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After 2003, Iraq had no developed aviation staff and services, one of which is aircrafts maintenance. Thus, a new engineering branch called Navigation and Guidance has been opened in the Electromechanical Engineering Department / University of Technology – Baghdad. Avionics is one of the important parts of aviation which their equipment need periodic monitoring and maintenance. That requires a highly capable engineer with knowledge of repairing and developing avionics systems, such as autopilot, navigation, radar, GPS, ACAS, FDR, COM, and NAV systems.
Today, in Iraq, desertification vulnerability is high challenge, which threatens agriculture in the country. This requires monitoring farmlands, usually very large, periodically. To do that, unmanned aerial system, UAS, is deployed. However, due to many active nearby airports, an airborne collision is a high probability scenario. This requires having an advanced system as part of the aviation system to avoid such scenario i.e. ACAS. Nowadays, ACAS Xu for civil UAS is the system being used. Most of commercial UAS requires having ground control units, sometimes however when a connection is lost between the UAS and the ground unit, an automated system is required to complete the required task i.e. monitoring and surveying the targeted area. Such system has to have an intelligent decision making algorithm based on scenario training using machine learning. This will help the UAS to avoid a collision with any aircraft in high load traffic airspace.
In addition to airborne collision scenario, when UAS is monitoring targeted area, and in the same time a sand storm is hitting the area, line-of-sight between the receiver antenna in UAS and the GPS/ GLONASS satellites will be lost. Thus, inertial navigation system, INS can be used as backup system because it has time-dependent error characteristics when operated in a stand-alone mode. In contrast, GPS and GLONASS can consistently provide accurate position, velocity and timing information under good satellite signal tracking environments. The main factor limiting the use of GPS and GLONASS are the requirement for line-of-sight between the receiver antenna and the satellites, which cannot always be met.
Additional shortcomings include the low data output rate and the need to obtain attitude information and also jamming. Combined GPS/GlONASS with low cost INS systems are capable of making up for the weaknesses inherent in each. The integration of INS with GPS/GlONASS can be implemented using an adaptive filter, such as Kalman filter.
The update rate of INS system is higher than that of the GPS and GlONASS receivers, for this reason a predictor should be used to predict between sampling instant of GPS and GlONASS receivers. GPS/GlONASS integration will improve spatial distribution of visible satellite, resulting in improved horizontal and vertical dilution of precision factors, DOP. In addition, Integration of GPS/GlONASS and INS, will result a more accurate position and velocity estimation in build-up areas where the view to some GPS satellites is obscured by buildings or by sand storms, and reduce the problems caused by obstructions, as well as improved horizontal and vertical DOP factors.
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