular Microphone Array

Chen

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…The mode space transformation, also known as beam space transformation, is widely used to solve DOA estimation problems in UCA. In [11,12], the mode space transformation method has been adopted to improve the accuracy of DOA estimation in the UCA. Also in [13], the authors have proposed a low complexity sparse beamspace DOA estimation method for UCA.…”

Section: Introductionmentioning

confidence: 99%

A Robust Algorithm for DOA Estimation of Coherent Sources with UCA

et al. 2022

View full text Add to dashboard Cite

Direction of arrival (DOA) estimation of coherent sources with a uniform circular array (UCA) is an intractable problem. The method-of-direction-estimation (MODE) algorithm has strong superiority in handling coherent sources compared with the classical MUSIC, and ESPRIT algorithms. However, MODE is sensitive to source numbers and does not work well in the UCA scenario. In order to improve the performance of MODE, a robust DOA estimation method named UCA-PUMA (principal-eigenvector-utilization-for-modal-analysis) is proposed. The complicated non-Vandermonde structured steering vector of UCA is transformed into a virtual Vandermonde structured steering vector in mode space. The proposed method gives a closed-form solution compared with the original UCA-MODE algorithm. The performance of the UCA-PUMA method is evaluated by simulations. Simulation results demonstrate that the UCA-PUMA is more robust to source numbers than the UCA-MODE, and coherent sources can be handled without spatial smoothing. In addition, the UCA-PUMA fully takes advantage of the UCA, which is able to discriminate sources coming from a 360o azimuthal field of view.

show abstract

“…Belloni [16] analyzes the error of this algorithm, provides design guidelines for choosing the key UCA configuration parameters and proposes a novel technique for bias removal. Xu [17] proposes an accurate and reliable technique to estimate DOA of source signals based on random sample consensus algorithm. Wang [18] studies the performance of the algorithm in the case of coherent sources.…”

Section: Introductionmentioning

confidence: 99%

A DOA Estimation Method for Uniform Circular Array Based on Virtual Interpolation and Subarray Rotation

2021

View full text Add to dashboard Cite

A uniform linear array (ULA) or a multi-element planar array composed of uniform linear arrays is the main applied research array for direction-of-arrival (DOA) estimation in array signal processing.In recent years, the uniform circular array (UCA) is getting more attention because its consistent azimuthal beam resolution, but the DOA estimation algorithm of a UCA is complex and difficult to implement. To solve this problem, a UCA positioning method based on virtual interpolation and subarray rotation (VISAR) is proposed. This method effectively reduces the computational complexity of DOA estimation for a UCA, and the simulation analysis of the algorithm shows that in terms of positioning performance, the proposed algorithm is better than the existing virtual interpolation algorithms in the case of a low signal-to-noise ratio (SNR). INDEX TERMSDirection of arrival (DOA), Uniform circular array (UCA), Virtual Interpolation, Subarray rotation. I.

show abstract

A Robust Direction of Arrival Estimation Method for Uniform Circular Array

Cited by 8 publications

References 33 publications

Acoustic-Based Rolling Bearing Fault Diagnosis Using a Co-Prime Circular Microphone Array

Acoustic-Based Rolling Bearing Fault Diagnosis Using a Co-Prime Circular Microphone Array

A Robust Algorithm for DOA Estimation of Coherent Sources with UCA

A DOA Estimation Method for Uniform Circular Array Based on Virtual Interpolation and Subarray Rotation

Contact Info

Product

Resources

About