  Radio frequency interference (RFI) mitigation and radar echo recovery are
critically important for the proper functioning of ultra-wideband (UWB) radar
systems using one-bit sampling techniques. We recently introduced a technique
for one-bit UWB radar, which first uses a majorization-minimization method for
RFI parameter estimation followed by a sparse method for radar echo recovery.
However, this technique suffers from high computational complexity due to the
need to estimate the parameters of each RFI source separately and iteratively.
In this paper, we present a computationally efficient joint RFI mitigation and
radar echo recovery framework to greatly reduce the computational cost.
Specifically, we exploit the sparsity of RFI in the fast-frequency domain and
the sparsity of radar echoes in the fast-time domain to design a one-bit
weighted SPICE (SParse Iterative Covariance-based Estimation) based framework
for the joint RFI mitigation and radar echo recovery of one-bit UWB radar. Both
simulated and experimental results are presented to show that the proposed
one-bit weighted SPICE framework can not only reduce the computational cost but
also outperform the existing approach for decoupled RFI mitigation and radar
echo recovery of one-bit UWB radar.
