Information driven optimal sensor control for efficient target localization and tracking

This paper describes the problem of multiple target tracking and localization using dynamic sensors such as Unmanned Ariel Vehicles. Often the location or path of the target is uncertain and has to be accounted along with UAV fuel costs while optimally planning the dynamic sensor trajectory. The coupled problem of optimal target state estimation and sensor path planning is computationally expensive and at times intractable. In this paper, an iterative sub-optimal control approach is proposed with the intent of a real-time application.

[1]  Puneet Singla,et al.  Optimal information collection for nonlinear systems- An application to multiple target tracking and localization , 2013, 2013 American Control Conference.

[2]  A. Jazwinski Stochastic Processes and Filtering Theory , 1970 .

[3]  Munther A. Dahleh,et al.  Maneuver-based motion planning for nonlinear systems with symmetries , 2005, IEEE Transactions on Robotics.

[4]  Qian Huang,et al.  A new distance measure for probability distribution function of mixture type , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[5]  Peter D. Scott,et al.  Adaptive Gaussian Sum Filter for Nonlinear Bayesian Estimation , 2011, IEEE Transactions on Automatic Control.

[6]  Thomas M. Cover,et al.  Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing) , 2006 .

[7]  Sameera S. Ponda,et al.  Trajectory Optimization for Target Localization Using Small Unmanned Aerial Vehicles , 2009 .

[8]  K. Kastella,et al.  A Comparison of Task Driven and Information Driven Sensor Management for Target Tracking , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[9]  P.T. Kabamba,et al.  Path planning for cooperative time-optimal information collection , 2008, 2008 American Control Conference.

[10]  Hugh F. Durrant-Whyte,et al.  A new method for the nonlinear transformation of means and covariances in filters and estimators , 2000, IEEE Trans. Autom. Control..

[11]  Francesco Bullo,et al.  Optimal sensor placement and motion coordination for target tracking , 2006, Autom..

[12]  Petros G. Voulgaris,et al.  On optimal ℓ∞ to ℓ∞ filtering , 1995, Autom..

[13]  Puneet Singla,et al.  The Conjugate Unscented Transform — An approach to evaluate multi-dimensional expectation integrals , 2012, 2012 American Control Conference (ACC).