Researches On UAV Based Moving Targets Detection And Tracking And Vision Aided UAV Landing System

Unmanned Aerial Vehicle (UAV) is extra favored by the military experts for its own dominance. Specially,UAV has already been one of the very important military development fields for its success in the last brushfires. Moving target tracking on the platform of UAV and the assistant landing system of UAV are taken as the backgrounds of this dissertation. The image corner detection, camera ego motion compensation, moving target tracking in the cluttering background, the scale and rotation adaptive tracking of the target, puny target real-time and high-accurate detection, the assistant landing system and other relative technologies are investigated in this dissertation. The main contents and achievements of this dissertation are as follows:(1) There is definite error to calculate the gradient orientation by traditional gradient operators. Based on the analysis of the gabor wavelet, a new gradient calculating operator is proposed. The new operator can obtain the orientation of the gradient more accurately, and restrains the noise more effectively than the traditional gradient operators. And a new corner detecting algorithm based on gabor gradient operator is proposed. Experimental results with some synthetic and real images show that this new algorithm detects the corner more efficiently, locates the corner more accurately, and restrains the noise more effectively than the classical algorithms.(2) For the tracking of the moving target on the moving platform, one commonly used algorithm is to eliminat the camera ego motion firstly, and then track the moving target. An camera ego motion compensation algorithm based on the gabor feature descriptions is proposed. Experimental results show that the new method can effectively compensate the camera ego motion and detect the moving targets.(3) When a target moves in the cluttering backgrounds, the variational backgrounds can reduce the stability and reliability of the tracking algorithms. So the backgrouds must be restrained. For the heterogeneous target, the target areas in the image are different for the target's ununiformity. If some areas in the target are more different from the backgrounds, it shows that the diversity of these areas is stronger and these areas are more helpful for target tracking. Based on the above-mentioned principle, a diversity weight calculation algorithm is proposed. Experimental results show that the new algorithm can restrain the backgrounds effectively, and that the weights accord with the human intuitionistic recept. Based on the diversity weights, a diversity weighted least square image matching method is proposed. Simulation experimental analysis and real image tracking results show that the new method can track moving target in the cluttering backgrounds more effectively and accurately than the traditional tracking methods. A new diversity weighted Mean Shift tracking method (DWMS) is proposed. Its convergence condition is discussed. And its convergence is proved. Experimental results show that DWMS can effectively track moving targets in the cluttering background too.(4) It is one of the most important problem for target tracking whether the initial features and the describing areas of the target are accurate. Based on the scale-space theory, a new method of the optimal ellipse describing area of the target is proposed. The new method provide a foundation for the feature analysis of the target. It is one of the most difficult research fields of computer vision to track target which takes the change of rotation and scales at the same time. Based on the analysis of the scale-space theory , the current Mean Shift algorithms and the optimal ellipse describing area of the target, a scale and rotation adaptive Mean Shift tracking algorithm is proposed. Experimental results show that the new Mean Shift tracking algorithm can more effectively track the target which takes the change of both rotation and scale than the current mean shift algorithms. At the same time, the new algorithm can supply the size and angle information of the target.(5) To detect and track puny target high-accurately and in real-time, a new scale adaptive little target detecting and tracking method based on the positive and negative LOG operator is proposed. Experimental results demonstrate that the new method has great capability in real time detection, precise detection and noise restraint.(6) In the landing process of UAV, navigation control is very important. At present, the GPS navigation is usually used because it is very accurate and easy. But its signal can be easily disturbed during the war. The vision-based navigation system becomes one of the most important research fields for its superiority. A assistant landing system based on the photogrammetry is proposed. Experimental results show that the system can obtain the accurate location of UAV according to the runway, and save the images of the whole landing process of UAV synchronously. which can provide effective information for post analysis.