光学 精密工程, 2017, 25 (10): 2584, 网络出版: 2017-11-24   

中高轨道目标的地基光电监视

Ground-based photoelectric surveillance for mid-high orbit target
作者单位
1 中国科学院 长春光学精密机械与物理研究所, 吉林 长春 130033
2 中国科学院大学, 北京 100049
摘要
针对中高轨目标暗弱为目标识别和识别效率增加的难度, 研究了基于被动光学系统的地基光电光测系统; 同时提出了一种通过对原始图像进行最优化处理, 从而有效提高目标信噪比, 增加目标识别效率的方法。首先分析了在轨目标的光学反射特性, 比较了不同模式下目标的信噪比, 给出光电监视系统的最优设计方案。然后, 结合目标运动特性和观测条件等因素, 设计了适合中高轨道目标的地基地球同步轨道(GEO)目标的观测模式。最后, 针对暗弱目标图像识别难题, 提出了基于最优化原理的低信噪比目标识别图像处理的新方法。根据实测数据对本文方法进行了实验验证, 并与传统差帧法进行了比较。结果显示, 本文方法可在目标信噪比大于3.09点条件下识别出目标。 该项研究对中高轨道目标光电监视用设备的设计和使用很有参考价值。
Abstract
A ground-based photo-electronic surveillance system based on passive optical systems was investigated for improving its recognition ability and recognition efficiency for faint targets in mid-high orbits. Meanwhile, an optimized processing method for original images was presented to enhance the Signal to Noise Ratios(SNRs)of the faint targets and improve the system recognition efficiency. The optical reflection characteristics of orbital targets were analyzed and a optimized design scheme for the ground-based photo-electronic surveillance system was given by comparing the SNRs in different modes. In combined with target motion, observation conditions and other factors, an observation model of Geosynchronous Orbit (GEO) targets was designed. Finally, in view of faint target recognition, a new target recognition method for faint targets was presented based on optimization principle. According to the measured data, this method was validated and compared with that of the traditional difference frame method. The results show that the target can be identified when the target SNR is greater than 3.09. This research provides a high reference value for the design and application of photo-electronic surveillance equipment for faint targets in the mid-high orbit.

高扬, 赵金宇, 刘俊池, 杨晓霞, 王斌, 王敏, 陈涛. 中高轨道目标的地基光电监视[J]. 光学 精密工程, 2017, 25(10): 2584. GAO Yang, ZHAO Jin-yu, LIU Jun-chi, YANG Xiao-xia, WANG Bin, WANG Min, CHEN Tao. Ground-based photoelectric surveillance for mid-high orbit target[J]. Optics and Precision Engineering, 2017, 25(10): 2584.

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