安永泉, 王志斌, 李晋华, 王召巴. 基于O2 吸收特性单站被动测距机理研究[J]. 红外与激光工程, 2015, 44(1): 310-316.
引用本文: 安永泉, 王志斌, 李晋华, 王召巴. 基于O2 吸收特性单站被动测距机理研究[J]. 红外与激光工程, 2015, 44(1): 310-316.
An Yongquan, Wang Zhibin, Li Jinhua, Wang Zhaoba. Research on single station passive ranging based on O2 absorption characteristics[J]. Infrared and Laser Engineering, 2015, 44(1): 310-316.
Citation: An Yongquan, Wang Zhibin, Li Jinhua, Wang Zhaoba. Research on single station passive ranging based on O2 absorption characteristics[J]. Infrared and Laser Engineering, 2015, 44(1): 310-316.

基于O2 吸收特性单站被动测距机理研究

Research on single station passive ranging based on O2 absorption characteristics

  • 摘要: 大气中氧分子浓度分布相对稳定,随纬度位置和季节变化不大;吸收波段跨越762 nm,易于被非低温探测器探知;带内无叠加其他大气组分吸收谱。据此提出基于其吸收特性的比尔定律被动测距。通过基线拟合寻找762 nm 和690 nm 附近的吸收率来反演距离。朗伯-比尔定律应用中的一项固有误差项被发现,定义为非线性初值。其本质是仪器非理想特性的限制引起的不可消除的线间辐射强度。搭建距离测算实验平台,对东经113,北纬38地区,不同季节不同时段不同天气条件,建立大量的不同组约束条件下的氧吸收率与距离的关系样本数据库。统计拟合得到经验模型实时修正理论模型中的非线性初值项,距离反演精度小于2.7%。

     

    Abstract: The distribution of oxygen density is relatively stable in the atmosphere. It changes little with latitude and season. Its absorption bands step across 762 nm which is easy to be obtained by non-cryogenic detectors. No other absorption spectrum of atmospheric constituents add to this band. Accordingly, the single station passive ranging based on O2 absorption characteristics and Beer's law was proposed. The absorption rate near 762 nm and 690 nm was used to calculate distance by baseline fitting. An inherent error term was found in application of Lambert-Beer law. It was defined as Nonlinear Initial Value (NIV). Its innate character is the radiation intensity between the lines caused by limitations of instrument characteristics. It can not be eliminated. The experimental platform was built to calculate the distance. For 113 degrees east longitude, 38 degrees north latitude, different seasons, times and weather conditions, a large number of samples were collected to establish the database. Each sample is a relationship between absorption rate and distance in one set of constraints. Empirical model was gotten through statistical fitting. The Nonlinear Initial Value (NIV) in theoretical model was corrected in real time. The distance inversion accuracy is 2.7%.

     

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