ADVANCED CALCULATION FOR DETERMINING POSITION AND ANGLE OF UNGUIDED AIRCRAFT-ROCKET BASED ON THE MOTION DETECTION IN AERIAL WEAPON SCORING SYSTEM

Most of all techniques of the Aerial Weapon Scoring System (AWSS) are developed to determine the final position of practice aircraft-rockets in which identified by the impact point coordinates. This paper presents the technique of implementing 3D-view geometry approach to determine all required rocket-parameter results including trajectory, position, and angle in the shootingtarget. The developed system generates the resulted rocket-trajectory data which consists of an explosionimage- point and rocket-image-point from the motion detection method used. The aircraft-rocket is observed by the 3CCD-digital video camera where its position should be perpendicular to the position of the-rocketshot. The transforming view of the Z-axis in the initial video processing are the key point of determining the absolute view of captured-images processed. The calculation used in this research employs the scaling and comparison of pixel coordinates and real-world coordinates. All experimental results in this paper are generated from the real rocket-firing exercise conducted in the Air Weapon Range. The results will be useful to support AWSS in producing advanced analysis of fighter air-to-ground rocket-firing exercise.

[1]  Tae-Hyun Oh,et al.  Real-time motion detection based on Discrete Cosine Transform , 2012, 2012 19th IEEE International Conference on Image Processing.

[2]  R. Venkatesh Babu,et al.  Sprite Generation From Mpeg Video Using Motion Information , 2004, Int. J. Image Graph..

[3]  Yanpeng Cao,et al.  Viewpoint invariant features from single images using 3D geometry , 2009, 2009 Workshop on Applications of Computer Vision (WACV).

[4]  Song-Chun Zhu,et al.  Scene Parsing by Integrating Function, Geometry and Appearance Models , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Lijing Zhang,et al.  Motion Human Detection Based on Background Subtraction , 2010, 2010 Second International Workshop on Education Technology and Computer Science.

[6]  Taizo Umezaki,et al.  Moving object detection using strip frame images , 2010 .

[7]  Widyawan,et al.  Adaptive motion detection algorithm using frame differences and dynamic template matching method , 2012, 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).

[8]  Juan Moreno García,et al.  Video sequence motion tracking by fuzzification techniques , 2010, Appl. Soft Comput..

[9]  Cordelia Schmid,et al.  Multi-view object class detection with a 3D geometric model , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.