# trackingMSCEKF

Extended Kalman filter for object tracking in modified spherical coordinates (MSC)

*Since R2018b*

## Description

The `trackingMSCEKF`

object represents an extended Kalman filter
(EKF) for object tracking in modified spherical coordinates (MSC) using angle-only
measurements from a single observer. Use the filter to predict the future location of an
object in the MSC frame or associate multiple object detections with their tracks. You can
specify the observer maneuver or acceleration required by the state-transition functions
(`@constantvelmsc`

and `@constantvelmscjac`

) by using the
`ObserverInput`

property.

The following properties are fixed for the `trackingMSCEKF`

object:

`StateTransitionFcn`

-`@constvelmsc`

`StateTransitionJacobianFcn`

-`@constvelmscjac`

`MeasurementFcn`

-`@cvmeasmsc`

`MeasurementJacobianFcn`

-`@cvmeasmscjac`

`HasAdditiveProcessNoise`

-`false`

`HasAdditiveMeasurementNoise`

-`true`

## Creation

### Description

returns an
extended Kalman filter to use the MSC state-transition and measurement functions with
object trackers. The default `mscekf`

= trackingMSCEKF`State`

implies a static target at 1
meter from the observer at zero azimuth and elevation.

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

= trackingMSCEKF(Name,Value)`Name,Value`

pair arguments. Any unspecified properties take default values.

## Properties

## Object Functions

`predict` | Predict state and state estimation error covariance of tracking filter |

`correct` | Correct state and state estimation error covariance using tracking filter |

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

`distance` | Distances between current and predicted measurements of tracking filter |

`likelihood` | Likelihood of measurement from tracking filter |

`clone` | Create duplicate tracking filter |

`residual` | Measurement residual and residual noise from tracking filter |

`initialize` | Initialize state and covariance of tracking filter |

`smooth` | Backward smooth state estimates of tracking filter |

## Examples

## References

[1] Aidala, V. and Hammel, S., 1983.
*Utilization of modified polar coordinates for bearings-only tracking.*
IEEE Transactions on Automatic Control, 28(3), pp.283-294.

## Version History

**Introduced in R2018b**

## See Also

`trackingEKF`

| `trackingCKF`

| `trackingIMM`

| `trackingGSF`

| `trackingPF`