Dissertation > Aviation, aerospace > Aviation > Aircraft instrumentation,avionics, flight control and navigation > Flight control system and navigation > Navigation

Multi-sensor Data Fusion Technology Research and Application in UAV Navigation System

Author DieJiaYu
Tutor PeiHaiLong
School South China University of Technology
Course Control Theory and Control Engineering
Keywords UAV data fusion height measuring Kalman filter autonomous taking-off and landing
CLC V249.3
Type Master's thesis
Year 2011
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The helicopter is capable of taking-off and landing vertically and hovering at some point,this is impossible for other aircrafts.In military field,the UAV can be used to low-altitude reconnaissance and electronic warfare and greatly improved the capability of fighting efficiency.The other hand,it can be used to biochemical weapons detection and target instruction and so on.In civil field,it mainly be used for aerial mapping,eco-environment monitoring,real-time broadcast TV and a variety of pipelines exploration and maintenance and so on. It is the ever increasing applications that create the project.Firstly introduced the basic knowledge of aircraft navigation,include common navigation coordinates,attitude description methods and inertial navigation system,then introduced the basic theory of data fusion:basic concepts of data fusion,related mathematical knowledge and quantitative analyzed the detection performance of that system base on multi-sensor height measuring,it provides the necessary theoretical support for the design.Through rational attitude,altitude sensors’selection,we made a stable attitude-position measuring system.Kalman filtering algorithm is the key of data processing.The perfect combination of hardware and algorithm provide reliabile data for height and velocity,it is the guarantee for autonomous taking-off and landing and trajectory tracking.In this paper,we analyzed the performance of three height sensors and established state equations and observation equations,and made the state estimation of system model with Kalman filtering algorithm.The simulate results show that the data fusion algorithm is effective.The vertical motion model is the key of precise vertical velocity control,the combination of strategy of taking-off and landing and vertical motion model completed the autonomous taking-off and landing control algorithm.In the premise of attitude maintain,the accurate height data made the stable taking-off and landing,hovering and trajectory tracking.The actual flight curves shows the perfect performance of the navigation system and achieve the flight expect result basically.

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