Title: INTEGRATED NAVIGATION SYSTEMS AND KALMAN FILTERING: A PERSPECTIVE
Author(s): R. G. Brown
Published in: NAVIGATION, Journal of the Institute of Navigation, Volume 19, Number 4
Pages: 355 - 362
Cite this article: Brown, R. G., "INTEGRATED NAVIGATION SYSTEMS AND KALMAN FILTERING: A PERSPECTIVE", NAVIGATION, Journal of The Institute of Navigation, Vol. 19, No. 4, Winter 1972-1973, pp. 355-362.
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Abstract: KALMAN FILTERING has been used in a wide variety of aided inertial navigation systems in recent years. Yet it appears that Kalman filtering and its overall role in the integrated system in still not well understood by many in the navigation community. This paper is largely tutorial and is directed toward pinpointing the precise role that the filter plays in the integrated system. The presentation is made from a system viewpoint with the details of Kalman filtering completely surpressed. It is first noted that in the current generation of aided inertial systems the filter operates only on the system errors and not on the total dynamical quantities such as position and velocity. The inertial system is then corrected in accordance with the filter’s best estimates of the system errors. It is shown that this mode of operation fits within the framework of complementary filtering which has been used in a number of instrumentation applications. This perspective is particularly useful in helping one understand the system limitations in this mode of operation. Next, it is pointed out that the more general problem of estimating total position and velocity is actually one of nonlinear estimation. Within this context, then, the current scheme of system integration can be seen as a special form of nonlinear filtering known as an extended Kalman filter. When viewed this way, one thinks of the inertial system as providing the estimated trajectory, and the aiding sources are the noisy measurements that provide corrections to the trajectory. This viewpoint gives some additional insight into the filter limitations, because nonlinear estimation theory can be brought to bear on the problem. In summary, the current state of the art is on a plateau in terms of system organization, and has been for the past decade. No genuinely new information-processing concepts have been introduced into the navigation business since the early Sixties. The paper concludes on a speculative note with regard to possible advances in system organization.