Co-development of Mathematical Models and Monte-Carlo Algorithms for Improved Detection of Targets in the Commercial Maritime Domain
The industrial challenge is:
1) to develop technology which could improve on the ability to detect objects of interest given a fixed sensor deployment;
2) to quantify the improvement in detection performance that results from the use of such models in both single-sensor and multi-sensor scenarios.
The closely-coupled scientific challenge is then:
1) to devise non-linear SDEs which describe the trajectories of objects of interest (eg ships) and models for sea clutter (as manifest in radar and in other sensor’s data);
2) to develop non-linear non-Gaussian dynamic models as high-accuracy solutions to such SDEs and clutter models;
3) to integrate the resulting dynamic models into state-of-the-art non-linear non-Gaussian multi-target tracking systems;
4) to quantify the improvement in detection performance that results from the use of such models in both single-sensor and multi-sensor scenarios.
The PhD will focus on meeting both sets of challenges.
This studentship is co-funded by EPSRC and Denbridge Marine Ltd (via a CASE award provided through the Industrial Mathematics Knowledge Transfer Network). Since the project is part EPSRC funded, it is only open to UK/EU citizens. The start date is to be agreed but a start of October 2014 would be preferred. This studentship is co-funded by EPSRC and Denbridge Marine Ltd (via a CASE award kindly provided by the Mathematics Knowledge Transfer Network). Since the project is part EPSRC funded, it is only open to UK/EU citizens. The start date is to be agreed but a start of October 2014 would be preferred. Since the project is funded by a CASE award, the stipend includes a generous top-up of approximately £18363 per year.
For further information and application details see: http://tinyurl.com/pnoated
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