Xu Wenjing, Xian Jinhong, Sun Dongsong. Polarization lidar system for smoke and dust monitoring and experimental research[J]. Infrared and Laser Engineering, 2023, 52(3): 20220508. DOI: 10.3788/IRLA20220508
Citation: Xu Wenjing, Xian Jinhong, Sun Dongsong. Polarization lidar system for smoke and dust monitoring and experimental research[J]. Infrared and Laser Engineering, 2023, 52(3): 20220508. DOI: 10.3788/IRLA20220508

Polarization lidar system for smoke and dust monitoring and experimental research

  •   Objective   The fires in forests, wetlands, grasslands and other natural areas are characterised by their sudden and destructive nature, and it is important to reduce the damage caused by fires through early detection and fighting. Traditional fire monitoring methods such as manual inspections and cameras do not allow for 24/7, wide-area monitoring, and there is a lag in detecting fires. Therefore, the use of lidar with high precision, high resolution, long detection distance and sensitivity to changes in aerosol particle concentration, etc., can play an important role in the field of smoke and fire monitoring, to achieve early detection and early warning of fire. Researchers have made some explorations in this area. However, for lidar detection distance of 2 km or more, the single pulse energy of the laser was on the order of millijoule, and there is a human eye safety risk for outdoor use. Moreover, the researchers have not given an analysis of the measurement and application in a multi-obstacle environment. Therefore, a polarimetric lidar system with a day and night detection, and detection distance of more than 6 km and the single pulse energy of the laser on the order of microjoule is proposed.
      Methods   Laser wavelengths adapted to outdoor long-range detection are obtained through simulations. The lidar scanning strategies are designed for different installation scenarios, for flat environments and for environments with many obstacles, respectively. As the lidar measurement areas are at a certain height from the ground, correction for fire point positioning errors is based on a Gaussian plume model. A portable lidar system with polarization channels was built to further validate the simulation results, scanning control strategies and inversion algorithms through field experiments.
      Results and Discussions   By simulating the detection distance of lidar with different wavelengths, the results show that the detection distance of lidar with 1 064 nm wavelength is 1.3-1.4 times of 532 nm wavelength (Fig.2). By optimizing the scanning strategy and algorithm (Fig.4), the influence of fixed obstacles and temporary moving obstacles can be eliminated. In order to avoid obstacles of similar height around the installation site, a certain elevation angle is usually set for the lidar, and the horizontal distance deviation and vertical height measurement deviation resulting from the existence of the detection elevation angle are calculated. When the elevation angle of lidar detection is 2°, the measured height deviation at 6 km is 209.397 m. The Gaussian plume model is used to simulate the soot concentration distribution. When the atmospheric stability is B and the average wind speed is 1 m/s, the high value point of soot concentration distribution at 200 m height is ≥1 km from the ground fire point, it provides a correction basis for accurate location of fire point. Outfield measurements by using 1 064 nm polarization lidar in both mountainous and plain environments can quickly and accurately identify fire points, which demonstrate the feasibility of using lidar for smoke and fire monitoring.
      Conclusions   A scanning polarization lidar can rapidly identify fire smoke and dust. The field experiments were conducted in Panshan County, Panjin City, Liaoning Province, around Yanghu Scenic Area, and Guanyin Mountain Forest Park, Dongguan City, Guangdong Province, respectively. The polarization lidar was able to identify the smoke and dust quickly under the open area and multi-obstacle mountainous area. Observational data will be accumulated in subsequent experimental tests to verify the optical properties of various types of soot particles and further improve the identification efficiency.
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