Monotonous Trend Estimation of Deck Displacement for Automatic Landing of Rotorcraft UAVs
Journal of Intelligent and Robotic Systems
| Hi-index | 35.68 |
A new iterative version of the Prony method is presented and shown to be exceptionally effective in finding ARMA models for acoustic data in the time domain. The method is based on a quadratic type of gradient algorithm, where it is shown that the gradient and Hessian are easily computed from the data. The new algorithm is found experimentally to have excellent convergence behavior. The performance of the algorithm is demonstrated and compared with that of the original Prony method and with that of the Steiglitz and McBride (1965) iterative prefiltering algorithm on some recorded acoustic data