# benedict_bornder_constants¶

Copyright 2015 Roger R Labbe Jr.

FilterPy library. http://github.com/rlabbe/filterpy

Supporting book at: https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python

filterpy.gh.benedict_bornder_constants(g, critical=False)[source]

Computes the g,h constants for a Benedict-Bordner filter, which minimizes transient errors for a g-h filter.

Returns the values g,h for a specified g. Strictly speaking, only h is computed, g is returned unchanged.

The default formula for the Benedict-Bordner allows ringing. We can “nearly” critically damp it; ringing will be reduced, but not entirely eliminated at the cost of reduced performance.

Parameters: g : float scaling factor g for the filter critical : boolean, default False Attempts to critically damp the filter. g : float scaling factor g (same as the g that was passed in) h : float scaling factor h that minimizes the transient errors

References

Brookner, “Tracking and Kalman Filters Made Easy”. John Wiley and Sons, 1998.

Examples

from filterpy.gh import GHFilter, benedict_bornder_constants
g, h = benedict_bornder_constants(.855)
f = GHFilter(0, 0, 1, g, h)