Appendix: Comparison of Swerling's and Kalman's Formulations of Swerling–Kalman Filters
Peter Swerling · 1998
In the late 1950s and 1960s Swerling and Kalman independently developed what amounts to the same technique of recursive statistically optimum estimation. Swerling was motivated by applications to estimating the orbits of earth satellites or other space vehicles. He presented his results as recursive implementations of the Gauss method of least squares. Kalman was motivated by the aim of deriving new ways to solve linear filtering and prediction problems. His development was presented as a recursive way to implement the solution of Wiener filtering and prediction. It is a simple matter to show either equivalence of the actual results or the straightforward extension of either Swerling's or Kalman's results to the other's, as discussed in this appendix.