Presentation + Paper
1 May 2017 Methods for the specification and validation of geolocation accuracy and predicted accuracy
John Dolloff, Jacqueline Carr
Author Affiliations +
Abstract
The specification of geolocation accuracy requirements and their validation is essential for the proper performance of a Geolocation System and for trust in resultant three dimensional (3d) geolocations. This is also true for predicted accuracy requirements and their validation for a Geolocation System, which assumes that each geolocation produced (extracted) by the system is accompanied by an error covariance matrix that characterizes its specific predicted accuracy. The extracted geolocation and its error covariance matrix are standard outputs of (near) optimal estimators, either associated (internally) with the Geolocation System itself, or with a “downstream” application that inputs a subset of Geolocation System output, such as sensor data/metadata: for example, a set of images and corresponding metadata of the imaging sensor’s pose and its predicted accuracy. This output allows for subsequent (near) optimal extraction of geolocations and associated error covariance matrices based on the application’s measurements of pixel locations in the images corresponding to objects of interest. This paper presents recommended methods and detailed equations for the specification and validation of both accuracy and predicted accuracy requirements for a general Geolocation System. The specification/validation of accuracy requirements are independent from the specification/validation of predicted accuracy requirements. The methods presented in this paper are theoretically rigorous yet practical.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John Dolloff and Jacqueline Carr "Methods for the specification and validation of geolocation accuracy and predicted accuracy", Proc. SPIE 10199, Geospatial Informatics, Fusion, and Motion Video Analytics VII, 1019908 (1 May 2017); https://doi.org/10.1117/12.2263855
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Databases

Analytical research

Computer programming

Computing systems

Data modeling

Analytics

Interfaces

Back to Top