Screen Shot #7 (Merely a picture to illustrate that our GUI is totally self-explanatory)

Tables are essentially files and variable and time can be specified as outputs (without any internal TK-MIP headers). Standard statistics can be invoked and compiled on appropriate sample functions and TK-MIP includes capability to perform calculation of Spherical Error Probable (SEP) and Circular Error Probable (CEP) either at the standard probability of 0.50 or as possibly customized to a more stringent designated probability of containment, as say at probability 0.90 (as occurs for NMD application).

TK-MIP avails collections of coarser output plots (where an illustrative example is offered below) that are quickly  selectable (from an automatically available standard menu or repertoire of reasonable outputs of interest to analysts for comparison purposes) with application identifiers that can be further customized by the user for conveying quick insight into the status of computed results. These results may be cascaded or either horizontally or vertically tiled and multiple plots may be displayed within a single graph as distinctly identified by style of tick mark, plot style, and color.

By clicking on the face of the corresponding graph with their mouse, the USER causes the graph to fill out to full size,  which completely covers the background border (which is pink, as in the above example). Each graph created in this way is assigned its own unique background border color (which makes them easier to track and distinguish at a glance). If USER later wants to rename graph titles, axis titles, change tick marks, connecting graph colors, or styles, USER just clicks maximize button in upper right corner for the graph of interest and the colored border is again exposed to offer further customizing options (an operation that can be invoked and be performed over and over again). After grouping and tiling multiple graphs via juxtaposition in a way that best suits the USER’s needs to “tell a story”, the entire collection can be printed out either one-at-a-time or en masse as a single snapshot using the upper left Print.  

These coarse “no frills” output plots (above) just connect the individually computed output pairs depicted here above as “dots”, as obtained at every designated discrete-time sample, to visually depict the computed results graphically for the immediate benefit to the User, by quickly availing any trends that a knowledgeable User may, perhaps, recognize and understand right away as an immediate cross-check as a form of immediate USER gratification by availing fast bare-bones results to appease the USER's curiosity. The other more sophisticated plot packages, depicted earlier above, have all the standard computational accoutrements (i.e., “bells and whistles”), such as the option of invoking Bézier curves so that all output curves are smooth (except where estimator outputs are depicted as essentially instantaneous vertical jumps between two different finite levels), representing processing results obtained both before and immediately after a measurement sensor data update, as they specifically affect:

1. computed state estimator outputs,

2. the associated on-line computed covariances,

3. the associated computed errors in these outputs, as obtained by directly comparing the available “true state” to the computed estimated state.