Tracking and Kalman filtering made easy /
| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
New York :
Wiley,
©1998.
|
| Series: | Wiley-Interscience publication.
|
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- G-h and g-h-k filters
- Kalman filter
- Practical issues for radar tracking
- Least-squares and minimum-variance estimates for linear time-invariant systems
- Fixed-memory polynomial filter
- Expanding-memory (growing-memory) polynomial filters
- Fading-memory (discounted least-squares) filter
- General form for linear time-invariant system
- General recursive minimum-variance growing-memory filter (Bayes and Kalman filters without target process noise)
- Voltage least-squares algorithms revisited
- Givens orthonormal transformation
- Householder orthonormal transformation
- Gram-Schmidt orthonormal transformation
- More on voltage-processing techniques
- Linear time-variant system
- Nonlinear observation scheme and dynamic model (extended Kalman filter)
- Bayes algorithm with iterative differential correction for nonlinear systems
- Kalman filter revisited.