1-g-h and g-h-k filters
2-Kalman filter
3-Practical issues for radar tracking
4-Least-squares and minimum-variance estimates for linear time-invariant systems
5-Fixed-memory polynomial filter
6-Expanding-memory(Growing-memory) plynomial filters
7-Fading-memory(discounted least-squares) filter
8-General form for linear time-invariant system
9-General recursive minimum-variance growing-memory filter(bayes and kalman without target process noise)
10-Voltage least-squares algorithms revisited
11-Givens orthonormal transformation
12-Householder orthonormal transformation
13-Gram-schmidt orthonormal transformation
14-More on voltage-processing techniques
15-Linear time-variant systenm
16-Nonlinear observation scheme and dynamics model
17-Bayes algorithm with iterative differential correction for nonlinear systems
18-Kalman filter revisited
Appendix:Comparison of swerling`s and kalman`s formulations of swerling-kalman filters