Position Covariance Projection Choose Plane
Projection of the equal probability density ellipsoid defined by the position covariance matrix onto the specified plane. Any plane defined in the Vector Geometry Tool is available for use, including user defined planes. The data requires position covariance to be defined for the object.Available for these objects: Aircraft, GroundVehicle, LaunchVehicle, Missile, Satellite, Ship
Type: Time-varying data.
Availability: Reports | Graphs | Dynamic Displays | Strip Charts
Pre-data required: "<Scale> <SEPProb> <PlanePath> <PlaneName>" where <PlanePath> is the truncated path of the plane parent.
Data Provider Elements
Name | Dimension | Type | Description |
---|---|---|---|
Time | Date | Real Number or Text | Time. |
Sigma Axis-1 | Distance | Real Number | Square root of the first diagonal component of the projected covariance matrix. |
Sigma Axis-2 | Distance | Real Number | Square root of the second diagonal component of the projected covariance matrix. |
Correlation 12 | Unitless | Real Number | Correlation coefficient of the projected covariance matrix. |
1/(Inverted Sigma Axis-1) | Distance | Real Number | Square root of the inverse of the first diagonal element of the inverse of the projected covariance matrix. |
1/(Inverted Sigma Axis-2) | Distance | Real Number | Square root of the inverse of the second diagonal element of the inverse of the projected covariance matrix. |
Major Sigma Dir Angle | Angle | Real Number or Text | Angle between the major axis of the equal probability density ellipse and the first axis of the projection plane. |
Major Sigma | Distance | Real Number | Square root of the maximum eigenvalue of the projected covariance matrix. |
Minor Sigma | Distance | Real Number | Square root of the minimum eigenvalue of the projected covariance matrix. |
Area | Area | Real Number | Model area. |
CEP | Distance | Real Number | "Circular error probable" - statistically equivalent circular representation for the elliptical equal probability density contour defined by the projected covariance matrix. |