kf_mcda_predict

KF_MCDA_PREDICT  KF Monte Carlo Data Association Prediction

 Syntax:
   S = KF_MCDA_PREDICT(S,A,Q)

 In:
   S - 1xN cell array containing particle structures.
   A - State transition matrix which can be a same numeric matrix 
       for every target or a TxN cell array containing separate matrices
       for each target in each particle.      
   Q - Process noise covariance matrix which can be a same numeric matrix 
       for every target or a TxN cell array containing separate matrices
       for each target in each particle.

 Out:
   S - 1xN cell array containing the struct arrays of predicted particles.
   
 Description:
   Perform Extended Kalman Filter prediction step for each target
   and each association hypothesis particle. The model is

     x_i[k] = a_i(x_i[k-1], q , param),  q ~ N(0,Q_i)

   for each target i. Dynamics a_i() for each target
   are assumed to have known statistics.

 See also:
   KF_MCDA_UPDATE, KF_PREDICT, KF_UPDATE