Real-time estimation of wireless ground-to-air communication parameters

To enable effective communication-based mission planning, a Scaled Unscented Kalman Filter (SUKF) is implemented on an unmanned aircraft to estimate the communication performance of ground nodes in real time, based solely on signal strength measurements. Our communication model extends Rappaport's log-distance model to account for directional antenna patterns. The filter is tuned on simulated data for fast convergence, and then tested through 12 flight experiments where the aircraft communicates with several types of ground nodes over IEEE 802.11b channels. State estimates settle within 15 minutes of a 45-minute flight, with the final eistmate's RMS deviation from the observed signal achieving between 4 and 9 dB. This represents a 20 to 80% improvement over a tuned filter based on the traditional log-distance model that ignores directional effects.