Function filter::gh::critical_damping_parameters_order_two

pub fn critical_damping_parameters_order_two<T: FloatCore>(theta: T) -> (T, T)

Computes values for g and h for a critically damped filter. The idea here is to create a filter that reduces the influence of old data as new data comes in. This allows the filter to track a moving target better. This goes by different names. It may be called the discounted least-squares g-h filter, a fading-memory polynomal filter of order 1, or a critically damped g-h filter.

References

• Brookner, "Tracking and Kalman Filters Made Easy". John Wiley and Sons, 1998.
• Polge and Bhagavan. "A Study of the g-h-k Tracking Filter". Report No. RE-CR-76-1. University of Alabama in Huntsville. July, 1975