Estimation and Mitigation of Time-Variant RFI Based on Iterative Dual Sparse Recovery in Ultra-Wide Band Through-Wall Radar

Abstract

This paper focuses on the time-variant radio frequency interference (RFI) issue that ultra-wide band (UWB) through-wall radar (TWR) is faced with, and presents an iterative dual sparse recovery (IDSR) framework to combat it. The framework consists of two stages: 1) RFI estimation and detection and 2) IDSR of scattered echoes from objects and RFI signals. In the first stage, an overlapped short time Fourier transform is employed to construct and update the discrete frequency Doppler spectrum (DFDS). Then, a minimum statistic operation is conducted on the DFDS to estimate RFI signals, followed by detection via a 1-D cell-averaging constant false alarm rate detector to determinate whether RFI signals exist or not. In the second stage, a dual sparse model of the collected signals is set up, based on the fast-time frequency sparsity of RFI signals because of their narrow bands and the Doppler frequency sparsity of scattered echoes from objects because of their limited moving velocities. The alternating direction method of multipliers (ADMM) is introduced to iteratively and alternately recover RFI signals and scattered echoes from objects. Specifically, the iterative hard thresholding (IHT) method is used to complete the two sparse recovery operations. The involved two sparse dictionaries are simple and only made up of inverse discrete Fourier transform basis and independent of the received signals. The IDSR framework is able to relieve the influences of RFI signals and scattered echoes from objects on each other, and thus can reconstruct the two type signals to the maximum limit. Field experiments using a UWB TWR were carried out to verify the proposed method.