Arwin Datumaya Wahyudi Sumari, Aldi Surya Pranata, Irsyad Arif Mashudi, Ika Noer Syamsiana, Catherine Olivia Sereati
Automatic Target Detection, Recognition, and Identification (ADTRI) is an important task, especially for the military. This paper enhances the military technique for recognizing and identifying air objects by utilizing a Support Vector Machine (SVM) combined with information fusion. For this purpose, SVM, as the recognizer, generated knowledge of 11 characteristics that consist of the Wing, Engine, Fuselage, and Tail (WEFT) of 155 military and civilian aircraft and helicopters. Then, the identification is carried out by the information fusion from the SVM result. Using the 80:20 scheme, the combination of SVM and information fusion can achieve an average accuracy of 99.60% during training and 98.39% during the testing for the combination of primary and secondary characteristics. Another important thing is that this combination can speed up the process of recognition and identification by up to 0.52 seconds. © 2022 IEEE.
Cognitive Artificial Intelligence Research Group (CAIRG), Department of Electrical Engineering, Politeknik Negeri Malang, Indonesia Adisutjipto Institute of Aerospace Technology, Yogyakarta, Indonesia; Politeknik Negeri Malang, Department of Information Technology, Malang, Indonesia; Cognitive Artificial Intelligence Research Group (CAIRG), Faculty of Engineering, Atma Jaya Catholic University, Jakarta, Indonesia