The current trend in high-accuracy aircraft navigation systems is towards using data from one or more inertial navigation
subsystem and one or more navigational reference subsystems. The enhancement in fault diagnosis and detection is
achieved via computing the minimum mean square estimate of the aircraft states using, for instance, Kalman filter
method. However, this enhancement might degrade if the cause of a subsystem fault has some effect on other subsystems
that are calculating the same measurement. One instance of such case is the tragic incident of Air France Flight 447 in
June, 2009 where message transmissions in the last moment before the crash indicated inconsistencies in measured
airspeed as reported by Airbus. In this research, we propose the use of mathematical aircraft model to work out the
current states of the airplane and in turn, using these states to validate the readings of the navigation equipment
throughout smart diagnostic decision tree network. Various simulated equipment failures have been introduced in a controlled environment to proof the concept of operation. The results have showed successful detection of the failing equipment in all cases.
This paper describes the concept of an intelligent high speed wireless ad-hoc network, which is currently being
developed. The technology aims at, not replacing any of the existing standards, but aims to complement them in urban,
military and hazardous environments. Known as Rhino, the technology is a platform independent, IP based network
which will provide adequate bandwidth for real time video, audio and data traffic. The technology and specifications
described in this paper are based on initial development of the technology.