Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation¶
Gordon, N. J., Salmond, D. J., & Smith, A. F. M. (1993). Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation. IEE Proceedings F—Radar and Signal Processing, 107-113.
Cited by¶
1 citation across 1 artifact.
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Domain-specific¶
- Particle Filter
- Gordon, Salmond, and Smith’s bootstrap filter made this concrete by representing the state density with random samples and recursively updating and propagating them in nonlinear, non-Gaussian tracking.
This sourceIntroduces the bootstrap filter as a random-sample implementation of recursive Bayesian filtering and demonstrates nonlinear bearings-only tracking.
- Gordon, Salmond, and Smith’s bootstrap filter made this concrete by representing the state density with random samples and recursively updating and propagating them in nonlinear, non-Gaussian tracking.
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