Since the lack of explicit modeling of the system dynamics of an UAV limits the efficiency of the control system, a method for time domain parameter identification of a miniature rotorcraft based UAV is presented. A linear state space model improvised by nonlinear extensions is proposed. Exclusive attention is given to the execution of special flight test maneuvers to expose the subtleties of the complex dynamics inherent to rotorcrafts. State of the art instrumentation, avionics and sensor fusion packages are implemented to increase data reliability. After checking for Kinematic Consistency the recorded data is analyzed to estimate model parameters with a Maximum Likelihood Output Error estimation method through a time-domain matching algorithm. The results obtained to date and the challenges faced are discussed in this paper.
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