Area surveillance and target tracking
Paul Davies, Chris Firth (Thales UK), Abhir Bhalerao (Computer Science)
Identifying objects of interest in a given area and tracking their movement is an important
surveillance problem. Two main strategies are available:
1. Deploy one (expensive) airborne detection device with large and variable range of
detection
2. Deploy many (cheap) devices with small and possibly fixed range of detection
The project:
Use computer simulations to determine the optimal strategy for successful target detection
and tracking for a given a terrain with moving targets, which are of different
importance/mobility and have to be revisited by the tracking device in time intervals of
different duration.
Under reasonable restrictions on the detection range provided by Thales (mostly narrow and
far vs. wide and near detection), identify an optimal strategy to survey the area with a single,
complex detection device. A possible method is to use agent-based simulations with fixed
strategy and evolutionary type algorithms for optimization.
For the same scenario, find the optimal strategy using a large number of small devices with
fixed narrow detection range. Compare the “costs” (using a cost function dependent on
financial acquisition cost, ongoing operation cost, and quality / timeliness of surveillance
information) of both alternatives. Genetic algorithms are likely to be of use here.
Interesting supplementary problems include studying the complexity of maintaining
communication and coordination between the small devices sharing restricted bandwidth.
Thales can provide realistic scenarios and model parameters for use in the project.