covmat_nswn: Calculate Theoretical Covariance Matrix of Non-Stationary...

In avar: Allan Variance

Calculate Theoretical Covariance Matrix of Non-Stationary White Noise Process

Description

This function allows us to calculate the theoretical covariance matrix of a non-stationary white noise process.

Usage

covmat_nswn(sigma2, n_total)

Arguments

sigma2	A double value for the variance parameter \sigma ^2.
n_total	An integer indicating the length of the whole non-stationary white noise process.

Value

The theoretical covariance matrix of the non-stationary white noise process.

Note

This function helps calculate the theoretical covariance matrix of a non-stationary process, non-stationary white noise. It is helpful to calculate the theoretical allan variance of non-stationary processes, which can be used to compare with the theoretical allan variance of stationary processes as shown in "A Study of the Allan Variance for Constant-Mean Non-Stationary Processes" by Xu et al., 2017, IEEE Signal Processing Letters, 24(8): 1257–1260.

Author(s)

Yuming Zhang

Examples

covmat1 = covmat_nswn(sigma2 = 1, n_total = 1000)
covmat2 = covmat_nswn(sigma2 = 2, n_total = 800)

avar documentation built on Aug. 29, 2023, 5:09 p.m.