Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2021-2022).

Tracking the states of mobile objects (e.g., ground vehicles, ships, aircraft, people) has many applications in communications, law enforcement, defense and biomedical engineering. A wide variety of sensors (e.g., radar, video, sonar, infrared), which may be stationary or mounted on mobile platforms (e.g., aircraft, satellites, ships, cars), are available to generate measurements that are in turn used to estimate the unknown states of mobile objects. With the recent advances in sensor, computer hardware and software technologies, it is possible to adaptively modify the processing, operational modality and configuration of sensors in real time in response to the ever-changing environment. For example, with an active electronically scanned array (AESA) radar, one can adaptively change waveforms, sampling time and sensing mode in real time. The objective of adaptation is to provide rapid response capability or agility.x000D
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With adaptation, it is possible to obtain the most accurate object detection, state estimation and classification results (i.e., get the best out of the available sensors) by mitigating as much as possible the effects of the environment, uncertainties in modeling and inaccuracies in sensing. This is precisely the motivation for the proposed work. In this project, we propose to develop a set of adaptive algorithms with particular application to multisenor-multitarget tracking in airborne surveillance systems with an AESA radar. With some changes, the same concepts can be used in intelligent highway systems (IHS) and maritime vessel traffic management service (VTMS) systems as well.x000D