Quadcopter sensing of magnetic and electric field with geospatial analytics

Mark W. Roberson; C. Kenneth Williams; Laura E. Roberson

doi:10.1117/12.2305050

27 April 2018 Quadcopter sensing of magnetic and electric field with geospatial analytics

Mark W. Roberson, C. Kenneth Williams, Laura E. Roberson

Proceedings Volume 10645, Geospatial Informatics, Motion Imagery, and Network Analytics VIII; 1064504 (2018) https://doi.org/10.1117/12.2305050
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

Monitoring the level and type of power consumption in an area over a period of time by mapping of field strengths presents detailed information of human activities and the presence of facilities. Power grid usage traditionally has been collected for subsequent viewing at a few fixed locations. Transitioning from collect-and-view to real-time geospatial analytics over a continuous spatial coverage requires making more extensive use of moving sensors. Unmanned airborne systems (UAS) provide mobility in three dimensions, but also present noise issues and severe weight constraints. We discuss our work with collection of multi-axis magnetic and electric field data from a quadcopter UAS. We model collection physical sensor geometries as well as sensor electronics in order to discuss the performance trade-offs. We collect electromagnetic data at several heights above the ground plane of the target sites and calculate the fundamental and harmonic frequency power of the data as well as the self-sense noise. We analyze the data using ArcGIS for visualization of power “hot spots” for different combinations of power spectral data and compare the results to 3-D modeling tools to estimate the magnetic and electric field strengths. We discuss the results of our experiments in using the UAS to perform advanced processing on board in real time in order to initiate cross-cueing of sensors.

Conference Presentation

Citation Download Citation

Mark W. Roberson, C. Kenneth Williams, and Laura E. Roberson "Quadcopter sensing of magnetic and electric field with geospatial analytics", Proc. SPIE 10645, Geospatial Informatics, Motion Imagery, and Network Analytics VIII, 1064504 (27 April 2018); https://doi.org/10.1117/12.2305050

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