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Multidimensional Radar Imaging and ATR

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Sensors & Electronics Technology

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AI, ATR, Deep Learning, Machine Learning, NCTR, Radar, Radar Imaging


A NATO SET specialist meeting, namely SET-228 on Radar Imaging for Target Identification, was organized in fall 2015 as a companion meeting of the SET PBM. SET-228 aimed at bringing together both radar imaging and ATR scientific and military communities. SET-228 was very successful and attracted more than 100 participants, with roughly 30 paper submitted and presented in the two-day event. Results of SET-228 have helped a number of SET RTGs to continue and improve their work in the following years. Three radar imaging and ATR related RTGs, namely SET-215 on Model Based Automatic Target Recognition, SET-245 on Radar based Non-cooperative target recognition (NCTR) in the low airspace and complex surface environments and SET-250 on Multidimensional Radar Imaging, have decided to repeat that experience with a slightly new flavor, although maintaining the idea to bring together the same two communities of researchers and military experts. New studies conducted within the NATO and outside have indicated that the use of multi-channel, multi-static, multi-frequency and multi-polarization, therefore multi-dimensional radar data have the ability to improve classification performances. This RSM will showcase the latest research results in this field and will open the ground for discussions about the impact of such results on NATO operations and inspire the way ahead. Moreover, given the wide diversity provided by multi-dimensional radar systems, recent advancements along the direction of artificial intelligence and cognitive systems prove effective if not necessary to solve very complex problems.


This specialist meeting aims at bringing together experts of radar imaging and Non-Cooperative Target Recognition (NCTR), with the aim of enabling discussions and closer collaboration. Moreover, the interaction between scientist, industry and military experts will ensure that new ideas are directed towards real and important needs. Improvement in current work and inspiration for future activities is expected to be achieved along with more collaboration among active RTGs in this and closely related fields. It is also expected that latest research in the field of AI, deep learning and cognitive radar will be displayed during this RSM which will trigger and inspire future radar imaging and ATR systems.


The following list of topics is to be considered non-exhaustive, but only as a general indication of the flavour of this RSM: • SAR/ISAR image formation including bistatic, multistatic, multi-frequency and fully polarimetric • SAR/ISAR image feature extraction • SAR/ISAR image quality measurement • NCTR / ATR schemes and algorithms • NCTR / ATR theory and performance estimation • Simulations & Model based recognition • Micro-Doppler based ATR • Automatic HRR / SAR / ISAR mode selection • Employment context : target, system • Effective Databases: Common/Shared, Reduced, etc • Artificial Intelligence for imaging and ATR • Passive radar imaging for ATR • Convolutional Neural Networks and Deep Learning for radar imaging and ATR

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