An introduction to radar Automatic Target Recognition (ATR) technology in ground-based radar systems

This paper presents a brief examination of Automatic Target Recognition (ATR) technology within ground-based radar systems. It offers a lucid comprehension of the ATR concept, delves into its historical milestones, and categorizes ATR methods according to different scattering regions. By incorporating ATR solutions into radar systems, this study demonstrates the expansion of radar detection ranges and the enhancement of tracking capabilities, leading to superior situational awareness. Drawing insights from the Russo-Ukrainian War, the paper highlights three pressing radar applications that urgently necessitate ATR technology: detecting stealth aircraft, countering small drones, and implementing anti-jamming measures. Anticipating the next wave of radar ATR research, the study predicts a surge in cognitive radar and machine learning (ML)-driven algorithms. These emerging methodologies aspire to confront challenges associated with system adaptation, real-time recognition, and environmental adaptability. Ultimately, ATR stands poised to revolutionize conventional radar systems, ushering in an era of 4D sensing capabilities

Développement d'algorithmes pour la fonction NCTR - Application des calculs parallèles sur les processeurs GPU.

Le thème principal de cette thèse est l'étude d'algorithmes de reconnaissance de cibles non coopératives (NCTR). Il s'agit de faire de la reconnaissance au sein de la classe "chasseur" en utilisant le profil distance. Nous proposons l'étude de quatre algorithmes : un basé sur l'algorithme des KPPV, un sur les méthodes probabilistes et deux sur la logique floue. Une contrainte majeure des algorithmes NCTR est le contrôle du taux d'erreur tout en maximisant le taux de succès. Nous avons pu montrer que les deux premiers algorithmes ne permettait pas de respecter cette contrainte. Nous avons en revanche proposé deux algorithmes basés sur la logique floue qui permettent de respecter cette contrainte. Ceci se fait au détriment du taux de succès (notamment sur les données réelles) pour le premier des deux algorithmes. Cependant la deuxième version de l'algorithme a permis d'augmenter considérablement le taux de succès tout en gardant le contrôle du taux d'erreur. Le principe de cet algorithme est de caractériser, case distance par case distance, l'appartenance à une classe en introduisant notamment des données acquises en chambre sourde. Nous avons également proposé une procédure permettant d'adapter les données acquises en chambre sourde pour une classe donnée à d'autres classes de cibles. La deuxième contrainte forte des algorithmes NCTR est la contrainte du temps réel. Une étude poussée d'une parallélisation de l'algorithme basé sur les KPPV a été réalisée en début de thèse. Cette étude a permis de faire ressortir les points à prendre en compte lors d'une parallélisation sur GPU d'algorithmes NCTR. Les conclusions tirées de cette étude permettront par la suite de paralléliser de manière efficace sur GPU les futurs algorithmes NCTR et notamment ceux proposés dans le cadre de cette thèse.The main subject of this thesis is the study of algorithms for non-cooperative targets recognition (NCTR). The purpose is to make recognition within "fighter" class using range profile. The study of four algorithms is proposed : one based on the KNN algorithm, one on probabilistic methods and two on fuzzy logic. A major constraint of NCTR algorithms is to control the error rate while maximizing the success rate. We have shown that the two first algorithms are not sufficient to fulfill this requirement. On the other hand, two algorithms based on fuzzy logic have been proposed and meet this requirement. Compliance with this condition is made at the expense of success rate (in particular on real data) for the first of the two algorithms based on fuzzy-logic. However, a second version of the algorithm has greatly increased the success rate while keeping control of the error rate. The principle of this algorithm is to make classification range bin by range bin, with the introduction of data acquired in an anechoic chamber. We also proposed a procedure for adapting the data acquired in an anechoic chamber for a class to another class of targets. The second major constraint algorithms NCTR is the real time constraint. An advanced study of a parallelization on GPU of the algorithm based on KNN was conducted at the beginning of the thesis. This study has helped to identify key points of a parallelization on GPU of NCTR algorithms. Findings from this study will be used to parallelize efficiently on GPU future NCTR algorithms, including those proposed in the thesis.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

Collected Papers (on Neutrosophic Theory and Applications), Volume VII

This seventh volume of Collected Papers includes 70 papers comprising 974 pages on (theoretic and applied) neutrosophics, written between 2013-2021 by the author alone or in collaboration with the following 122 co-authors from 22 countries: Mohamed Abdel-Basset, Abdel-Nasser Hussian, C. Alexander, Mumtaz Ali, Yaman Akbulut, Amir Abdullah, Amira S. Ashour, Assia Bakali, Kousik Bhattacharya, Kainat Bibi, R. N. Boyd, Ümit Budak, Lulu Cai, Cenap Özel, Chang Su Kim, Victor Christianto, Chunlai Du, Chunxin Bo, Rituparna Chutia, Cu Nguyen Giap, Dao The Son, Vinayak Devvrat, Arindam Dey, Partha Pratim Dey, Fahad Alsharari, Feng Yongfei, S. Ganesan, Shivam Ghildiyal, Bibhas C. Giri, Masooma Raza Hashmi, Ahmed Refaat Hawas, Hoang Viet Long, Le Hoang Son, Hongbo Wang, Hongnian Yu, Mihaiela Iliescu, Saeid Jafari, Temitope Gbolahan Jaiyeola, Naeem Jan, R. Jeevitha, Jun Ye, Anup Khan, Madad Khan, Salma Khan, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, Kifayat Ullah, Kishore Kumar P.K., Sujit Kumar De, Prasun Kumar Nayak, Malayalan Lathamaheswari, Luong Thi Hong Lan, Anam Luqman, Luu Quoc Dat, Tahir Mahmood, Hafsa M. Malik, Nivetha Martin, Mai Mohamed, Parimala Mani, Mingcong Deng, Mohammed A. Al Shumrani, Mohammad Hamidi, Mohamed Talea, Kalyan Mondal, Muhammad Akram, Muhammad Gulistan, Farshid Mofidnakhaei, Muhammad Shoaib, Muhammad Riaz, Karthika Muthusamy, Nabeela Ishfaq, Deivanayagampillai Nagarajan, Sumera Naz, Nguyen Dinh Hoa, Nguyen Tho Thong, Nguyen Xuan Thao, Noor ul Amin, Dragan Pamučar, Gabrijela Popović, S. Krishna Prabha, Surapati Pramanik, Priya R, Qiaoyan Li, Yaser Saber, Said Broumi, Saima Anis, Saleem Abdullah, Ganeshsree Selvachandran, Abdulkadir Sengür, Seyed Ahmad Edalatpanah, Shahbaz Ali, Shahzaib Ashraf, Shouzhen Zeng, Shio Gai Quek, Shuangwu Zhu, Shumaiza, Sidra Sayed, Sohail Iqbal, Songtao Shao, Sundas Shahzadi, Dragiša Stanujkić, Željko Stević, Udhayakumar Ramalingam, Zunaira Rashid, Hossein Rashmanlou, Rajkumar Verma, Luige Vlădăreanu, Victor Vlădăreanu, Desmond Jun Yi Tey, Selçuk Topal, Naveed Yaqoob, Yanhui Guo, Yee Fei Gan, Yingcang Ma, Young Bae Jun, Yuping Lai, Hafiz Abdul Wahab, Wei Yang, Xiaohong Zhang, Edmundas Kazimieras Zavadskas, Lemnaouar Zedam