ABSTRACT
One essential feature of advanced RNAV systems
is the use of Kalman filters, named after Dr
Richard Kalman who introduced this concept in
the 1960s. Kalman filters are optimal recursive
data processing algorithms that filter navigation
sensor measurements. The mathematical model is
based on equations solved by the navigation
processor. To illustrate the principles of Kalman
filters, consider an RNAV system based on
inertial navigation sensors with periodic updates
from radio navigation aids. (Inertial navigation is
described in Chapter 17.) One key operational
aspect of inertial navigation is that system errors
accumulate with time. When the system receives
a position fix from navigation aids, the inertial
navigation system’s errors can be corrected.
