This paper addresses the loss (if any) in radar target recognition performance if the features are extracted directly in the compressive domain compared to those extracted in the classical (Nyquist rate) domain. This study examines the impact of extracting wavelet features from compressively sampled signatures on recognition performance. Two other comparison schemes involve; 1) signal reconstruction after compressive sampling followed by wavelet decomposition, and 2) wavelet decomposition applied directly onto compressively sampled signatures using the compressive-domain equivalent discrete wavelet transform. These comparisons use real radar signatures collected in a compact range, and include various additive noise and azimuth ambiguity scenarios.

© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Ismail Jouny, "Radar target recognition using wavelet-based features extracted from compressively sensed signatures ," Proc. SPIE 10988, Automatic Target Recognition XXIX, 109880H (Presented at SPIE Defense + Commercial Sensing: April 16, 2019; Published: 14 May 2019); https://doi.org/10.1117/12.2513953.