Reference : DoA Estimation Using Low-Resolution Multi-BitSparse Array Measurements |
Scientific journals : Article | |||
Engineering, computing & technology : Electrical & electronics engineering | |||
Security, Reliability and Trust | |||
http://hdl.handle.net/10993/47509 | |||
DoA Estimation Using Low-Resolution Multi-BitSparse Array Measurements | |
English | |
Sedighi, Saeid ![]() | |
Mysore Rama Rao, Bhavani Shankar ![]() | |
Soltanalian, Mojtaba ![]() | |
Ottersten, Björn ![]() | |
2021 | |
IEEE Signal Processing Letters | |
Institute of Electrical and Electronics Engineers | |
Yes (verified by ORBilu) | |
International | |
1070-9908 | |
United States | |
[en] Direction of arrival (DoA) estimation ; low-resolution quantization ; Sparse linear arrays | |
[en] This letter studies the problem of Direction of Arrival (DoA) estimation from low-resolution few-bit quantized data collected by Sparse Linear Array (SLA). In such cases, contrary to the one-bit quantization case, the well known arcsine law cannot be employed to estimate the covaraince matrix of unquantized array data. Instead, we develop
a novel optimization-based framework for retrieving the covaraince matrix of unquantized array data from low-resolution few-bit measurements. The MUSIC algorithm is then applied to an augmented version of the recovered covariance matrix to find the source DoAs. The simulation results show that increasing the sampling resolution to $2$ or $4$ bits per samples could significantly increase the DoA estimation performance compared to the one-bit sampling regime while the power consumption and implementation costs is still much lower in comparison to the high-resolution sampling implementations. | |
Fonds National de la Recherche - FnR | |
Researchers ; Professionals ; Students | |
http://hdl.handle.net/10993/47509 | |
10.1109/LSP.2021.3090647 |
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