Digital radars with low-resolution analog-to-digital converters (ADCs) can reduce digital processing complexity and power consumption but suffer from limited dynamic range. The poor dynamic range causes high radar cross-section (RCS) targets to mask low-RCS ones. To mitigate this issue, we propose operating the ADC at a high resolution during the initial slowtime slot of each radar frame. The high-resolution measurements are used to estimate the range and RCS of dominant targets, which, along with their known Doppler statistics, are used to construct a dither signal. This dither signal is then employed to acquire low-resolution ADC measurements in the subsequent slow-time slots. With the proposed receiver architecture, our method suppresses strong target returns in the low-resolution measurements, effectively unmasking weak targets. Simulations demonstrate significant improvements in target detection and reduced normalized mean square error in radar channel estimation compared to existing benchmarks.

Digital radars with low-resolution analog-to-digital converters (ADCs) have attracted attention as a solution to reducing the high digital processing complexity and power consumption at the receiver. Radars employing low-resolution ADCs, however, have a limited dynamic range, due to which high-radar cross section (RCS) targets mask low-RCS targets. The masking occurs because the quantized output is primarily determined by returns from high-RCS targets. To enhance the dynamic range of such radars, we propose to operate the ADC at a high resolution in the initial slow-time slot of each radar frame. The resulting high-resolution measurements are used together with the known Doppler statistics of dominant targets to construct a dither signal, which is used as a quantization threshold to acquire low-resolution ADC measurements in the subsequent slow-time slots. By incorporating situation awareness in the form of Doppler statistics, our dither signal can suppress returns from strong targets, effectively unmasking weak targets with low-resolution measurements. We analyze system performance in terms of the probability of detection and show that the proposed approach outperforms existing methods in enhancing the detection of weak targets. The simulations demonstrate that our method significantly improves target detection and reduces the normalized mean square error (NMSE) in the estimated radar channel over comparable benchmarks.