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Research on Acquiring and Tracking Moving Object Based on Optical Phased Array

Author: ChengXin
Tutor: ZhangJian
School: Harbin Institute of Technology
Course: Instrument Science and Technology
Keywords: Optical Phased Array Moving target capture Moving Target Tracking Position transformation
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 56
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Abstract


Lidar play an important role in the protection of space security, mainly used for the search of space moving target acquisition and tracking. Optical Phased Array as a laser beam control device, in real time, without inertia, high-precision control of the multi-beam laser beam, so the use of laser optical phased array radar compared with conventional laser radar in a more flexible manner, higher efficiency, higher precision tracking moving targets, this study is based on optical phased array moving target acquisition and tracking. One of the advantages of optical phased array is the flexibility and agility to change the shape and energy distribution of the beam, and active illumination closed loop tracking system with real-time image acquisition system. System via the search target, the laser light emitted by the optical phased array network once the moving target, the optical phased array i.e. adaptive to change the beam shape of the light energy is concentrated in the target, within the system, moving target acquisition and tracking software system must first from the laser network image quickly found and isolated targets, and secondly to be able to predict the target trajectory is given to the optical phased array, the instruction of the control beam azimuth, so that the laser beam accurately track the target, the active illumination of the moving target fast, stable tracking. The main contents of this paper are as follows: (1) study the theoretical methods research in laser net lighting conditions to capture a moving target. In theory, the capture of the moving target detection by moving target, image thresholding segmentation and image filtering three parts. Image grayscale characteristics of moving targets on the basis of the different methods of moving target detection, image thresholding segmentation and image filtering, and then they are composed of a variety of capture methods simulation comparison, is determined by comparing the results fast, stable capture method. The capture method using background subtraction method to detect moving target, and then the median filter to weaken the influence of noise on the image of the moving target, and then using the Otsu method of image segmentation, morphological filtering to eliminate the last goal within the pores. (2) to capture the moving target on the basis of studies of a method for tracking a moving target. Moving target tracking method transformed target spatial position tracking and movement of the target image by the motion of two parts. Wherein the moving object image tracking using centroid wave gate tracking method, and the method is not only the target centroid position of the current frame image can be calculated, but also to predict the target centroid position of the next frame image. Transformed target spatial position through movement of the actual spatial position of the centroid position of the image target is converted into the target, in order to control the laser network point, thereby actively illuminate the moving target, in order to achieve the tracking target purposes. (3) the feasibility of tracking methods capture by tracking the experimental verification moving target. Acquisition and tracking moving targets based on optical phased array experimental platform was designed and implemented, the complete software preparation, and ultimately based optical phased array moving target acquisition and tracking experiment. The experimental results show that the acquisition and tracking methods in the active lighting conditions, can be fast, stable track moving targets.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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