NTS (version 1.1.3)

clutterKF: Kalman Filter for Tracking in Clutter

Description

This function implements Kalman filter to track a moving target under clutter environment with known indicators.

Usage

clutterKF(nobs, ssw, ssv, yy, ii)

Value

The function returns a list with the following components:

xhat

the fitted location.

shat

the fitted speed.

Arguments

nobs

the number of observations.

ssw

the standard deviation in the state equation.

ssv

the standard deviation for the observation noise.

yy

the data.

ii

the indicators.

References

Tsay, R. and Chen, R. (2018). Nonlinear Time Series Analysis. John Wiley & Sons, New Jersey.

Examples

nobs <- 100; pd <- 0.95; ssw <- 0.1; ssv <- 0.5;
xx0 <- 0; ss0 <- 0.1; nyy <- 50;
yrange <- c(-80,80); xdim <- 2; ydim <- nyy;
simu <- simuTargetClutter(nobs,pd,ssw,ssv,xx0,ss0,nyy,yrange)
outKF <- clutterKF(nobs,ssw,ssv,simu$yy,simu$ii)