On the development of practical nonlinear filters

Information Sciences

Volumn 7, Issue C, 1974, Pages 253-270

  Sorenson, H W ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION THEORY;

EID: 0016104320     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/0020-0255(74)90017-6     Document Type: Article

References (47)

1. A Bayesian approach to problems in stochastic estimation and control
2. A new approach to linear filtering and prediction problems
3. Comparison of Kalman, Bayesian and maximum likelihood estimation techniques
4. Kalman filtering techniques
5. Divergence of the Kalman filter
6. A comparison of two nonlinear filters for ballistic trajectory estimation
7. Pseudostate measurements applied to recursive nonlinear filtering
8. Recursive fading memory filtering
9. Recursive filtering for systems with small but nonnegligible nonlinearities
10. Suboptimal state estimators for continuous-time nonlinear systems from discrete noisy measurements
11. Nonlinear filtering by approximation of the a posteriori density
12. Optimal nonlinear estimation based on orthogonal expansions
13. State estimation by orthogonal expansion of probability distributions
14. Optimal adaptive estimation of sampled stochastic processes
15. Optimal estimation in the presence of unknown parameters
16. Bayes' theorem and digital realization for nonlinear filters
17. Realization of optimum discrete-time nonlinear estimators
18. Approximation of density function by a sum of Gaussians for nonlinear Bayesian estimation
19. Practical nonlinear filtering of discrete observations by generalized least-squares approximation of the conditional probability distribution
20. Practical nonlinear filtering based on generalized least-squares approximation of the conditional probability distribution
21. Spline filters
22. Recursive Bayesian estimation using Gaussian sums
23. Nonlinear Bayesian estimation using Gaussian sum approximations
24. Control and estimation of linear systems with non-Gaussian a priori distributions
25. Optimal adaptive estimation Structure and parameter adaptation
26. Recursive optimal estimation for a class of non-gaussian processes
27. Optimal nonlinear estimation
28. Finite-dimensional sensor orbits and optimal nonlinear filtering
29. Monte-Carlo study of the optimal nonlinear state-vector estimator for linear model and non-Gaussian initial state
30. Computational requirements for a discrete Kalman filter
31. Parallel computation of the conditional mean state estimate for nonlinear systems
32. Second thoughts on parallel processing
33. Digital realization of nonlinear filters
34. Quadrature formulae realization of nonlinear estimators
35. Optimum quantization and parallel algorithms for nonlinear state estimation
36. Hybrid computer synthesis of optimal discrete nonlinear filters
37. An engineer's guide to building nonlinear filters
38. Back to parallel computation: Proposal for a completely new on-line simulation system using standard mini-computers for low-cost multiprocessing
39. A comparison of three nonlinear filters
40. Approximations to nonlinear filters
41. A computational comparison of several nonlinear filters
42. Realization of nonlinear filters
43. An application of Bayes law estimation to non-linear phase demodulation