Application of Polynomial Filtering Algorithms to Nonlinear Discrete Dynamical Systems in Navigation Data Processing

A polynomial filtering algorithm is designed for estimating a Markov sequence with the use of linear measurements. The feature of the estimation problem is that the Markov sequence is described by a nonlinear shaping filter, which is a second-order polynomial with respect to the state vector components. The efficiency of the proposed algorithm is analyzed in comparison with the nonlinear optimal algorithm and an extended Kalman filter, when solving the problem of gyroscope drift model identification.