Authors:
Aritro Dey
;
Manasi Das
;
Smita Sadhu
and
T. K. Ghoshal
Affiliation:
Jadavpur University, India
Keyword(s):
Adaptive Filters, Nonlinear Filtering, Gauss Hermite Quadrature Rule, State Estimation, Parameter Estimation.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Nonlinear Signals and Systems
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
This paper presents an adaptive Gauss Hermite filter for nonlinear signal models in the situation when the
measurement noise statistics is unknown. The proposed nonlinear filter, based on the Gauss Hermite
quadrature rule, can ensure satisfactory estimation performance despite the problem of unknown
measurement noise statistics by online adaptation. Results of Monte Carlo Simulation demonstrate the
efficacy of the proposed filter for joint estimation of parameters and states using an object tracking problem.