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Alpha-beta filter for object tracking

The `trackingABF`

object represents an alpha-beta filter designed
for object tracking for an object that follows a linear motion model and has a linear
measurement model. Linear motion is defined by constant velocity or constant acceleration. Use
the filter to predict the future location of an object, to reduce noise for a detected
location, or to help associate multiple objects with their tracks.

`abf = trackingABF`

`abf = trackingABF(Name,Value)`

returns an alpha-beta
filter for a discrete time, 2-D constant velocity system. The motion model is named
`abf`

= trackingABF`'2D Constant Velocity'`

with the state defined as ```
[x; vx;
y; vy]
```

.

specifies
the properties of the filter using one or more `abf`

= trackingABF(Name,Value)`Name,Value`

pair
arguments. Any unspecified properties take default values.

`predict` | Predict state and state estimation error covariance |

`correct` | Correct state and state estimation error covariance |

`correctjpda` | Correct state and state estimation error covariance using JPDA |

`distance` | Distances between measurements and predicted measurements |

`residual` | Measurement residual and residual noise |

`likelihood` | Likelihood of measurement |

`clone` | Copy filter for object tracking |