Mixed Quantization of One-bit and Full-precision Signals for Direction of Arrival Estimation

Direction of Arrival (DOA) estimation is a crucial technology in array signal processing. One-bit quantization is commonly employed to reduce hardware costs in DOA estimation, yet it introduces significant quantization noise, adversely affecting the accuracy of DOA estimation. To mitigate this issue, we propose a mixed-precision quantization method that integrates one-bit and full-precision quantization. We derive the covariance matrix of signals subjected to mixed-precision quantization and establish the Cramér-Rao Bound (CRB) for this quantization approach. Through experiments, we evaluate the performance of mixed-precision quantization in both DOA estimation and target recognition. The results demonstrate that mixed-precision quantization significantly enhances DOA estimation accuracy compared to one-bit quantization. Additionally, this method improves the target recognition capability of signals. Our approach strikes a better balance between hardware costs and quantization errors, offering a promising solution for practical applications.