Adaptive tuning of a Kalman filter using the fuzzy integral for an intelligent navigation system

This paper describes the development of an intelligent, adaptive tuning system for a Kalman filter to optimally integrate data from an inertial navigation system (INS) and the Global Positioning System (GPS). This system is particularly useful for accurate navigation of an aircraft during maneuvering periods. The tuning algorithm is based on fuzzy logic. Specifically, the inference method in the fuzzy rule base uses the concepts of fuzzy measure and fuzzy integral. This method of inference is particularly useful for multivariable fuzzy systems that are embedded in expert systems. Typical results obtained from the developed approach are presented and discussed in the paper, illustrating satisfactory performance.