On-board wind speed estimation for UAVs

Motivated by the desire to improve the navigation and guidance performance of small unmanned aerial vehicles (UAVs), we propose simple methods for modeling the local wind flow that affects the vehicle’s trajectory. Particularly we present an algorithm applicable to estimating those wind patterns when considering a conventional suite of onboard UAV avionics. In addition, the proposed algorithm can be performed efficiently using small, sparse data sets collected in real-time by the sensor platform . As such this paper deals with the estimation of the 3D wind components and shows that successful wind estimation is possible for any UAV trajetory. The available sensors are the GPS, IMU/Compass for heading and elevation and the Air Data sensors for speed measurement. Monte Carlo simulations are performed to illustrate the efficacy of the proposed algorithms. The estimator is then implemented on data obtained from real flight experiments to further illustrate the algorithm’s efficacy.