Reference number : GC-2017-Q2-00538, amendment number : , agreement type : G, recipient legal name : Kirubarajan, Thia (McMaster University), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Department of National Defence / NSERC Research Partnership - Project, program name french : Partenariat de recherche du ministère de la Défense nationale et du CRSNG - projet, program purpose english : 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_, program purpose french : 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_
_x000D_
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_, agreement title english : Software-Controlled Active Electronically Scanned Array Radar for Airbone Ground Surveillance, agreement title french : Software-Controlled Active Electronically Scanned Array Radar for Airbone Ground Surveillance, agreement number : DNDPJ, agreement value : 328000.0, agreement start date : 2017-08-23, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2021-2022)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2021-2022)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada