Date

2015

Author

Uzun, Çağlar

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In this work, the concept of sensor management is introduced and stochastic dynamic programming based resource allocation approach is proposed to track multiple targets. The core of this approach is to use Lagrange relaxation for decreasing the state space dimension. By this approximation, the overall problem is separated into components instead of using joint Markov model to optimize large scale stochastic control problem. The aim of this study is to adaptively allocate radar resources in an optimal way in order to maintain track qualities for multi-target case. The radar is electronically steered antenna radar. Resource allocation is done only for tracking excluding the search beams. Adaptive target tracking is performed by Kalman filter. Problem is modeled as a set of controlled Markov chains each dedicated to one track. Time scale is divided into two levels that are called as micro management and macro management. During the thesis, we deal with macro management part that aims to construct a policy which is optimal for a given objective function under the resource constraints. Stochastic dynamic programming with constraints in the sense of [32] is the method used. In this thesis, five different scenarios are constructed and corresponding algorithms are confirmed by simulation results. The performances of the algorithms are also compared. Their performances are analyzed on the average number of update decision and average number of target drops in time horizon.

Subject Keywords

Radar, Sensor networks., Markov processes., Dynamic programming., Mathematical optimization.

URI

http://etd.lib.metu.edu.tr/upload/12618383/index.pdf
https://hdl.handle.net/11511/24371

Collections

Graduate School of Natural and Applied Sciences, Thesis