Brown92 Brown, R. G. and P. Y. C. Hwang. 1992. Introduction to Random Signals and Applied Kalman Filtering, Second Edition, John Wiley & Sons, Inc.
Gelb74 Gelb, A. 1974. Applied Optimal Estimation, MIT Press, Cambridge, MA.
Jacobs93 Jacobs, O. L. R. 1993. Introduction to Control Theory, 2nd Edition. Oxford University Press.
Julier Julier, Simon and Jeffrey Uhlman. "A General Method of Approximating Nonlinear Transformations of Probability Distributions," Robotics Research Group, Department of Engineering Science, University of Oxford [cited 14 November 1995]. Available from http://www.robots.ox.ac.uk/~siju/work/publications/Unscented.zip.
Also see: "A New Approach for Filtering Nonlinear Systems" by S. J. Julier, J. K. Uhlmann, and H. F. Durrant-Whyte, Proceedings of the 1995 American Control Conference, Seattle, Washington, Pages:1628-1632. Available from http://www.robots.ox.ac.uk/~siju/work/publications/ACC95_pr.zip.
Also see Simon Julier's home page at http://www.robots.ox.ac.uk/~siju/.
Kalman60 Kalman, R. E. 1960. "A New Approach to Linear Filtering and Prediction Problems," Transaction of the ASME--Journal of Basic Engineering, pp. 35-45 (March 1960).
Lewis86 Lewis, Richard. 1986. Optimal Estimation with an Introduction to Stochastic Control Theory, John Wiley & Sons, Inc.
Maybeck79 Maybeck, Peter S. 1979. Stochastic Models, Estimation, and Control, Volume 1, Academic Press, Inc.
Sorenson70 Sorenson, H. W. 1970. "Least-Squares estimation: from Gauss to Kalman," IEEE Spectrum, vol. 7, pp. 63-68, July 1970.