Research On Pure Azimuth Target Tracking And Navigation Technology For Unmanned Aerial Vehicle Based On Image Vision

Bearing-only target positioning and tracking based on image vision is a passive location and tracking technology.It only needs to passively receive the target azimuth angle information to achieve the positioning and tracking of the target,and no need to radiate external energy,it has the characteristics of good concealment performance,strong anti-interference ability and high reliability,so it has become a research hotspot of current target tracking.At present,the use of observers to achieve positioning and tracking of targets under orbital motion has received much attention,it includes two parts: target state estimation and circumnavigation control.But the performances of the existing estimation and control laws are not so accurate when the target position is not known beforehand,and resulting in low target tracking accuracy.For the above problems,this paper proposes a virtual intersecting location approach based on bearing-only,and designs a target state estimation strategy and a circumnavigation strategy based on a quadrotor drone.And the accurate of target state estimation strategy is obtained with Kalman filter,also improving the accuracy of target positioning and tracking.The main work of the paper is as follows:Firstly,the overall design of the quadrotor UAV system is designed.In response to the functional requirements of vision-based bearing-only target positioning and tracking system,the quadrotor UAV control system and visual navigation system are designed,and the specific functions of each part are introduced in detail.Secondly,for the azimuth of target and UAV in the bearing-only target positioning and navigation system,this paper uses the Raspberry Pi and camera as the visual navigation system,obtain target information by camera.First,the target image information is captured by the camera;the image thresholding method and morphological filtering method are used to extract the target and obtain the image offset information of the target;and then alignment of attitude angle measurement and height measurement with image sampling time is achieved through time registration,and the offset of the target is obtained,and a calculation algorithm of the target azimuth is given according to the coordinate conversion.Finally,the registration of the azimuth angle information and image information of the UAV is performed by the time registration technology,and the target azimuth angle is given according to the coordinate conversion.Through the image tracking experiments on actual targets,the correctness of the angle solution theory is verified,which verified that the algorithm described in this article can provide highprecision angle measurement informationThen,in order to solve the problem of low target state estimation accuracy in the current bearing-only target tracking,this paper proposes a virtual intersection localization algorithm combined with Kalman filtering algorithm,and designs a state estimation strategy to achieve the unbiased estimation of target.First,achieve a rough estimation of target used the estimation strategy,solve the virtual observation position of the drone by the rough estimated speed and the current position of UAV.Then,the localization value of the target is obtained according to the algorithm.Finally,the Kalman filter algorithm is used to achieve unbiased estimation of the target state.Finally,in response to the problem of large circumnavigation control errors in current bearing-only target tracking,this paper designs a circumnavigation control strategy,and modified it by the unbiased estimation of the target state to achieve the accurate circumnavigation of the target,which ensure that the circumnavigation radius control error converges to zero asymptotically.Numerical simulations and experiments verify the theoretical correctness and engineering practicability of the algorithm.Compared with existing target tracking methods and circumnavigation control strategies,the algorithm proposed in this paper can effectively improve the accuracy of target state estimation and circumnavigation radius control accuracy.