Fast and accurate reproduction of the radar signature of a target is important for many radar applications, such as target identification and hardware-in-the-loop simulations. Real-world targets are electrically large, and the Nyquist criteria require fine sampling in frequency and angle to fully characterize the radar signature. Because of the fine sampling requirement, acquiring the radar signature is time and memory intensive. Even though fine sampling is required in the frequency and angle domains, most targets are sparse in a point scatter domain. This paper shows that the Nyquist criteria can be overcome through compressed sensing theory by leveraging the point scatter representation of a target. This greatly reduces the amount of data needed to characterize the radar signature for these defense applications.
Compressed Sensing for Radar Signature Analysis
IEEE Transactions on Aerospace and Electronic Systems ; 49 , 4 ; 2631-2639
01.10.2013
1666477 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Optimized sensing matrix design of filter structure based compressed sensing radar
Online Contents | 2013
|Information Theory Based Radar Signature Analysis
IEEE | 2007
|Compressed Sensing Applied to Radar — Call for Papers for Transactions
Online Contents | 2012
Research on deception jammer against monopulse radar based on compressed sensing
British Library Online Contents | 2017
|