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📄 ekf_nmcda_update.m

📁 基于RBMCDA (Rao-Blackwellized Monte Carlo Data Association)方法的多目标追踪程序
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%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% History:%   11.02.2008  Added support for the new particle structure%   24.08.2004  Changed birth/death model to that of article%   09.12.2003  The first official version.%% Copyright (C) 2003 Simo S鋜kk

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