Weak Signal Detection With Low-Bit Quantization in Colocated MIMO Radar
Yang, Shixing ; Yi, Wei ; Jakobsson, Andreas LU
; Wang, Yao
and Xiao, Hang
(2023)
In IEEE Transactions on Signal Processing
71.
p.447-460
- Abstract
This paper addresses the weak signal detection problem in a massive colocated multiple-input multiple-output (MIMO) radar. To cope with the sheer amount of data produced by the large-scale antennas, a low-bit quantizer is introduced in the sampling process to enable both for hardware limitations and a high detection performance. The generalized likelihood ratio test (GLRT) detector is proposed for the quantized data, with the batch gradient descent algorithm being introduced to form an estimate of the unknown parameters. Furthermore, as a low-complexity alternative to the GLRT detector, we propose a multi-bit Rao detector, yielding a closed-form test statistic, whose theoretical distribution is also presented. Finally, we refine the... (More)
This paper addresses the weak signal detection problem in a massive colocated multiple-input multiple-output (MIMO) radar. To cope with the sheer amount of data produced by the large-scale antennas, a low-bit quantizer is introduced in the sampling process to enable both for hardware limitations and a high detection performance. The generalized likelihood ratio test (GLRT) detector is proposed for the quantized data, with the batch gradient descent algorithm being introduced to form an estimate of the unknown parameters. Furthermore, as a low-complexity alternative to the GLRT detector, we propose a multi-bit Rao detector, yielding a closed-form test statistic, whose theoretical distribution is also presented. Finally, we refine the design of the quantizer by optimizing the quantization thresholds, which are obtained using the particle swarm optimization algorithm. Results from simulation and experimental data demonstrate the performance of the detectors using both unquantized and quantized data. They corroborate the theoretical analyses and show that the performance with 3-bit quantization yields a performance that approaches the cases without quantization, while reducing the overall complexity of the system substantially.
(Less)
- author
- Yang, Shixing
; Yi, Wei
; Jakobsson, Andreas
LU
; Wang, Yao
and Xiao, Hang
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Colocated MIMO radar, GLRT, multi-bit, Rao test, signal detection
- in
- IEEE Transactions on Signal Processing
- volume
- 71
- pages
- 14 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85149382515
- ISSN
- 1053-587X
- DOI
- 10.1109/TSP.2023.3246233
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 1991-2012 IEEE.
- id
- 0b06ba87-c819-4626-b852-7c2f93070e5e
- date added to LUP
- 2024-01-12 13:55:20
- date last changed
- 2024-02-09 10:53:10
@article{0b06ba87-c819-4626-b852-7c2f93070e5e,
abstract = {{<p>This paper addresses the weak signal detection problem in a massive colocated multiple-input multiple-output (MIMO) radar. To cope with the sheer amount of data produced by the large-scale antennas, a low-bit quantizer is introduced in the sampling process to enable both for hardware limitations and a high detection performance. The generalized likelihood ratio test (GLRT) detector is proposed for the quantized data, with the batch gradient descent algorithm being introduced to form an estimate of the unknown parameters. Furthermore, as a low-complexity alternative to the GLRT detector, we propose a multi-bit Rao detector, yielding a closed-form test statistic, whose theoretical distribution is also presented. Finally, we refine the design of the quantizer by optimizing the quantization thresholds, which are obtained using the particle swarm optimization algorithm. Results from simulation and experimental data demonstrate the performance of the detectors using both unquantized and quantized data. They corroborate the theoretical analyses and show that the performance with 3-bit quantization yields a performance that approaches the cases without quantization, while reducing the overall complexity of the system substantially.</p>}},
author = {{Yang, Shixing and Yi, Wei and Jakobsson, Andreas and Wang, Yao and Xiao, Hang}},
issn = {{1053-587X}},
keywords = {{Colocated MIMO radar; GLRT; multi-bit; Rao test; signal detection}},
language = {{eng}},
pages = {{447--460}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Signal Processing}},
title = {{Weak Signal Detection With Low-Bit Quantization in Colocated MIMO Radar}},
url = {{http://dx.doi.org/10.1109/TSP.2023.3246233}},
doi = {{10.1109/TSP.2023.3246233}},
volume = {{71}},
year = {{2023}},
}