Single-Channel DoA Estimation Based on Nonuniform Time-Modulated Array With Asynchronous Sampling

doi:10.1109/JSEN.2023.3286941

2024-07-15

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DOI：10.1109/JSEN.2023.3286941

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摘要

En 中文

Direction-of-arrival (DoA) estimation is an essential component for intelligent perception and precise navigation. However, conventional methods require multiple channels to collect signals, making them unsuitable for Internet of Things (IoT) devices due to high hardware complexity. Meanwhile, existing single-channel methods do not fully consider accuracy and practicality. In this article, we propose a novel single-channel DoA estimation method based on a nonuniform time-modulated array (NTMA) to reduce system complexity while maintaining high performance. The basic principle is to isolate the receiving signals of different antennas in the frequency domain for realizing a single channel. This article shows that hardware complexity can be significantly reduced by making full use of spectrum resources, mainly reflected in the reduction of multiple receivers into one. To improve the accuracy, we apply a 1-bit phase shifter to the array design, and the simulation results show that it leads to a 6-dB improvement in signal-to-noise ratio (SNR). In addition, because synchronous sampling requires a high sampling rate, we design a particular antenna array and adopt asynchronous sampling to quantize analog signals at a lower sampling rate of 15.36 MHz. The experimental results indicate that our method has a mean error below 0.27 degrees, and a maximum absolute error of 0.8 degrees when sources incident from 60 degrees, which is superior to other related works. Moreover, our method has advantages in complexity and practicality, making it expected to be widely applied to portable and cost-efficient devices.

Keyword:

Estimation

Direction-of-arrival estimation

Modulation

Harmonic analysis

Frequency modulation

Power harmonic filters

Complexity theory

Asynchronous sampling

direction finding

direction-of-arrival (DoA) estimation

Internet of Things (IoT)