IMM_UPDATE UKF based Interacting Multiple Model (IMM) Filter update step Syntax: [X_i,P_i,MU,X,P] = IMM_UPDATE(X_p,P_p,c_j,ind,dims,Y,H,R) In: X_p - Cell array containing N^j x 1 mean state estimate vector for each model j after prediction step P_p - Cell array containing N^j x N^j state covariance matrix for each model j after prediction step c_j - Normalizing factors for mixing probabilities ind - Indices of state components for each model as a cell array dims - Total number of different state components in the combined system Y - Dx1 measurement vector. H - Measurement matrices for each model as a cell array. h - Measurement mean param - parameters R - Measurement noise covariances for each model as a cell array. Out: X_i - Updated state mean estimate for each model as a cell array P_i - Updated state covariance estimate for each model as a cell array MU - Probabilities of each model X - Combined state mean estimate P - Combined state covariance estimate Description: IMM-UKF filter measurement update step. If some of the models have linear measurements standard Kalman filter update step is used for those. See also: IMM_PREDICT, IMM_SMOOTH, IMM_FILTER

- kf_update KF_UPDATE Kalman Filter update step
- ukf_update1 UKF_UPDATE1 - Additive form Unscented Kalman Filter update step

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