This paper compares the performance of recursive state estimation techniques for tracking the physical location of a radioactive source based on radiation measurements obtained from a series of detectors at fixed locations. Specifically, the first order, iterated, and a second order Kalman filter performance is compared to nonlinear least squares estimation. The results of this study indicate that least squares estimation significantly outperforms the extended Kalman filter implementations in this application due to the nature of the model nonlinearities.
K.R. Muske and J.W. Howse, Comparison of recursive estimation techniques for position tracking radioactive sources. Los Alamos National Laboratory Techinical Report LA-UR-00-4497. Proceedings of the 2001 American Control Conference, Arlington, VA, June 2001, pp. 1656-1660, 2001. [ Abstract | PDF (462 KB) ]
