Coherent DOA Estimation of Multi-Beam Frequency Beam-Scanning LWAs Based on Maximum Likelihood Algorithm

Multi-Beam frequency scanning leaky-wave antennas (FBS-LWAs) offer a viable solution for hardware miniaturization in direction-of-arrival (DOA) estimation systems. However, the presence of multiple spatial harmonics results in responses in multiple directions for a given incident source, introducing estimation ambiguity and significantly challenging accurate DOA estimation. Moreover, due to the nonlinear frequency response of the FBS-LWA, its response matrix does not satisfy the Vandermonde structure, which renders common rank-recovery techniques ineffective for processing coherent signals. As a result, the DOA estimation of coherent sources using multi-beam FBS-LWAs remains an open and challenging problem. To address this issue, this paper proposes a novel DOA estimation method for coherent signals based on multi-beam frequency scanning leaky-wave antennas. First, the received signals are transformed into the frequency domain via fast Fourier transform (FFT) to construct the signal data matrix from which the covariance matrix is computed.Then, conventional beamforming (CBF) is employed to obtain an initial estimate of the angle set, which will be further refined by a smaller grid to form a candidate angle set. Finally, a maximum likelihood algorithm based on the stochastic principle (Sto-ML) is used to suppress the interference of the parasitic directions and select the final DOA estimates from the candidate angle set. Simulation results show that the proposed method effectively mitigates the impact of parasitic directions and achieves an accurate DOA estimation of multiple coherent sources, even under both low and medium-to-high signal-to-noise ratio (SNR) conditions.

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Publication Details

Journal
Sensors
Published
2025-06-17
DOI
https://doi.org/10.3390/s25123791
Citations
2
Primary Topic
Direction-of-Arrival Estimation Techniques
Type
article
Field-Weighted Citation Impact
2.97

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article

Coherent DOA Estimation of Multi-Beam Frequency Beam-Scanning LWAs Based on Maximum Likelihood Algorithm

Biyun Ma, Rongping Zeng, Yide Wang, Zhu Qingqing et al.
2 citations
Sensors
Direction-of-Arrival Estimation Techniques
2.97
article

Coherent DOA Estimation of Multi-Beam Frequency Beam-Scanning LWAs Based on Maximum Likelihood Algorithm

Biyun Ma, Rongping Zeng, Yide Wang, Zhu Qingqing, W. X. Fang, Yifan Yang
article en
2 citations

Abstract

Multi-Beam frequency scanning leaky-wave antennas (FBS-LWAs) offer a viable solution for hardware miniaturization in direction-of-arrival (DOA) estimation systems. However, the presence of multiple spatial harmonics results in responses in multiple directions for a given incident source, introducing estimation ambiguity and significantly challenging accurate DOA estimation. Moreover, due to the nonlinear frequency response of the FBS-LWA, its response matrix does not satisfy the Vandermonde structure, which renders common rank-recovery techniques ineffective for processing coherent signals. As a result, the DOA estimation of coherent sources using multi-beam FBS-LWAs remains an open and challenging problem. To address this issue, this paper proposes a novel DOA estimation method for coherent signals based on multi-beam frequency scanning leaky-wave antennas. First, the received signals are transformed into the frequency domain via fast Fourier transform (FFT) to construct the signal data matrix from which the covariance matrix is computed.Then, conventional beamforming (CBF) is employed to obtain an initial estimate of the angle set, which will be further refined by a smaller grid to form a candidate angle set. Finally, a maximum likelihood algorithm based on the stochastic principle (Sto-ML) is used to suppress the interference of the parasitic directions and select the final DOA estimates from the candidate angle set. Simulation results show that the proposed method effectively mitigates the impact of parasitic directions and achieves an accurate DOA estimation of multiple coherent sources, even under both low and medium-to-high signal-to-noise ratio (SNR) conditions.

SensorsVol. 25(12)
Centre National de la Recherche Scientifique (FR), China Mobile (China) (CN), Institut d'Électronique et des Technologies du numéRique (FR), South China University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province
Openalex Percentile: Top 9%
Direction-of-Arrival Estimation Techniques
2.97
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