Title :
Compressive sensing based ISAR: Performance evaluation
Author :
Giusti, E. ; Bacci, A. ; Tomei, S. ; Martorella, M.
Author_Institution :
Dept. of Inf. Eng., Univ. of Pisa, Pisa, Italy
Abstract :
Compressive Sensing theory has been recently proven to be a valid tool to reconstruct ISAR images by using a limited amount of data samples. This property has gained the attention of the radar scientific community as it seems to overcome the Nyquist theorem. However, the capability of the CS to effectively reconstruct an ISAR image is still to be proven. From here, the need to provide the means to measure the CS based algorithm performance. A set of parameters to measure CS-based ISAR algorithm performance is provided in this paper and some examples are also shown by using real data.
Keywords :
compressed sensing; image reconstruction; radar imaging; synthetic aperture radar; CS capability; ISAR image reconstruction; Nyquist theorem; compressive sensing theory; synthetic aperture radar; Compressed sensing; Frequency-domain analysis; Image reconstruction; Indexes; Integrated circuits; Radar imaging; Sensors;
Conference_Titel :
Radar Symposium (IRS), 2015 16th International
Conference_Location :
Dresden
DOI :
10.1109/IRS.2015.7226312
