This function implements one step of the sequential importance sampling method for a target with passive sonar.
Sstep.Sonar(mm, xx, logww, yy, par, xdim = 1, ydim = 1)
The function returns a list with the following components:
the new sample.
the log weights.
the Monte Carlo sample size m
.
the sample in the last iteration.
the log weight in the last iteration.
the observations with T
columns and ydim
rows.
a list of parameter values. H
is the state coefficient matrix, W*t(W)
is the state innovation covariance matrix,
V*t(V)
is the covariance matrix of the observation noise, s2
is the second sonar location.
the dimension of the state variable x_t
.
the dimension of the observation y_t
.
Tsay, R. and Chen, R. (2018). Nonlinear Time Series Analysis. John Wiley & Sons, New Jersey.