Direction Finding Using Compressive One-Bit Measurements

In this paper, we propose a novel direction-of-arrival (DOA) estimation scheme, which is named the compressive one-bit measurement scheme. In the proposed scheme, the one-bit quantization technique is used to reduce the system cost in terms of the analog-to-digital converter (ADC). However, the one-bit quantization leads to a serious information loss, thus compromising the estimation accuracy. Inspired by the compressive sensing theory, the compressive measurement method is used to expand the receive array aperture. To be specific, the compressive measurement allows more sensors than the number of front-end circuit chains to be used. Thus, the additional information is obtained, and the estimation performance can be improved from the system structure layer. It is noted that by introducing the compression operation, the relationship between the normalized and the original covariance matrix is different to the conventional one-bit quantization structure. Thus, two DOA estimation algorithms, i.e., the iterative compressive measurement-based multiple signal classification (CM-MUSIC) and the compressive sensing (CS)-based algorithm, are proposed for the compressive one-bit measurement scheme. The iterative CM-MUSIC can achieve a high-resolution estimation, whereas the CS-based algorithm can resolve more sources than the sensors. Numerical simulations validate the effectiveness of the proposed scheme.