## 1 Introduction  
Aerosols with the ability to reflect, absorb, and scatter light are composed of solid or liquid particles suspended in the atmosphere. Generally, climate change will be directly or indirectly affected by aerosols [1; 2; 3; 4]. It will also have a serious impact on human health, especially the respiratory system [5; 6]. On the other hand, aerosols will reduce atmospheric visibility, which will have an important impact on traffic, navigation, and satellite remote sensing [7; 8]. In recent years, the globalization process has become inseparable from the excessive combustion of fossil fuels and automobile exhaust emissions, and anthropogenic aerosol pollution in many areas has become increasingly serious [9; 10; 11]. Lidar is an important tool for detecting the spatial and temporal distribution of aerosols and is widely used in the fields of atmospheric science research and environmental monitoring [12; 13; 14; 15]. However, for Lidar low-altitude observations, the incomplete overlap of the laser beam and the telescope's field of view (FOV) in the near field partially receive the echo signal. The ratio of the overlap area to the cross-section of the laser beam is called the overlap factor or geometrical form factor [16]. To effectively detect the vertical distribution of low-altitude aerosols, the overlap factor of Lidar must be corrected. The overlap factor is zero in the near field and gradually reaches one as the distance increases. The influenced distance of the overlap factor differs from a few hundred meters to three kilometers, depending on the structure of the transmitting and receiving systems. Theoretically, the overlap factor can be calculated by a ray-tracing model [17, 18]. In practice, the system parameters are difficult to obtain accurately, so the overlap factors are mainly obtained by experimental means. For example, [PERSON] et al. proposed that the overlap factor can be obtained through horizontal observations under the condition of a uniform atmospheric level [19]. [PERSON] et al. proposed a method of using Raman signals to measure overlap factors [20]. In recent years, the traditional Raman method has been improved by the introduction of constraints by researchers [21, 22, 23]. It is worth noting that for aerosol Lidar that cannot perform horizontal observation and only has a meter scattering channel, the horizontal observation method and the Raman method are not suitable for calculating overlap factors. Therefore, [PERSON] et al. combined the ceilometer profile to extract the overlap factors of the Lidar [24]. [PERSON] et al. used CCD to observe the side scattering of the emitted beam to calculate the overlap factor [25]. However, to meet the detection accuracy requirements of more Lidar in different complex environments, more methods for correcting the overlap factor need to be studied.  
In this paper, a method to correct the overlap factor of Lidar is proposed, named UAVC (unmanned aerial vehicle correction), which uses an aerial vehicle (UAV) to detect the vertical distribution of particle concentration. In Section 2, the experiment and method are introduced. In Section 3, the overlap factor of the two methods under different weather conditions is calculated. The low-altitude detection capabilities of Lidar before and after geometric factor correction are compared. Finally, a conclusion is given in Section 4.