Atomic Network-Based DOA Estimation Using Low-Bit ADC

Autor: Peng Chen, Yuxuan Yao, Shuran Sheng, Zhimin Chen, Lenan Wu
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Electronics
Volume 10
Issue 6
Electronics, Vol 10, Iss 738, p 738 (2021)
ISSN: 2079-9292
DOI: 10.3390/electronics10060738
Popis: In the direction of arrival (DOA) estimation problem, when a low-bit analog to digital converter (ADC) is used, the estimation performance severely deteriorates. In this paper, the DOA estimation problem is considered in a low-cost direction finding system with low-bit ADC. To eliminate quantization noise, we propose a novel network ADCnet, which is a composition of fully connected layers and exponential linear unit (ELU) layers, and the input signals are the received signals using low-bit ADC. After the ADCnet, an AtomicNet is also proposed to estimate the DOA from the denoised signals, where atomic vectors are corresponding to the steer vectors. A loss function considering both the reconstruction performance and the sparsity is proposed in the AtomicNet. Different from the exiting atomic norm-based methods, the proposed method can avoid an optimization problem and estimate the DOA with lower computational complexity. Simulation results show that the proposed method outperforms the existing methods in the DOA estimation performance using low-bit ADC.
Databáze: OpenAIRE