Aerospace and Electronic Systems Magazine May 2017 - 20

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



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