Gridless Parameter Estimation for Pulse–Doppler Radar Under Limited Bit Budgets

In this work, we investigate the gridless parameter estimation of pulse–Doppler radar targets using a reduced number of samples under a limited bit budget. We propose a hybrid analog and digital (HAD) acquisition system integrating a tunable analog component, low-resolution quantizers, and a digital filter. Under the framework of task-based quantization, the HAD architecture is designed to optimize target parameter estimation within the constraints of the bit budget. Specifically, a small subset of the received signal samples is observed and the low-rank parameter matrix is recovered using matrix completion techniques. The atomic norm minimization method is applied to reconstruct the complete parameter matrix, enabling gridless estimation of the parameters. Numerical experiments are conducted to validate the effectiveness of the proposed receiver in gridless parameter estimation.