基于激光雷达能见度仪的微弱信号检测方法

发布时间：2018-11-25 18:34

【摘要】：在不良气象条件下,能见度的精确探测对机场飞机安全起降有着举足轻重的地位。然而激光雷达能见度系统在强光照条件工作时,易受到背景噪声的影响,该背景噪声主要来自于太阳、天空的光辐射和内部元件热辐射,且随地点、时间和天气状况不同而变化。本文基于激光雷达能见度仪进行了微弱信号检测工作,能够有效地抑制背景噪声,从而大幅度地提高能见度设备的测量范围和精度,对于确保民航安全有着很高的实际价值。本文研究系统基于后向散射原理,采用具有低脉冲能量、高脉冲重复频率的二极管泵浦固体激光器(DPSSL)和具有低噪声、高量子效率的雪崩光电二极管(APD)探测器,确保了系统的测量精确性;特别的,采用了嵌入式计算机作为系统的控制和数据处理核心,并实现了对系统工作时序的控制。针对强光照条件下回波信噪比恶化的实际情况,本文采用系统改进与信号处理相结合的办法,提出了一种新的实时背景噪声补偿法配合采用阈值分割的移动平均法的组合方法处理信号,大幅度地去除了回波信号中的背景噪声,提高了回波信噪比,进而提高了后续能见度的反演精度。最后经过数值仿真和外场对比实验,该检测方法的能见度探测总体误差小于20%,表明该方法具有较高的准确性和有效性。
[Abstract]:Under bad weather conditions, the accurate detection of visibility plays an important role in the safe take-off and landing of airport aircraft. However, the visibility system of lidar is easily affected by background noise, which comes mainly from the sun, the sky and the heat radiation of the internal elements, and it is affected by the background noise when operating in the strong illumination condition, and the background noise comes from the sun, the sky and the heat radiation of the internal elements. Time and weather vary. In this paper, the weak signal is detected based on the lidar visibility meter, which can effectively suppress the background noise, thus greatly improve the measurement range and accuracy of the visibility equipment, which has a high practical value to ensure the safety of civil aviation. Based on the principle of backscattering, a diode pumped solid-state laser (DPSSL) with low pulse energy and a high pulse repetition rate and an avalanche photodiode (APD) detector with low noise and high quantum efficiency are used in this paper. The accuracy of the system is ensured. In particular, the embedded computer is used as the control and data processing core of the system, and the control of the working sequence of the system is realized. Aiming at the deterioration of echo signal to noise ratio (SNR) under strong illumination condition, the method of system improvement and signal processing is adopted in this paper. In this paper, a new real-time background noise compensation method combined with moving average method with threshold segmentation is proposed to process the signal, which removes the background noise in the echo signal and improves the signal-to-noise ratio of the echo signal. Furthermore, the inversion accuracy of subsequent visibility is improved. Finally, through numerical simulation and field contrast experiments, the overall error of visibility detection is less than 20, which shows that the method has high accuracy and effectiveness.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN958.98

【相似文献】