Wideband Noise Interference Suppression for Sparsity-Based SAR Imaging Based on Dechirping and Double Subspace Extraction

Abstract

Sparsity-based synthetic aperture radar (SAR) imaging has attracted much attention since it has potential advantages in improving the image quality and reducing the sampling rate. However, it is vulnerable to deliberate blanket disturbance, especially wideband noise interference (WBNI), which severely damages the imaging quality. This paper mainly focuses on WBNI suppression for SAR imaging from a new perspective—sparse recovery. We first analyze the impact of WBNI on signal reconstruction by deducing the interference energy projected on the real support set of the signal under different observation parameters. Based on the derived results, we propose a novel WBNI suppression algorithm based on dechirping and double subspace extraction (DDSE), where the signal of interest (SOI) is reconstructed by exploiting the known geometric prior and waveform prior, respectively. The experimental results illustrate that the DDSE-based WBNI suppression algorithm for sparsity-based SAR imaging is effective and outperforms the other algorithms.

Special Issue on “Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement”

“…After a very careful peer-review process, a total of 32 papers were accepted. These works include SAR/ISAR [2][3][4][5][6][7][8][9], polarimetry [10][11][12], MIMO [13,14], direction of arrival (DOA)/direction of departure (DOD) [13][14][15], sparse sensing [5,14,16], ground-penetrating radar (GPR) [17][18][19], through-wall radar [20,21], coherent integration [22,23], clutter suppression [24,25], and meta-materials, among others [26][27][28][29][30][31]. All of these accepted papers are the latest research results and are expected to be further advanced, applied, and diverted.…”

Improved Main Lobe Cancellation Method for Suppression Directional Noise in HFSWR Systems

“…In other words, directional noise can be considered a kind of main lobe broadband noise interference. Currently, the research on HFSWR narrowband interference suppression by signal processing methods is relatively in-depth, mainly including frequency domain notch methods [24], parameter estimation methods [25], characteristic subspace spatial-based filtering methods [26], adaptive beam forming methods [27], blocking matrix preprocessing methods [28], eigenprojection matrix preprocessing methods [29], and blind source separation technique [30]. Adaptive beamforming technology can automatically form a notch in the interference direction.…”

“…Yao investigated a transient interference suppression method based on a spacetime cascade and an optimal sample selection strategy based on information geometry through interference correlation in the spatial domain [37]. G. Li et al [25] developed a wideband noise suppression method based on de-chirping and double subspace extraction. Chen proposed a suppression method based on fractional Fourier change and second-order blind identification [38].…”

CNN-Based Vehicle Target Recognition with Residual Compensation for Circular SAR Imaging

“…Research based on SAR and CSAR includes time-frequency analysis, 2D/3D imaging, digital elevation model (DEM), target detection and recognition, etc. [1][2][3][4][5][6][7][8][9][10][11].…”