A computer program has been developed that analyzes Deep Space Network monitor data, looking for changes of trends in critical parameters. This program represents a significant improvement over the previous practice of manually plotting data and visually inspecting the resulting graphs to identify trends. This program uses proven numerical techniques to identify trends. When a statistically significant trend is detected, then it is characterized by means of a symbol that can be used by pre-existing model-based reasoning software. The program can perform any of the following functions:

  • Given an expectation that data in a given list should exhibit an upward, downward, constant, or unknown trend, it can determine whether the data do or do not follow such a trend.
  • Given a list of data, it can identify which of the aforementioned trends the data follow.
  • Given two lists of data, it can determine whether or not both follow the same trend.

This program can be executed on a variety of computers. It can be distributed in either source code or binary code form. It must be run in conjunction with any one of a number of Lisp compilers that are available commercially or as shareware.

This program was written by Mark James of Caltech for NASA's Jet Propulsion Laboratory. For further information, access the Technical Support Package (TSP) free online at www.techbriefs.com/tsp under the Software category.

This software is available for commercial licensing. Please contact Karina Edmonds of the California Institute of Technology at (626) 395-2322. Refer to NPO-42107.


This Brief includes a Technical Support Package (TSP).
Identifying Trends in Deep Space Network Monitor Data

(reference NPO-42107) is currently available for download from the TSP library.

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This article first appeared in the December, 2006 issue of NASA Tech Briefs Magazine.

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