红外, 2016, 37 (11): 29, 网络出版: 2017-01-03
被动红外易制毒挥发气体光谱数据预处理技术
Preprocessing of Spectra of Precursor Chemical Vapor Detected by Passive Infrared Remote Sensing
被动红外遥测技术 禁毒 光谱数据预处理 卡尔曼滤波 passive infrared remote sensing drug control spectral data preprocessing Kalman filtering
摘要
由于信号强度低、环境复杂等因素会造成光谱杂乱和波峰不 明显,利用被动红外远程遥测技术难以准确地对易制毒化学品 气体进行定性检测,即使采用基本的数字滤波算法也无 法有效解决这些问题。为此提出了一种基于卡尔曼/维 纳叠加的滤波算法。通过用该算法对光谱信号进行预处理,可以有效提高后期 波峰匹配的定性检测的准确性。基于改进的算法对采集到的 实验数据进行了验证。结果表明,与其他滤波算法的 处理效果相比,本文方法可以对干扰信号进行有效 过滤,并且可以对特征峰进行准确识别。
Abstract
Since the factors such as low signal intensity and complicated environment may cause the spectrum to be cluttered and cause the wave peak to be not obvious, it is difficult for infrared remote sensing to detect precursor chemical vapor accurately. Even the basic digital filtering algorithm is used, the problem can not be solved. For this reason, a filtering algorithm based on Kalman/Wiener superimposion is proposed. By using this algorithm to preprocess spectral signals, the qualitative detection accuracy in subsequent wave peak match can be improved effectively. The experimental data collected are verified on the basis of the improved algorithm. The result shows that compared with other filtering algorithms, the improved algorithm can filter interference signals effectively and can identify characteristic peaks accurately.
沈俊, 李志豪. 被动红外易制毒挥发气体光谱数据预处理技术[J]. 红外, 2016, 37(11): 29. SHEN Jun, LI Zhi-hao. Preprocessing of Spectra of Precursor Chemical Vapor Detected by Passive Infrared Remote Sensing[J]. INFRARED, 2016, 37(11): 29.