Uavs Auxiliary Landing Research Based On Different View

In order to increase autonomy and intellectuality of the UAV landing, this paper studies the visual assistant landing method of fixed wings UAV. Through the analysis of UAV landing process, this paper divided the UAV landing process into three visual stages, which is remote stage, middle stage and close stage. In different stages, UAV uses different visual strategies, identify different goals, achieve different accuracies.In the remote stage, the main mission of the visual identification is confirming the orientation of the airport by identifying the airport and the main environmental objectives around it. The method of identifying airports is to divide the image into 16*16 sized subblocks firstly, making multi-scale decomposition of every subblock through the Contoulet transform, then extracting moment feature and texture feature under different scales, and combine these features as subblock’s feature vector. Comparing each subblock’s feature vector with the airport environmental feature database in order to identify which environment the subblock belongs to, finally determine the location of the airport in the view. In the middle stage, the runway is the main target that UAV need to identify from background. The template matching method can be used for the runway identification in this paper. The rapid improved SIFT algorithm is used to extract SIFT characteristics of the background and the template, then comparing the template’s SIFT features with the background’s, in order to look for the characteristic points matched with template in the background. There must be a runway in the background, when there are some matched feature points in the background, then getting the location of the runway. In the close stage, the main task of UAV visual recognition is identifying the landing logo. This paper designs landing logo as "H" and extracts it from background by using the difference of bright color between the landing logo and the runway. Because of the complexity of the actual environment, this paper uses the steady Hough transformation to detect line of logo’s edge and extract characteristic points on the logo by getting cross points of straight-line equation. Then making camera on-line calibration by using the homography of plane, getting attitude angle and location by establishing coordinate system and calculating external parameters matrix of the camera.There is scientificity in dividing UAV visual landing process into three stages, because each stage has certain continuity, the identifying key is different and recognition task is light in each stage. The experimental results show that the main environmental logo can be recognized well in the remote stage, the SIFT feature matching can locate the runway very well in the middle stage, the technology of on-line calibration and pose estimation can meet the need of the UAV landing in the close stage.