An integrated GPS/vision UAV navigation system based on Kalman filter

Unmanned system (UAS) is a new type of payload, which carry the perceptive communication processing and decision-making device. Navigation system, as an important part of the unmanned system, which lead to low accuracy by GPS and vision navigation insufficient features. To solve these problems, we propose an integrated GPS/vision UAV navigation system based on Kalman filter. First, we studied the basic theory of integrated navigation and smoothing processing, introduced the knowledge of combined navigation and path smoothing, and analyzed the problems of integrated UAV navigation technology in real application. Based on Kalman filter algorithm, we design the GPS and vision fusion navigation scheme and optimize the UAV navigation path. Finally, the performance improvement of the algorithm in positioning accuracy was verified using MATLAB simulation.