ekf_mcda_predict.m

基于RBMCDA (Rao-Blackwellized Monte Carlo Data Association)方法的多目标追踪程序

%EKF_MCDA_PREDICT  EKF Monte Carlo Data Association Prediction
%
% Syntax:
%   S = EKF_MCDA_PREDICT(S,A,Q,AM,AW,param)
%
% In:
%   S    - 1xN cell array containing particle structures.
%   A    - Derivative of a() w.r.t. state 
%          as matrix if common for all targets or
%          as cell array of size TxN, for each target in
%          each particle. Can also be a inline function or name of
%          function in form A(x,i,param), where i
%          is the index of the target x.             (optional, default eye())
%   Q    - Process noise of discrete model as matrix
%          if common for all targets, or as cell array
%          of size Tx1 for all targets separately.   (optional, default zero)
%   a    - Dynamical model as cell array
%          of size TxN, for each target in each particle,
%          or inline function or name of function in
%          form a(x,i,param), where i is the
%          index of the target x.                    (optional, default A(x,i)*X)
%   AW   - Derivative of a w.r.t. q
%          as matrix if common for all targets or
%          as cell array of size TxN, for each target
%          in each particle. Can also be a inline function or name
%          of function in form AW(x,i,param), where
%          i is the index of the target x.           (optional, default identity)
%  param - Parameters of A and a.
%
% 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:
%   EKF_MCDA_UPDATE, EKF_PREDICT, LTI_DISC, KF_PREDICT

% History:
%   16.01.2008  JH  Changed the way the parameters of a are passed.
%                   Also modified the description a bit. 
%   13.05.2003  SS  Support for function handles
%    3.12.2002  SS  The first official version.
%
% Copyright (C) 2002 Simo S鋜kk