algorithm_2: Estimation of White Noise and Random Walk Innovation...

In Yuming-Zhang/synimu: Scale-wise Variance Optimization

Estimation of White Noise and Random Walk Innovation Covariances R and Q

Description

This function provides an estimate based on the Allan variance for the white noise and the random walk innovation covariances R and Q. The implementation reflects Algorithm 2 in Richard J. Vaccaro and Ahmed S. Zaki, "Reduced-Drift Virtual Gyro from an Array of Low-Cost Gyros".

Usage

algorithm_2(X, remove_last_scale = FALSE)

Arguments

X	A matrix of dimension T by p, where T is the length of the time series and p is the number of processes.
remove_last_scale	wether the last scale of the Allan variance should be removed

Value

A list with the following structure:

• R: A vector of size p of the estimated white noise variances.

• Q: A matrix of size p by p of the estimated random walk innovation covariance.

Author(s)

Davide Antonio Cucci

Yuming-Zhang/synimu documentation built on Jan. 29, 2023, 11:59 a.m.