Trajectory prediction via a feature vector approach
Patent
·
OSTI ID:1771505
Described herein are various technologies pertaining to extracting one or more features from trajectory data recorded during motion of a body, and further, generating a n-dimensional feature vector based upon the one or more extracted features. The n-dimensional feature vector enables expedited analysis of the trajectory data from which the feature vector was generated. For example, rather than having to analyze a trajectory curve comprising a large number of time-position data points, the n-dimensional feature vector can be compared with one or more search parameters to facilitate clustering of the trajectory data associated with the n-dimensional feature vector with other trajectory data which also satisfies the search request. The trajectory data can be plotted on a screen in combination with the n-dimensional feature vector, and other pertinent information. The trajectory data, etc., can be displayed using heat maps or other graphical representation.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- Assignee:
- National Technology & Engineering Solutions of Sandia, LLC (Albuquerque, NM)
- Patent Number(s):
- 10,801,841
- Application Number:
- 15/454,812
- OSTI ID:
- 1771505
- Country of Publication:
- United States
- Language:
- English
Adaptive Algorithm to Improve Trajectory Prediction Accuracy of Climbing Aircraft
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journal | January 2013 |
Trajectory Clustering and an Application to Airspace Monitoring
|
journal | December 2011 |
A Methodology for Automated Trajectory Prediction Analysis
|
conference | August 2004 |
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