Abstract:
Autonomous Navigation Systems (ANS) used in ballistic or cruise missiles are mostly dependent on
very high grade Inertial Navigation System (INS). INS is a dead reckoning system and its navigation
solution always drifts with time from the correct one. Using aiding from other navigation sensors such
as Global Positioning System (GPS) can help getting much better navigation solution and can allow
dependence on lower grade INS. Data fusion from both INS and GPS can be done through an
Extended Kalman Filter (EKF) either by fusing navigation solution from both sensors in a loosely
coupled (LC) technique, or by using Doppler measurements aiding to aid INS or both INS and GPS as
in tightly coupled (TC) or tightly coupled with aiding (TCA) technique which is sometimes called
Ultra-Tight (UT) integration. GPS usage has limitations in terms of missile high dynamics and signal
interference. The GPS receiver requirements to avoid these problems are conflicting. The Phase Lock
Loops (PLLs), used to track GPS signals, are required to have a bandwidth as narrow as possible to
reduce the impact of signal interference. On the contrary, the loop bandwidth has to be as wide as
possible to accommodate high signal dynamics. To solve this contradiction, a new adaptive GPS
tracking loop bandwidth tuning algorithm is designed based on integrated INS/GPS through an EKF
linked to a Fuzzy Logic Controller (FLC). This controller senses the vehicle dynamics and the
jamming signal conditions and decides the bandwidth value according to those inputs. The Adaptive
Fuzzy Ultra Tight (AFUT) GPS/INS integration architecture has been developed and assessed by
simulation using SPIRENT GSS7700 GPS hardware simulator showing that it provides a significant
anti-jam and dynamics margins over an INS/GPS with fixed tracking bandwidths in addition to the
ability of using lower grade and cheaper inertial sensors.