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rlabbe / Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
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Curiosity about provided solution for Chapter 2, "Exercise: Write Generic Algorithm" #379

Open dthakur opened 3 years ago

dthakur commented 3 years ago

The provided solution has:

dx = dx + h * (residual) / dt

In my own solution, I wrote:

dx = (1 - h) * dx + h * (residual) / dt

Is the (1 - h) applied to the prediction unnecessary for updating dx?

endolith commented 2 months ago

Chapter 1, not 2. https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/9e3d2f6ed023d937587cf2ef2ecfbf7afc3d8054/01-g-h-filter.ipynb#L974