A Two-Stage Approach for TSNB and ITWB RFI Mitigation in P- and L-Band SAR Data
Zongsen Lv, Zhimin Zhang, Huaitao Fan, Zhen Chen, Jinsong Qiu, Yulun Wu
Abstract
P- and L-band synthetic aperture radar (SAR) sensors have foliage- and ground-penetrating imaging capabilities and thus contribute to missions such as deforestation monitoring, biomass estimation, and deformation measurements. The spectrums they employed are also allocated to many services, such as radio navigation satellite services, radio location services, telecommunication, and broadcasting, which is prone to generate harmful radio frequency interference (RFI) to SAR including time stationary narrow band (TSNB) and intermittently transmitted wideband (ITWB) versions. Researchers generally perform on-ground processing to mitigate RFIs by which notch filtering is the best known. However, the phenomena of side-lobe uplift and SNR degradation caused by spectral gaps will deteriorate SAR image quality and further affect image interpretation. This article models and characterizes the signature of TSNB and ITWB RFI in P- and L-band SAR, and on this basis, a two-stage approach is developed to mitigate RFI that overcomes the drawbacks of notch filtering-based approaches. In the first stage, a spectrum cancellation-based RFI detector is proposed, which simultaneously locates RFI and produces an orthogonal projection operator. In the second stage, a low-rank approximation model regulated by truncated nuclear norm, which is solved by the alternating direction method of multipliers (ADMM), is established to recover the missing spectral information. Experiments are conducted extensively on simulated data as well as real-world data collected by Advanced Land Observing Satellite (ALOS) Phased-Array L-Band Synthetic Aperture Radar (PALSAR) system and a P-band airborne SAR system to validate the proposed approach.