针对比尔-朗伯定律单色传输和其他透过率模型计算速度慢的问题, 为了实现红外目标的高速被动测距, 研究了被动测距系统中氧分子A带吸收特征及大气中氧分子吸收率的计算方法。分析了大气中氧分子A带的吸收光谱及分布特性, 以当前大气参数和测量环境为基础, 结合HITRAN数据库, 将随机Malkums带模式引入到氧分子带平均吸收率计算中, 建立了基于随机Malkums带模式的被动测距数学模型。搭建了测距实验平台, 在12~128 m内对7个不同点进行了距离测量。实验结果表明, 在实际大气条件下, 利用该被动测距模型测得被测目标距离与实际距离的平均误差达到1.8%。该模型正确、可行, 满足红外目标被动测距的高速在线测试及隐蔽性、高精度、抗干扰能力强等要求。

Aiming at the slow calculation speed both of monochrome transmission based on Beer-Lambert Law and other transmittance models, the absorption features of oxygen A band was analyzed and algorithms of oxygen absorptivity in atmosphere was investigated in order to realize real-time and high-efficient passive ranging of infrared targets. The absorption spectrum and distribution characters for oxygen A band were analyzed. The passive ranging model based on random Malkums mode was built by introducing the random Malkums mode to the calculation of the band average absorptivity of oxygen molecules with the current atmospheric parameters, testing environment and HITRAN database. Then the passive ranging test platform was established for measuring seven different points ranging from 12 to 128 m. Experimental results show that the model is accuracy and the average error of oxygen A band between measured and calculated distances is 1.8% in current atmosphere. The proposed passive ranging algorithms is feasible and can satisfy the system requirements of rapid speed, online, concealing, higher precision, as well as strong anti-jamming.