Optimization of Unmanned Aerial Vehicle Aeromagnetic Surveys through Real-Time Noise Characterization and Adaptive Sensing

Abstract:

A consideration when designing a high-resolution unmanned aerial vehicle (UAV) aeromagnetic system involves characterizing and mitigating the electromagnetic interference signals generated by the UAV platform. In this study, an electromagnetic interference characterization methodology was applied using three different magnetometers with unique sensitivities and sampling frequencies. These magnetometers included a low-sensitivity, vector, fluxgate magnetometer and two high-sensitivity, scalar, optically pumped magnetometers. The successful integration of a specific magnetometer payload and UAV platform, into a UAV-borne aeromagnetic system, will be a unique process that preserves the integrity of the total magnetic intensity (TMI) measurements. This process can be informed by: (1) characterizing the sources of magnetic and electromagnetic interference generated by the UAV platform, and (2) analysing the spectral content (up to 500 Hz) of the sensed total magnetic field in real-time during surveying. Once the UAV’s electromagnetic interference signals have been characterized, this information can be used to inform the appropriate mitigation strategy for adaptive sensing. Appropriate mitigation techniques can include magnetic compensation, spectral filtering, magnetic shielding and positioning the magnetometer at a distance from the UAV. Real-time noise characterization and the application of the correct mitigation technique (adaptive sensing) allow for each survey to be optimized, leading to the acquisition of research quality TMI observations with a UAV-borne aeromagnetic system. Overall, this approach enables target-focused surveys and minimizes total flight time.