Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/103631
Title: Improved compressed sensing radar by fusion with matched filtering
Authors: Dauwels, Justin
Srinivasan, K.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2014
Source: Dauwels, J. & Srinivasan, K. (2014). Improved compressed sensing radar by fusion with matched filtering. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 6795 - 6799.
Series/Report no.: 
Abstract: Compressed Sensing (CS) provides a rich mathematical framework to efficiently acquire a sparse signal from few non-adaptive measurements. In radar imaging, most scenes are sparse and CS can be successfully applied for efficiently acquiring the target scene. Although the use of CS in radar is advantageous in many aspects, a higher noise in the received signal makes the output of CS unreliable. We propose a framework based on CS and matched filtering to improve the performance of CS particularly in high noise scenarios. We realize this framework by CS on chirp signal and discuss some limitations associated with it. Numerical experiments confirm a substantial performance improvement using the proposed framework compared to conventional CS reconstruction.
URI: https://hdl.handle.net/10356/103631
http://hdl.handle.net/10220/23921
DOI: http://dx.doi.org/10.1109/ICASSP.2014.6854916
Rights: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/ICASSP.2014.6854916].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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