In the real world, weather conditions rarely present themselves in a simple, singular, and uniform manner. Instead, they usually exist in a mixed state of countless randomly distributed particles. These particles are of a wide variety. In natural environments, we encounter elements such as rain, fog, or snow. In the realm of man-made environments, there are randomly dispersed particles like smoke. Regardless of their origin, these particles have the potential to exert a significant and far-reaching impact on laser transmission.When a laser signal propagates through this complex particle environment, it undergoes a substantial attenuation process. As it passes through numerous discrete and randomly arranged particles, its energy is continuously absorbed and scattered. This complex process transforms the laser echo signal into an extremely complex and unstable one. The consequences are two-old: not only does it exponentially increase the complexity of signal processing, but it also significantly weakens the reliability and stability of the laser communication system. Therefore, dealing with the impact of these complex particles on laser transmission has become a core and crucial challenge in multiple key fields, including the fields of laser communication, target recognition, navigation, and fuze technology.This study comprehensively explores the combined effects of a variety of particles (rain, fog, snow, ammonium sulfate, silicate, and black carbon) across a range of wavelengths. It carefully takes into account the rich and diverse meteorological conditions prevalent in the real-world environment. By establishing laser transmission models for three different mixed particle groups (each particle group having unique distributions and complex refractive index characteristics), this study has gained a deeper and more profound understanding of these complex phenomena. Utilizing the powerful tools of second-and fourth-order speckle statistics, an in-depth and detailed analysis has been carried out on the intensity fluctuation correlation function and the intensity distribution autocorrelation function of speckle patterns at different transmission distances.The results of this study have led to a series of key and enlightening observations. First of all, for the three mixed particle swarm models under study, as the transmission distance gradually increases, the scattering intensity undulation correlation function shows a continuous upward trend. Notably, when considering the 1 064-nanometer wavelength, under the influence of larger particle swarms, this function only experiences relatively small and subtle changes. It turns out that different particles have different and unique effects on the scattering intensity undulation correlation function. In scenarios consisting solely of rain, fog, and snow particles, raindrop particles become the dominant factor influencing the overall variation of this function. Conversely, in environments filled with ammonium sulfate, silicate, and black carbon particles, for 532-nanometer laser light, the correlation between different positions within the same spatial region is significantly weakened. This weakening of the correlation can be attributed to the stronger penetration ability of near-infrared wavelengths, which in turn leads to distinctly different scattering behaviors.The sharpness of the peaks in the autocorrelation function of the scattering spot's intensity distribution is also intricately related to the proportion of different particles. Specifically, the larger radius of raindrop particles results in more widespread and dispersed light scattering, while the significant imaginary part in the complex refractive index of black carbon particles leads to more intense absorption of laser light. Among all the particles analyzed, an increase in the proportion of ammonium sulfate particles has the most significant and far-reaching impact on this function, followed closely by raindrop particles. By carefully adjusting the contrast of the simulated scattering patterns, these patterns can be clearly distinguished visually. A comparison of these patterns vividly shows that the scattering pattern generated by the 1 064-nanometer laser wavelength becomes more obvious and prominent after passing through a random medium filled with ammonium sulfate particles.In such a complex and unpredictable random environment, the information transmitted through the LiDAR system is extremely vulnerable to interference. The insights obtained from this study provide valuable and crucial guidance for optimizing LiDAR signal coding and modulation. By thoroughly understanding how various environmental factors and particle characteristics affect laser transmission, it is possible to enhance the anti-interference ability of the transmitted information in these challenging environments, thereby ensuring its accuracy and stability. These insights also provide the necessary and crucial theoretical support for extracting accurate and effective target information. In addition to optimizing communication systems, a deep understanding of the relationship between the scattering intensity distribution and particle swarm characteristics can completely revolutionize the optimization process of feature extraction algorithms for point cloud data. Therefore, this study has laid a solid and stable foundation for subsequent important tasks, such as creating accurate three-dimensional models and identifying specific static or dynamic targets. Ultimately, these research results play an important role in improving the efficiency and reliability of LiDAR systems and related technologies in practical applications, thus promoting innovation and improvement in a wider range of fields.