A Study on Coaxial Quadrotor Model Parameter Estimation: an Application of the Improved Square Root Unscented Kalman Filter

The parametrized model of the Unmanned Aerial Vehicle (UAV) is a crucial part of control algorithms, estimation processes and fault diagnostic systems. Among plenty of available methods for model structure or model parameters estimation, there are a few, which are suitable for nonlinear UAV models. In this work authors propose an estimation method of parameters of the coaxial quadrotor’s orientation model, based on the Square Root Unscented Kalman Filter (SRUKF). The model structure with different aerodynamic aspects is presented. The model is enhanced with various friction types, so it reflects the real quadrotor characteristics more precisely. In order to validate the estimation method, the experiments are conducted in a special hall and essential data is gathered. The research shows that the SRUKF, can provide fast and reliable estimation of the model parameters, however the classic method may lead to serious instabilities. Necessary modifications of the estimation algorithm are included, so the approach is more robust in terms of numerical stability. The resultant method allows for dynamics of selected parameters to be changed and is proved to be adequate for on-line estimation. The studies reveals tracking properties of the algorithm, which makes the method more viable.