The Tracker Component Library mations of the probability density function (PDF) of the target. The measurement update and state propagation functions in the Tracker Component Library have been separated. This allows one to, for example, use a square-root cubature Kalman filter for the measurement update and a simple square-root Kalman filter for the state propagation step. The measurement update filters are listed in Table 1, and the state-propagation filters are listed in Table 2. Nonlinear filters take function handles for the dynamic models, allowing the user to quickly swap different dynamic models. Of interest for those using fixed-gain filters, is also the function findAsymptoticGain, which finds the optimal gain for general α-β style filters. Table 1. Measurement Update Functions in Version 2.0 of the Tracker Component Library a Description Function Name General Filter 1 Generic cubature/unscented/sigma-point information filter cubInfoUpdate 2 Generic cubature/unscented/sigma-point cubature Kalman filter cubKalUpdate 3 Extended information filter (first order) EIFUpdate 4 (Iterated) extended Kalman filter (first or second order) EKFUpdate 5 Ensemble Kalman filter EnKFUpdate 6 Extended square-root information filter (first order) ESRIFUpdate 7 Fixed gain (generalized α-β-γ) filter fixedGainUpdate 8 Gaussian particle filter GaussPartFilterUpdate 9 H∞ filter HInfinityUpdate 10 Information filter infoFilterUpdate 11 Kalman filter KalmanUpdate 12 Generic progressive Gaussian filter progressivGaussUpdate 13 Modified pure propagation filter purePropUpdate 14 Quasi-Monte Carlo Kalman filter (additive noise) QMCKalUpdate 15 Generic square-root cubature/unscented/sigma-point Kalman filter sqrtCubKalUpdate 16 Generic square-root cubature/unscented/sigma-point Kalman filter (nonadditive noise) sqrtCubKalNonAdditiveUpdate 17 Square-root central difference/first- or second-order divided difference filter sqrtDDFUpdate 18 Square-root central difference/first- or second-order divided difference filter (nonadditive noise) sqrtDDFNonAdditiveUpdate 19 Square-root extended Kalman filter (first order) sqrtEKFUpdate 20 Square-root information filter sqrtInfoFilterUpdate 21 Square-root Kalman filter sqrtKalmanUpdate Specialized Filters 22 Best linear unbiased estimator (BLUE), polar measurements BLUEPolarMeasUpdateApprox 23 Best linear unbiased estimator (BLUE), spherical measurements BLUESpherMeasUpdateApprox 24 Reduced state estimator reducedStateUpdate 25 Separated covariance filter separatedCovUpdate Many can be used in multiple model filters via the multipleModelUpdate function. Those using generalized α-β-γ filters will also find the function findAsymptoticGain useful. a 20 IEEE A&E SYSTEMS MAGAZINE MAY 2017