Abstract
Abstract : In conventional radar signal and image processing, the background clutter and noise are assumed to follow the Gaussian model. Under this assumption, it has been shown that the conventional matched filter is optimal in target detection. However, recent research has found that many nonhomogeneous types of clutter and noise, such as clutter, do not fit the Gaussian model well because of impulsive outliers or the so called sea spike. These types of clutter and noise lend themselves to a heavy tail in amplitude distribution; consequently, the conventional matched filter does not perform well. Most recent research has shown that the alpha-stable model is a better model. The alpha-stable model is a natural extension of the Gaussian model, and most radar clutter is modeled well by the alpha-stable statistics. A robust family of alpha-stable matched filters is a natural extension of the conventional matched filter. An optimal alpha-stable matched filter extracted from that family is being developed in a simple closed form. This optimal alpha-stable matched filter significantly improves target detection in both real clutter data and simulated data. Moreover, the alpha-stable matched filter is computationally efficient. It can be applied in wide varieties of radar signal and image processing.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
