Researchers: David Anisi and Xiaoming Hu in cooperation with John Robinson (FOI) and Petter Ögren (FOI).
Sponsor: Swedish Defence Research Agency (FOI).
A key part of missile guidance is the path planning problem, where a tentatively optimal path is laid out for the missile autopilot to follow. Optimality is here dictated by a mix of conditions and penalties relating to energy efficiency, threat avoidance, stealth behavior, kinematic and dynamic constraints of the missile and various end-point constraints imposed by the seeker, warhead and terrain.
Traditionally, trajectory optimization problems are solved with classical methods from optimal control, which means that the planning problem in general has to be solved off-line, due to the computational complexity. In modern day conflict scenarios however, this is no longer a feasible solution. In order to be effective against highly mobile, so-called time critical targets such as SCUD launch vehicles, the weapon systems must be able to do fast and robust path planning on-line, using an onboard computer. Issues such as cooperation between a number of different systems also increases the complexity of the planning problems at hand.
Since March 2005, the Division of Optimization and Systems Theory at KTH, cooperatively conducts research within this field together with the Department of Autonomous Systems at the Swedish Defence Research Agency (FOI). The central topic of the project is the problem of obtaining methods and computationally efficient algorithms for path planning/re-planning, that are possible to implement in real-time missile guidance systems.