EKF_NMCDA_PREDICT EKF/NMCDA Update step
Syntax:
[S,EV_STRS] = ekf_nmcda_update(S,Y,t,H,R,h,V,CP,CD,
a_birth,l_birth,
a_death,l_death,param)
In:
S - Struct array 1xNP of particles
Y - Dx1 measurement vector
t - Time stamp of the measurement
H - Derivative of h() with respect to state as matrix,
inline function or name of function in
form H(x,param).
R - Measurement noise covariance.
h - Mean measurement prediction as vector,
inline function or name of function in
form h(x,param). (optional, for default see EKF_UPDATE)
V - Derivative of h() with respect to noise as matrix,
inline function or name of function in
form V(x,param). (optional, for default see EKF_UPDATE)
CP - Prior probability of a measurement being due
to clutter. (optional, default zero)
CD - Probability density of clutter measurements,
which could be for example 1/V, where V is
the volume of clutter measurement space. (optional, default 0.01)
pb - Prior probability of birth (optional, default 0.01)
alpha - Parameter alpha for the gamma
distribution model for time to death (optional, default 1)
beta - Parameter beta for the gamma
distribution model for time to death (optional, default 10)
param - Parameters of H, h and V. See, for instance, ekf_predict1 or ekf_update1
for more details.
Out:
S - Predicted struct array of particles
EV_STRS - Comment strings of happened events
Description:
Perform update step of Rao-Blackwellized Monte Carlo
Data Association Algorithm with Number of Targets estimation.
See also:
EKF_NMCDA_INIT, EKF_NMCDA_PREDICT, EKF_UPDATE