  Radio frequency interference (RFI) mitigation is critical to the proper
operation of ultra-wideband (UWB) radar systems since RFI can severely degrade
the radar imaging capability and target detection performance. In this paper,
we address the RFI mitigation problem for one-bit UWB radar systems. A one-bit
UWB system obtains its signed measurements via a low-cost and high rate
sampling scheme, referred to as the Continuous Time Binary Value (CTBV)
technology. This sampling strategy compares the signal to a known threshold
varying with slow-time and therefore can be used to achieve a rather high
sampling rate and quantization resolution with rather simple and affordable
hardware. This paper establishes a proper data model for the RFI sources and
proposes a novel RFI mitigation method for the one-bit UWB radar system that
uses the CTBV sampling technique. Specifically, we first model the RFI sources
as a sum of sinusoids with frequencies fixed during the coherent processing
interval (CPI) and we exploit the sparsity of the RFI spectrum. We extend a
majorization-minimization based 1bRELAX algorithm, referred to as 1bMMRELAX, to
estimate the RFI source parameters from the signed measurements obtained by
using the CTBV sampling strategy. We also devise a new fast frequency
initialization method based on the Alternating Direction Method of Multipliers
(ADMM) methodology for the extended 1bMMRELAX algorithm to significantly
improve its computational efficiency. Moreover, an ADMM-based sparse method is
introduced to recover the desired radar echoes using the estimated RFI
parameters. Both simulated and experimental results are presented to
demonstrate that our proposed algorithm outperforms the existing digital
integration method, especially for severe RFI cases.
