Title :
A novel and efficient approach for automatic classification of radar emitter signals
Author_Institution :
Electr. Eng. Dept., Al-Baha Univ., Al-Baha, Saudi Arabia
Abstract :
Radar emitter signal identification is a special issue of data clustering for classifying unknown radar emitters. In this paper, an efficient approach for automatic classification of radar emitter signals in multisensor systems is proposed. The proposed approach exploits measured features extracted from multiple sensors as well as the sensor accuracies for classification of unknown multiple radar targets. The proposed approach can easily be applied to any number of sensors with different accuracies, any number of emitters, and any number of measured features without exponential growing of the required computations. The performance of the proposed classification approach is evaluated in terms of percentage of correct classification and compared to other classification approaches. The results show the feasibility and the effectiveness of the proposed classification approach.
Keywords :
pattern clustering; radar signal processing; sensor fusion; signal classification; data clustering; multisensor systems; radar emitter signal automatic classification; radar emitter signal identification; unknown multiple radar targets; Accuracy; Radar measurements; Sensor phenomena and characterization; Support vector machine classification; Vectors;
Conference_Titel :
Aerospace Conference, 2013 IEEE
Conference_Location :
Big Sky, MT
Print_ISBN :
978-1-4673-1812-9
DOI :
10.1109/AERO.2013.6496952