Table 1.

Overview of the state-of-the-art LiDAR sensor model working principles and validation approaches.

Authors	Covered Weather Phenomena	Covered Effects	Validation Approach
Goodin et al. [7]	Rain	Signal attenuation, false negative, ranging error $d_{error}$, decrease in maximum detection range	Simulation results
Wojtanowski et al. [8]	Rain, fog, aerosols	Signal attenuation, target reflectivity, range degradation	Simulation results
Rasshofer et al. [9]	Rain, fog, snow	Signal attenuation, range degradation	Simulation results, qualitative comparison with real measurements for fog attenuation
Byeon et al. [10]	Rain	Signal attenuation	Simulation results
Li et al. [11]	Rain, fog, snow, haze	Signal attenuation	Simulation results
Zhao et al. [12]	Rain, fog, snow, haze	Signal attenuation, false positive	Quantitative comparison with measurements for rain
Guo et al. [13]	Rain	Signal attenuation	Qualitative comparison with measurements
Hasirlioglu et al. [14,15]	Rain	Signal attenuation, false positive	Quantitative comparison with measurements
Berk et al. [16]	Rain	Signal attenuation, false positive	Simulation results
Espineira et al. [17]	Rain	Signal attenuation, false positive	Simulation results
Kilic et al. [18]	Rain, fog, snow	Signal attenuation, false positive	Quantitative comparison with measurements
Hahner et al. [19]	Fog	Signal attenuation, false positive	Quantitative comparison with measurements
Haider et al. (proposed approach)	Rain, fog	Signal attenuation, SNR, false positive, false negative, ranging error $d_{error}$	Qualitative comparison with measurements for all covered effects