Improvement of Navigation Accuracy Using Tightly Coupled Kalman Filter

In this paper, a mechanism is designed for integration of inertial navigation system information (ins) and global positioning system information (gps). in this type of system, a series of mathematical and filtering algorithms with tightly coupled techniques with several objectives such as application of integrated navigation algorithms, precise calculation of flying object position, speed and attitudes at any moment. obviously, gps speed information will contribute to make better estimates of the state in addition to location information. typically, kalman filter provides optimal method for states estimation and also creates possibility of combining several measurements to acquiesce a united estimate of system status. tightly coupled kalman filter is a novel and applicable approach to effectively track path with high accuracy especially when four satellites are not available or satellite system stops along the route. indeed, an important advantage of integration with tightly coupled filtration is related to application of software system rather than hardware which somehow reduces hardware complexity and also other advantages of sensors integration is associated with application of all benefits of various sensors as well as covering their individual imperfections in order to increase navigation accuracy. generally, in integration systems exact gps observations are used to estimate and ins errors modification by kalman filter. it is expected that an integrated system with high-precision provides an accurate estimation of all unknowns’ parameters and states through kalman filter. simulations executed for integrated navigation system demonstrate that a flying object could sufficiently compensate errors resulting from modeling of inertial navigation that grows integrally over time and also impressively inhibit flying object deviation respect to condition that only gps location information are available.