Recovery of missing spectral information in ultra-wideband synthetic aperture radar (SAR) data

Abstract

In this paper, we present a novel technique to recover the missing spectral information in multiple frequency bands of ultra-wideband (UWB) synthetic aperture radar (SAR) data that are either corrupted (due to the presence of interference sources) or nonexistent (because of no transmission in the prohibited frequency bands). Although the spectral information is lost due to the contaminated and missing frequency bands, each backscatter receive data record can be modeled as a linear combination of the spectrally filtered and time-shifted versions of the transmitted waveform. Thus, the target information (range, amplitude, and phase) can be computed based on direct sparse recovery via orthogonal matching pursuit using a dictionary that contains many spectrally filtered and time-shifted versions of the transmitted waveform. On the other hand, the desired receive signal (with full spectral information) can be modeled as a linear combination of the time-shifted versions of the desired transmitted waveform (with full spectrum). Thus, once the target information is computed by the sparse recovery process using the receive data and the dictionary, the desired received signal can be reconstructed using the target information and the desired transmitted waveform. Using both simulation data and SAR data from the U.S. Army Research Laboratory (ARL) UWB SAR, we show that the proposed technique can successfully recover the information from the missing or corrupted frequency bands. The paper also compares the result to that using the conventional technique that simply zeros out the fast Fourier transform (FFT) bins that correspond to the corrupted frequency bands.