One-Bit Radar Imaging Via Adaptive Binary Iterative Hard Thresholding

One-bit radar imaging has received much attention due to the low cost of the analog-to-digital converter (ADC) and the low storage and transmission burden. The one-bit radar imaging results using conventional one-bit compressive sensing (CS) algorithms, such as the binary iterative hard thresholding (BIHT) algorithm, are always contaminated by artifacts, especially under noisy conditions. In this paper, we present an adaptive-BIHT (A-BIHT) algorithm to mitigate artifacts and improve the one-bit radar imaging performance. In the proposed A-BIHT algorithm, we devise a quantization level parameter, and update the quantization level parameter and the imaging result in an iterative fashion by employing a relaxed quantization consistency condition. The relaxed quantization consistency condition is designed to allow some noisy one-bit measurements to be inconsistent. In this way, the proposed algorithm mitigates the effect of noise on consistent reconstruction, and thus, alleviates artifacts and improves the imaging quality. Simulations and experimental results demonstrate that the proposed A-BIHT method can provide superior imaging performance with suppressed artifacts compared with the conventional BIHT method.