Characterization and compensation of magnetic interference resulting from unmanned aircraft systems

Unmanned aircraft systems (UAS) are a viable platform for aeromagnetic surveys but the interference generated during flight can greatly impact data quality. In this thesis, the problem of interference reduction was approached from two directions: mapping to identify sources and manoeuvre compensation.Problematic interference sources were identified using magnetic intensity mappings of the UAS. For these mappings to be accurate, the UAS must have: (1) the motors engaged, (2) the flight surface servos powered and in a steady-state position, and (3) the electrical systems drawing a constant current. The strongest sources were the servos and the motor system with the largest field attributed to the direct current battery cables between the motor batteries and the electronic speed controller. Reduction methods recommended included the twisting of direct current cables, demagnetisation of steel components, and increasing the distance between the servos and the intended magnetometer installation point.To improve mapping quality, a magnetic scanner was designed and built to compare the magnetic intensity mappings and profiles of four different types of electric-powered UAS; a single-motor fixed-wing, a single-rotor helicopter, a quad-rotor helicopter and a hexa-rotor helicopter UAS. These UAS were found to have: (1) similar interference signatures under rotation, (2) interference levels dependent on the electrical current drawn by the motor(s), (3) a mixture of interference types composed of both material magnetisation and electrical current.The removal of interference produced by a 35 kg gasoline-powered UAS was demonstrated using a real-time compensator. The UAS was prepared with interference reduction techniques that reduced the heading error and 4th difference to acceptable levels. Two novel low-altitude calibration methods, named a "stationary" and "box" calibration, were tested in three geographic locations with different magnetic gradients. The best calibration using each method yielded an improvement ratio of 8.595 and 3.989, respectively and a standard deviation of the compensated total magnetic intensity of 0.075 and 0.083 nT, respectively. A best estimated Figure-of-Merit of 3.8 nT was calculated; the lowest value reported for a rotary-wing UAS to date. The stationary calibration was robust and compensated non-native flight data with a cross-correlation index of 1.073.