Wideband DOA estimation based on focusing signal subspace

Ma, Fuqiang; Zhang, Xiaotong

doi:10.1007/s11760-018-1396-4

Cited by 22 publications

(10 citation statements)

References 22 publications

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“…A suitable focus transformation matrix T( f j ) is constructed to minimize the error between the U S ( f j ) and U S ( f 0 ), which can be constrained by the Frobenius-norm in focusing signal subspace (FSS) [38] algorithms: min…”

Section: Wideband Beamforming By Matrix Transformationmentioning

confidence: 99%

Underwater wideband coherent signals DOA estimation using sparse representation and deconvolution

Fan,

Tao,

Qian

et al. 2024

Meas. Sci. Technol.

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The beamforming-based direction of arrival (DOA) estimation method is widely used because of its advantages of robustness, which requires large array aperture to ensure high spatial resolution. The deconvolution beam-forming method has high-resolution DOA estimation without increasing the array aperture. However, it is based on the assumption of incoherent narrowband signals. When the signals are coherent, the high cross-term sidelobes result in large estimation errors. In this paper, a new sparse deconvolution beamforming is proposed to estimate the DOA of wideband coherent signals. First, extending the deconvolution beamforming method to the wideband case by matrix transformation. Second, solving the problem that the traditional deconvolution algorithm is not applicable to coherent signals by sparse representation. Numerical simulations and underwater experiments are presented to verify the effectiveness of the proposed method. The results show that even at low Signal-to-Noise Ratio (SNR) and blind environment parameters, the proposed method can obtain better performance compared with other coherent signals DOA estimation algorithms.

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Section: Wideband Beamforming By Matrix Transformationmentioning

confidence: 99%

Underwater wideband coherent signals DOA estimation using sparse representation and deconvolution

Fan,

Tao,

Qian

et al. 2024

Meas. Sci. Technol.

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“…The main drawback of CSSM is the performance dependency on the pre-estimated DOAs so that errors in the pre-estimation of DOAs will degrade the DOA estimation accuracy [18]. To overcome this drawback, several techniques were proposed such as autofocusing algorithm for DOA estimation [19] and focusing signal subspace (FSS) algorithm [20]. In FSS algorithm, a unitary focusing matrix is constructed by combining the eigenvector of signal subspace at the reference frequency with the eigenvector of signal subspace at discrete frequencies.…”

Section: Introductionmentioning

confidence: 99%

A Compressive Sensing Based Computationally Efficient High-Resolution DOA Estimation of Wideband Signals Using Generalized Coprime Arrays

El-Khamy,

El-Shazly,

Eltrass

2024

Wireless Pers Commun

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Most recent state-of-the-art wideband direction of arrival (DOA) estimation techniques achieve reasonable accuracy at the expenses of high computational complexity. In this paper, a new computationally efficient approach based on compressive sensing (CS) is introduced for high resolution wideband DOA estimation. The low software complexity is achieved utilizing CS with deterministic chaotic Chebyshev sensing matrices that allow reducing the measurement vector dimension, while the high-resolution DOA estimation is acquired utilizing an efficient generalized coprime array configuration. The effectiveness of the introduced approach in enhancing the DOA estimation precision and reducing the computational complexity is studied along with a detailed comparison between three state-of-the-art wideband DOA estimation techniques, namely incoherent signal subspace method (ISSM), focusing signal subspace (FSS), and modified test of orthogonality of projected subspaces (mTOPS) with and without applying the proposed CS technique. The performance is examined utilizing various assessment metrics such as the spatial spectrum, the computational time, and the root mean square error between estimated and actual DOAs when varying the signal-to-noise ratio and number of elements. Results reveal that applying the proposed CS technique to the three algorithms (ISSM, FSS, and mTOPS) provides significant reduction in the execution time needed for the DOA estimation without affecting the resolution accuracy under various set of parameters. This reveals the importance of the proposed approach in wideband wireless communication systems.

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“…The use of such signals with large time-bandwidth products and low power in radar systems makes the detection and parametric estimation including a DOA of such signals difficult. There has been some research on wideband linear frequency modulated (LFM) signals using the synthetic data [3][4][5][6][7][8][9][10][11] or experimental data for sonar applications [12,13] and frequency-modulated continuous-wave (FMCW) signals at microwave frequencies [14][15][16][17][18]. This work investigates DOA estimation of pulsed wideband and high chirp-rate LFM signals used in modern radar applications.…”

Section: Introductionmentioning

confidence: 99%

Experimental validation of direction of arrival estimation for high chirp‐rate linear frequency modulated radar signals

Mulinde

Attygalle

Aziz

2021

IET Radar Sonar & Navi

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Direction of arrival (DOA) estimation for signals with large time‐bandwidth products is very important in modern communication and radar systems. Traditional narrowband DOA estimation algorithms are not accurate for such wideband signals. Further complexities arise with non‐stationary signals, for example, high chirp‐rate linear frequency modulated (LFM). These complexities imply that achieving real‐time performance with good DOA estimation accuracy is a challenge. This article uses experimentally acquired data on high chirp‐rate LFM signals to validate a channelised version of MUltiple SIgnal Classification (MUSIC) for DOA estimation. This technique eliminates pre‐processing and incoherently combines spatial pseudospectra from individual frequency channels to obtain a single accurate estimate and has much less computational complexity compared to coherent techniques. LFM signals of up to 500 MHz bandwidth and chirp rates of up to 50 MHz/μs have been used in the investigations and results show accurate DOA estimation at low SNR (0 dB). This technique is suitable for even wider operational bandwidths and low latency implementations. To the best of our knowledge, this is the first time DOA estimation for such high chirp‐rate LFM signals has been validated using real experimental data which is also corroborated with validation using synthetic data.

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Wideband DOA estimation based on focusing signal subspace

Cited by 22 publications

References 22 publications

Underwater wideband coherent signals DOA estimation using sparse representation and deconvolution

Underwater wideband coherent signals DOA estimation using sparse representation and deconvolution

A Compressive Sensing Based Computationally Efficient High-Resolution DOA Estimation of Wideband Signals Using Generalized Coprime Arrays

Experimental validation of direction of arrival estimation for high chirp‐rate linear frequency modulated radar signals

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