Application of aerodynamic model structure determination to UAV data

This paper concerns aircraft system identification and, in particular, the process of aerodynamic model structure determination. Its application to experimental data from unmanned aerial vehicles (UAVs) is also described. The procedure can be particularly useful for determining an aerodynamic model for aircraft with unconventional airframe configurations, which some unmanned aircraft tend to have. Two model structure determination techniques are outlined. The first is the well-established stepwise regression method, while the second is an adaptation of an existing frequency response approach which instead utilises maximum likelihood estimation. Example applications of the methods are presented for two data sources. The first is a set of UAV flight test data and the second is data recorded from dynamic wind tunnel tests on a UAV configuration. For both examples, the model structures determined using stepwise regression and maximum likelihood analysis matched one another, suggesting that the maximum likelihood approach and the chosen thresholds for its statistical metrics were reliable for the data being analysed.