Filtragem de kalman com restrições para sistemas não-lineares: revisão e novos resultados

Abstract

Constrained Kalman Filtering for Nonlinear Systems: Review and New ResultsThis paper addresses the state-estimation problem for nonlinear systems for the case in which prior knowledge is available in the form of constraints on the state vector. A review of methods investigated in the literature is presented together with new results. The main contribution of this paper is to categorize the investigated constrained state estimators in five groups according to the way in which the constraint information is enforced, namely, measurement augmentation, estimate projection, sigma point projection, quadratic programming, and truncation. Two illustrative examples are discussed.

Navegação terrestre usando unidade de medição inercial de baixo desempenho e fusão sensorial com filtro de Kalman adaptativo suavizado.

“…Para os que desejem obter maiores informações sobre as técnicas de filtragem estocástica, o autor recomenda além das referencias já citadas a consulta a outras obras tais como: (GELB, 1969), (LEONDES, 1970), (MAYBECK, 1976), (BAR-SHALOM, 1993), (BROOKNER, 1998), (BAR-SHALOM, 2001), (SIMON, 2006), e (TEIXEIRA et al, 2010).…”