Data Parser Approaches for (Online) Parameter Estimation

Abstract

Finding maneuvers for parameter estimation in flight data records is a laborious task and traditionally performed postflight on ground. Two different data parser approaches to automatically detect these maneuvers in flight are presented. Both methods search the control input signals for significant changes that correspond to test maneuvers. The first algorithm is based on the signal time derivative of the input signal whereas the second method uses a Fast Orthogonal Wavelet Transform. Both algorithms are tested with flight test data recorded with the DLR research aircraft ATTAS. Performance results are compared and potential problems when applying the parsers to other data are discussed. Results indicate that both methods are applicable in an online parameter estimation tool.