Title :
Detection and classification of radar signals in conic regions
Author :
De Nicola, Silvio
Author_Institution :
Studies & Obs. Office, AGCOM, Naples, Italy
Abstract :
In this paper, we address the adaptive detection and classification of signals in a homogenous interference environment. The detector assumes the signals belonging to conic regions, and relies on secondary data. To deal with this scenario, we adopt a two-stage detection/classification scheme, enjoying the constant false alarm rate property, to discriminate between target detection and coherent interferer rejection. Finally, we evaluate the system performance via Monte Carlo simulations. The results show that our system has interesting rejection capabilities and satisfactory detection levels, and it could be easily adapted to real scenarios.
Keywords :
Monte Carlo methods; interference suppression; object detection; radar signal processing; signal classification; signal detection; Monte Carlo simulations; adaptive detection; coherent interferer rejection; conic regions; constant false alarm rate property; homogenous interference environment; radar signals; secondary data; signal classification; signal detection; target detection; two-stage detection/classification; Detectors; Interference; Jamming; Receivers; Robustness; Signal to noise ratio; Vectors; Constant False Alarm Rate; Convex Optimization; Interference Rejection; Radar Signal Processing; Robust Adaptive Detection;
Conference_Titel :
Advances in Radar and Remote Sensing (TyWRRS), 2012 Tyrrhenian Workshop on
Conference_Location :
Naples
Print_ISBN :
978-1-4673-2443-4
DOI :
10.1109/TyWRRS.2012.6381110