A Variable Gain Complementary Filtering Fusion Algorithm Based on Distributed Inertial Network and Flush Air Data Sensing

Aiming at the problem that accuracy of flight parameters calculated by traditional flush air data sensing (FADS) and inertial navigation system (INS) complementary filter cannot meet fine real-time control aircraft, a fusion algorithm based on distributed network FADS is proposed. This method converts into parameters, using least squares fitting theory, are obtained from pressure measured hole. Then, adjusting constant filtering algorithm, fused with to obtain high-precision parameters. Finally, simulation results show proposed can keep parameter estimation error less than 0.01 degrees throughout phase. Compared filter, smaller.