High Fidelity In-Flight Pressure and Inertial Canopy Sensing

In order to effectively understand airdrop system dynamics, analysis and verification beyond simulation alone must be pursued. This requires accurate experimental data for both the canopy and payload. Measurement of parafoil-payload relative motion has always been challenging due to the flexible nature of the canopy and requires a sensing system that does not interfere with canopy packing, does not significantly increase the canopy mass, and requires no physical connection between the canopy and payload. In 1999, Strickert and Jann [1] successfully used video-image processing techniques to measure parafoil-payload relative motion. Post flight analysis demonstrated the difficulty in estimating the differences in the orientation of the payload and canopy. Later in [2] and [3], using the same videomeasurement system, a multi-body simulation was used primarily to investigate relative longitudinal displacement, lateral displacement, and yawing. In this paper, the authors take a different approach by embedding multiple miniature low power wireless inertial sensors into the canopy. After release, the canopy sensors transmit inertial data to a main payload flight computer in during flight. As in [4], information provided from each sensor includes: magnetometer data, angular velocity, and accelerations; however, new to this work is the addition of pressure sensors which can also measure individual cell pressures and multiple GPS modules. The miniature canopy sensors were installed in an MC-4/5 canopy that mated with an autonomous guidance unit (AGU). Data was collected first for two drops with three sensors, with an emphasis on working out communication logistics between all of the sensors and the main payload module and evaluating the most recent sensor upgrades. A final drop was completed with 14 sensors embedded in the canopy (two GPS sensors and 12 pressure-inertial sensors). The experimental miniature wireless canopy sensors platform used in the parafoil and payload system is outlined in Section 2. Section 3 details the first two drops and analyzes the trajectories of each, followed by the pressure measurements and their analysis in Section 4. Section 5 highlights the performance of the system with 14 embedded sensors.