Research On UAV Location And Navigation System For Building Detection

Concrete building facilities are liable to be cracking,which not only affects the appearance,reduces the durability,but even poses a threat to people's lives and property.The traditional building detection method is manual detection,which has the problems of strong subjectivity,low efficiency and even threatening the safety of monitoring person.With the rapid development of UAV and sensor technology,UAV has been gradually applied in building inspection work.However,the quality and efficiency of manual controlled UAV detection largely depends on the level of pilot operation,which is subjective and prone to accidents.In this paper,UAV is used as a carrier to detect buildings,which can meet the needs of the development of building inspection.According to the building size information,the flight path of UAV is preset,the surface image of building is collected by the camera carried by UAV,and finally the crack detection is completed by off-line image processing.On the basis of building detection,this paper mainly focuses on the research of UAV location and navigation system.The main contents of this paper are as follows:(1)The overall scheme design of UAV location and navigation system is carried out,including UAV optical flow/IMU integrated location and navigation system and the overall structure of software and hardware.The basic flow of UAV building detection is studied,the technical difficulties in the detection process are analyzed,and the basic principle of inertial navigation system(INS)is briefly introduced.(2)A UAV attitude estimation method based on adaptive Kalman filter is designed.In order to meet the requirements of UAV motion attitude,the research of adaptive Kalman filter algorithm is emphasized based on the traditional Kalman filter algorithm.An adaptive Kalman filter algorithm which can dynamically adjust the covariance matrix of system noise and measurement noise simultaneously is proposed.By monitoring the change of innovation sequence,the variance matrix of system and measurement noise is estimated and adjusted in real time to track the change of system model.Attenuation factor is introduced to prevent filtering divergence.Finally,the effectiveness of the algorithm is verified by experiments.(3)A location method of UAV based on particle filter is designed.The basic principle of optical flow velocity measurement is briefly introduced,and the basic process of particle filter localization is analyzed in detail.For the particle degradation problem of particle filter,the dynamic system resampling and EKF algorithm are combined to perform particle filter localization.The UAV building detection and location model is studied.Finally,a simple experiment is designed and analyzed.(4)The location experiment of UAV building detection and is designed.According to the requirements of UAV building inspection,the equipment are selected,the experimental platform is built,and the on-site field UAV flight location experiment and analysis are carried out.The location and navigation system of UAV building detection designed in this paper overcomes the problem of inaccurate location caused by weak GPS signal,which can ensure good flight location accuracy and has high security and practicability.The experimental study shows that the system achieves the desired design objectives.