## 1 Introduction  
The properties and distribution of aerosol particles in the atmosphere are attracting more and more research interest due to their impact on the climate system, air quality, and human health [1, 2]. Particles with aerodynamic diameters smaller than 2.5 \(\upmu\)m (PM\({}_{2.5}\)) have received considerable attention because of their great damage to human health, especially their ability to penetrate deep into the lungs and cause great damage. Particulate matter in the atmosphere has a variety of components, including carbonaceous material, sulfate, nitrate, ammonium, microorganisms, trace metals, sea salts, and crustal elements [3, 4]. These particles suspended in the air have complex physical and chemical properties, such as wider size distribution, irregular morphology, and different optical absorption. Measuring these properties can help classify and recognize different kinds of aerosols, and even evaluate their possible source, which can be very important for the control of atmospheric environmental pollution and also to better understand atmospheric dynamics and long-range transport [5]. Various methods and technologies have been used to determine aerosol types [6, 7, 8, 9]. A lidar system can provide altitude-resolved information. Based on extensive parameters,such as the scattering angstrom exponent (SAE), absorption angstrom exponent (AAE), and single scattering albedo (SSA) retrieved from Raman lidar systems [10] or high spectral resolution lidar (HSRL) systems [11], different aerosol types were distinguished by [PERSON] et al. [12] and [PERSON] et al. [5]. Some advanced lidar systems with polarization detection can improve the estimation of the microphysical properties of aerosols, allowing the backscattering separation of spherical particles from any other non-spherical particle [13]. In recent years, there have been many methods based on single-particle scattering in aerosol observation and analysis instruments [14; 15; 16], among which the aerosol optical counter (AOC) is most representative [17]. Research has revealed that the angular distribution of scattered light can be used to estimate a particle's nature. For example, the signal around 12\({}^{\circ}\) scattering angle is sensitive to particle size, and the signal around 60\({}^{\circ}\) is sensitive to the refractive index of particles. Combining measurements at the two angles, a light optical aerosol counter (LOAC) can provide the size distribution and differentiate some kinds of particles like droplets, carbonaceous particles, salts, and mineral particles [18]. The polarization version of AOC that detects horizontal and vertical polarization components at a scattering angle of 120\({}^{\circ}\), namely a polarization optical particle counter (POPC), is capable of classifying three aerosol types, mineral dust, air pollution, and sea-salt particles [19]. Our previous work also shows that the polarization index of S2/S0 at the scattering angle 115\({}^{\circ}\) can been used to differentiate soot from salt and sand [20]. A wealth of information, such as the size, composition, and morphology of particles, are contained in polarization properties. Extracting information based on the polarization method has been widely used in atmospheric, marine, and biomedicine applications [21; 22]. [PERSON] combined Mueller matrix polar decomposition (MMPD), frequency distribution histogram (FDH), and the central moment analysis method to distinguish qualitatively different bacterial colonies [23]. [PERSON] used polarization characterization [24; 25] to distinguish different kinds of marine algae. In this paper, we need an online dynamic monitoring system to analyze atmospheric suspended particulates one by one. It is difficult to obtain the full Mueller matrix of a single particle in real-time. Herein, we detect the Stokes vector of the suspended particles, and we can improve the information dimension of aerosol polarization signals by collecting the multi-angle scattering Stokes vectors synchronously.