Spatial spectrum for direction of arrival estimation of multiple non‐stationary wideband sources in the time–frequency plane

Cholnam, Om; Dokkil, Kang; Cholyong, Jong

doi:10.1049/iet-spr.2016.0022

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…We estimate the DOAs by the method in [36] and then calculate the steering matrix

A

. The separating matrix

W ()(, f)

is calculated as the pseudo‐inverse matrix of

A ()(, f)

.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…a m f , P = exp − j2π f τ m (36) where τ m is the delay time taken by a plane wavefront to travel from the mth sensor to the origin…”

Section: Source Localisation Using Music Algorithmmentioning

confidence: 99%

“…The sampling frequency is f s = 8192 Hz and the length of a frame is 10,000. We estimate the DOAs by the method in [36] and then calculate the steering matrix A. The separating matrix W f is calculated as the pseudo-inverse matrix of A f .…”

Section: Simulation On Source Separation Using Source Location Estimatesmentioning

confidence: 99%

See 2 more Smart Citations

Blind signal separation method and relationship between source separation and source localisation in the TF plane

Cholnam¹,

Chongil²,

Chol³

2018

IET signal process.

Self Cite

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A method for solving the instantaneous mixtures of the multiple non-stationary wideband signals in the timefrequency (TF) plane is proposed. The blind source separation is performed by calculation of spatial TF distribution matrices, estimation of a separating matrix, estimation of permutation matrices and scaling matrices and TF synthesis. The simulation result shows that the proposed method improves the signal-to-distortion ratio than the preceding methods. Moreover, also the mutual relationship between the source localisation and the source separation is clarified. The source localisation methods using the source separation result and the source separation method using the source localisation result are proposed.

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“…We estimate the DOAs by the method in [36] and then calculate the steering matrix

A

. The separating matrix

W ()(, f)

is calculated as the pseudo‐inverse matrix of

A ()(, f)

.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…a m f , P = exp − j2π f τ m (36) where τ m is the delay time taken by a plane wavefront to travel from the mth sensor to the origin…”

Section: Source Localisation Using Music Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Blind signal separation method and relationship between source separation and source localisation in the TF plane

Cholnam¹,

Chongil²,

Chol³

2018

IET signal process.

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is known that the time-frequency representation (TFR) is better suited for showing the energy distribution of the frequency components through the time. For the traditional TFR techniques, the Wigner-Ville distribution (WVD) [2] plays an important role in the target detection [3][4][5], radar imaging [6], rotating machinery [7], monitoring [8], speech, imaging processing [9,10], parameter estimation [11,12], and among others [13][14][15][16][17]. Due to the high computation complexity, it is a time-consuming process to calculate the WVD.…”

Section: Introductionmentioning

confidence: 99%

Efficient method for the field‐programmable gate arrays calculation of Wigner‐Ville distribution

Xiao-wei

Zuo

Huang

et al. 2019

IET signal process.

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Various signals of finite length are often analysed by the Wigner-Ville distribution (WVD). Thus, this article deals with the implementation of their discrete WVDs on field-programmable gate arrays (FPGAs). For the discrete WVD, its calculation procedures are composed of the autocorrelation function and Fourier transform. Since the autocorrelation procedure is the most time-consuming step in the entire computation process, the authors analyse the calculation procedure of autocorrelation function in detail. Here the proposed efficient method just calculates partial non-zero elements of the autocorrelation matrices in order to reduce the computation complexity. The FFT (built-in FPGAs) is then utilised to acquire the discrete WVD. In addition, the idea of the fully-pipelined and parallelism is borrowed to reduce the running time but at the cost of recourses. Finally, the authors provide implementations of both authors proposed method and two other algorithms on different FPGAs. The experimental results show that the Intel Arria-10 FPGA families are the better choice in the floating point arithmetic and that authors method has the best performance.

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Wideband array self-calibration and DOA estimation under large position errors

Liu

Zhao

et al. 2018

Digital Signal Processing

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Spatial spectrum for direction of arrival estimation of multiple non‐stationary wideband sources in the time–frequency plane

Cited by 6 publications

References 16 publications

Blind signal separation method and relationship between source separation and source localisation in the TF plane

Blind signal separation method and relationship between source separation and source localisation in the TF plane

Efficient method for the field‐programmable gate arrays calculation of Wigner‐Ville distribution

Wideband array self-calibration and DOA estimation under large position errors

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