This article is cited in 8 papers

Orthogonal supoptimal filters for nonlinear stochastic systems on manifolds

I. N. Sinitsyn

Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation

Abstract: The authors developed the synthesis theory of suboptimal filers (SOF) based on normal approximation method (NAM), statistical linearization method (SLM), orthogonal expansions method (OEM), and quasi-moment method (QMM) for nonlinear differential stochastic systems on manifolds (MStS) with Wiener and Poisson noises. Exact optimal (for mean square error criteria) equations for MStS with Gaussian noises in observation equations for the one-dimensional a posteriori characteristic function are derived. Problems of approximate solving of exact equations are discussed. Accuracy and sensitivity equations are presented. A test example for the nonlinear scalar differential equation with additive and multiplicative noises is given. Some generalizations are mentioned.

Keywords: a posteriori one-dimensional distribution; coefficient of orthogonal expansion; first sensitivity function; normal approximation method; normal suboptimal filter; orthogonal expansion method; orthogonal suboptimal filter; quasi-moment method; quasi-moment; statistical linearization method; stochastic system on manifolds; suboptimal filter; Wiener white noise.

Received: 29.10.2015

DOI: 10.14357/19922264160103

Bibliographic databases:

•