Compressive sensing based target detection in delay-doppler radars
Date
2013Source Title
2013 21st Signal Processing and Communications Applications Conference (SIU)
Publisher
IEEE
Language
Turkish
Type
Conference PaperItem Usage Stats
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Abstract
Compressive Sensing theory shows that, a sparse signal can be reconstructed from its sub-Nyquist rate random samples. With this property, CS approach has many applications. Radar systems, which deal with sparse signal due to its nature, is one of the important application of CS theory. Even if CS approach is suitable for radar systems, classical detections schemes under Neyman-Pearson formulations may result high probability of false alarm, when CS approach is used, especially if the target has off-grid parameters. In this study, a new detection scheme which enables CS techniques to be used in radar systems is investigated. © 2013 IEEE.
Keywords
Compressive sensingRadar signal processing
Compressive sensing
Detection scheme
High probability
Neyman-pearson
Off-grids
Radar signal processing
Random sample
Sparse signals
Doppler radar
Radar systems
Signal detection
Signal reconstruction
Permalink
http://hdl.handle.net/11693/28002Published Version (Please cite this version)
http://dx.doi.org/10.1109/SIU.2013.6531496Collections
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