Navigational sensors are evolving both on a commercial and research level. However, the limitation still lies in the accuracy of the respective sensors. For a navigation system to reach a certain accuracy, multi sensors or fusion sensors are used. In this paper, a framework of fuzzy sensor data fusing is proposed to obtain an optimised navigational system. Different types of sensors without a known state of inaccuracy can be fused using the same method proposed. This is demonstrated by fusing compass/accelerometer and GPS signal. GPS is prone to inaccuracies due to environmental factors. These inaccuracies are available in the extracted NMEA protocols as SNR and HDOP. Dead reckoning sensors on the other hand do not depend on external radio signal coverage and can be used in areas with low coverage, but the errors are unbounded and have an accumulative effect over time.
Soft computing control system have been applied in various applications particularly in the fields of robotics controls. The advantage of having a soft computing controls methods is that it enable more flexibility to the control system compared with conventional model based controls system. In this paper, a UAV airship is controlled using fuzzy logic for its propulsion and steering system. The airship is tested on a simulation level before test flight. The prototype airship has on board GPS and compass for telemetry and transmitted to the ground control system via a wireless link.