Dense Fog Conditions Research Articles

Modeling and Performance Study of Vehicle-to-Infrastructure Visible Light Communication System for Mountain Roads.

Visible light communication (VLC) is considered to be a promising technology for realizing intelligent transportation systems (ITSs) and solving traffic safety problems. Due to the complex and changing environment and the influence of weather and other aspects, there are many problems in channel modeling and performance analysis of vehicular VLC. Unlike existing studies, this study proposes a practical vehicle-to-infrastructure (V2I) VLC propagation model for a typical mountain road. The model consists of both line-of-sight (LOS) and non-line-of-sight (NLOS) links. In the proposed model, the effects of vehicle mobility and weather conditions are considered. To analyze the impact of the considered propagation characteristics on the system, closed-form expressions for several performance metrics were derived, including average path loss, received power, channel capacity, and outage probability. Furthermore, to verify the accuracy of the derived theoretical expressions, simulation results were presented and analyzed in detail. The results indicate that, considering the LOS link and when the vehicle is 50 m away from the infrastructure, the difference in channel gain between moderate fog and dense fog versus clear weather conditions is 1.8 dB and 3 dB, respectively. In addition, the maximum difference in total received optical power between dense fog conditions and clear weather conditions can reach 76.2%. Moreover, under clear weather conditions, the channel capacity when vehicles are 40 m away from infrastructure is about 98.9% lower than when they are 10 m away. Additionally, the outage probability shows a high correlation with the threshold data transmission rate. Therefore, the considered propagation characteristics have a significant impact on the performance of V2I-VLC.

A MSA-YOLO Obstacle Detection Algorithm for Rail Transit in Foggy Weather

Obstacles on rail transit significantly compromise operational safety, particularly under dense fog conditions. To address missed and false detections in traditional rail transit detection methods, this paper proposes a multi-scale adaptive YOLO (MSA-YOLO) algorithm. The algorithm incorporates six filters: defog, white balance, gamma, contrast, tone, and sharpen, to remove fog and enhance image quality. However, determining the hyperparameters of these filters is challenging. We employ a multi-scale adaptive module to optimize filter hyperparameters, enhancing fog removal and image quality. Subsequently, YOLO is utilized to detect obstacles on rail transit tracks. The experimental results are encouraging, demonstrating the effectiveness of our proposed method in foggy scenarios.

Time-gated imaging through dense fog via physics-driven Swin transformer

Imaging through the fog is valuable for many areas, such as autonomous driving and cosmic exploration. However, due to the influence of strong backscattering and diffuse reflection generated by the dense fog on the temporal-spatial correlations of photons returning from the target object, the reconstruction quality of most existing methods is significantly reduced under dense fog conditions. In this study, we describe the optical scatter imaging process and propose a physics-driven Swin Transformer method utilizing Time-of-Flight (ToF) and Deep Learning principles to mitigate scattering effects and reconstruct targets in conditions of heterogeneous dense fog. The results suggest that, despite the exponential decrease in the number of ballistic photons as the optical thickness of fog increases, the Physics-Driven Swin Transformer method demonstrates satisfactory performance in imaging targets obscured by dense fog. Importantly, this article highlights that even in dense fog imaging experiments with optical thickness reaching up to 3.0, which exceeds previous studies, commonly utilized quantitative evaluation metrics like PSNR and SSIM indicate that our method is cutting-edge in imaging through dense fog.

Evaluating the effects of material reflectivity and atmospheric attenuation on photonic radar performance in free space optical channels

Abstract The automotive industry is on the verge of embracing autonomous vehicles in the near future. In the pursuit of developing self-driving cars, photonic radars have emerged as a reliable sensor technology. These radars operate based on free space optical channels, but they are vulnerable to various atmospheric challenges. In this research, the objective is to examine the effect of material reflectivity on target recognition by utilizing photonic radar under various atmospheric conditions within free space optical channels. We explore four distinct scenarios representing targets with reflectivity ranging from 90 % to 20 %. The findings of this study indicate a decrease in received signal strength as reflectivity decreases across all analysed atmospheric conditions. The key findings include successful detection of stationary targets at a 1000-m range, the impact of target reflectivity on echo signal intensity and resolution, and the system’s effective performance in detecting targets even in dense fog conditions of up to 50 dB/km and are further validated through theoretical analysis.

MERRA-2 reanalysis-aided sea fog detection based on CALIOP observation over North Pacific

Sea fog can lead to a dangerous meteorological hazard over oceans and coastal areas. Cloud-aerosol Lidar with Orthogonal Polarization (CALIOP) is an effective tool to detect sea fog, however it is ineffective for dense fog detection because the lidar signal has been fully attenuated before reaching the layer base. To address this issue by improving dense fog detection, a reanalysis-aided sea fog detection method using CALIOP lidar measurements and MERRA-2 reanalysis dataset is proposed taking the Northwestern Pacific (NP) as study area. In this method, CALIOP lidar measurements are used to locate the ceiling and base of the hydrometeor layers, and extract the candidate fog layers in the Marine Atmospheric Boundary Layer (MABL). Reanalysis dataset are used to identify real fog from the candidate fog layers based on the near-surface meteorological difference under different weather conditions (sea fog, stratus and stratus precipitation). Method validation using in-situ weather records from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) and five climate stations, shows the detection accuracy and false alarm rate of 89.4% and 2.0%, respectively. Most importantly, about 87.4% of dense fogs are successfully discriminated with the aid of reanalysis data. Model application to CALIOP data from 2007 to 2019 shows pronounced spatial and seasonal characteristics of sea fog distribution over NP, with the highest frequency (>40%) found over the Kuril Islands, Sea of Okhotsk and Bering Sea from June to August. The example demonstrates that by using time series CALIOP observations and the proposed method, one may expect spatio-temporally complete sea fog information, which is important especially for remote regions with scarce in-situ measurements (e.g. polar regions). Our research proposes and proves a novel idea of sea fog detection from space by using satellite lidar and reanalysis data, which may benefit the sea fog forecasting and dynamics analysis, by providing unprecedented large-scale high-quality observations, especially over dense fog conditions.

ПОВЫШЕНИЕ ЭФФЕКТИВНОСТИ ВЫСОКОПРОИЗВОДИТЕЛЬНЫХ БЕСПРОВОДНЫХ ОПТИЧЕСКИХ КАНАЛОВ СВЯЗИ В РАЗЛИЧНЫХ ПОГОДНЫХ УСЛОВИЯХ

A common problem of traditional radio communication channels - the lack of free frequencies,noise, low bandwidth, the need to obtain a license to use the frequency, the relative ease of hacking.Free space optical communication channels overcome these limitations, is one of the types of communicationsystems that use open space to transmit information carried by light - this points to theneed for direct visibility of the transceivers. Due to the influence of various weather conditions, thelight flux is subject to atmospheric attenuation. In this paper, a method to improve the efficiency ofhigh-performance wireless optical communication channels in different weather conditions: clearsky, fog, rain and snow was investigated. The existing wireless optical communication technology, adense multiplexing multiplexing (DWDM) system with one input and one output (SISO), was considered.And it was proposed to improve the existing system by applying multiple input/output (MIMO).An impact and attenuation analysis on the wireless optical network in different weather conditionswas conducted. The study was based on the use of the Optisystem simulation software toolkit, whichis used to emulate different weather conditions of attenuation in two types of systems. Models weredeveloped for each of the optical communication systems studied. A comparison between SISO andMIMO systems is made in terms of quality factor under different weather conditions. The proposedsystem shows promising results in terms of performance and received signal quality. The transmissionpath length of the proposed system in dense fog conditions increases by 33.6%. The transmissionpath length of the proposed system in heavy rain increases by 63.89%. The transmission pathlength of the proposed system in heavy snow increases by 35,21%.

Performance analysis of 320 Gbps DWDM—FSO System under the effect of different atmospheric conditions

The last decade has witnessed significant growth of optical communication systems due to low attenuation offered for longer distances with high capacities. Optical wireless communication such as Free space Optical (FSO) systems provide license free secure transmission with lower deployment cost to make it attractive solution for providing communication services in remote areas. However atmospheric turbulences can become major challenges for deploying the FSO systems as it affects its performance. In this work, we propose a 320 Gbps, 32 channel’s hybrid fiber + FSO system using cost efficient On OFF Key modulation by incorporating hybrid dense wavelength division multiplexing scheme. Each channel carries 10 Gbps data segregated by 100 GHz channel spacing. Also, the effect of variant climatic turbulence analyzed for non-return to zero and Return to zero system considering clear sky, light fog, moderate fog and dense fog conditions.

Fog in heterogeneous environments: the relative importance of local and non‐local processes on radiative‐advective fog formation

AbstractA 100 m resolution simulation of radiation fog observed during the Local And Non‐local Fog EXperiment (LANFEX) was performed over the Shropshire hills (UK) in order to understand the impact of local circulation on valley fog formation. The model correctly resolves all valleys and their different geometries, their associated dynamical features, and the different fog conditions between the measurement sites. Passage of stratocumulus during the night led to fog dissipation and gave the opportunity to study two fog formation stages. In the narrow valleys, fog formed at the valley floor and non‐local drainage‐flow processes acted to dissipate it. This equilibrium determined the fog optical thickness, which varied within and between valleys. Wider basins were more subject to dense fog conditions (due to local formation) than narrower valleys, where advecting fog events are locally observed through basins overflowing. The largest and most open valley of Jay Barns was impacted by numerous circulations from narrower tributary valleys, and their complex interactions affected fog formation differently between events. The impact of cloud microphysics on the simulated fog is studied by comparing simulations with one‐moment and two‐moment schemes. The use of a two‐moment scheme brings improvements when the prognostic number concentration is used to compute cloud optical properties, meaning that the radiative impact of droplet concentration is greater than its gravitational settling effect.

Haze removal algorithm based on single-images with chromatic properties

Dense fog conditions formed by particles and water droplets in the atmosphere impact the road segmentation accuracy of Advanced Driver Assistance Systems (ADAS) by degrading the contrast and color fidelity of images. Existing road segmentation methods are not suitable for dense haze conditions; darkness, under-estimation, and over-enhancement problems occur after dehazing. This paper proposes a single-image haze removal technique based on hazy state detection and simple priors. Hazy state detection serves to identify the fog in an image by the linear relationship between brightness and saturation in HSV color space. Simple priors both in the background and hazy layers are based on a dichromatic reflection model (DRM) to accommodate different concentrations of fog. We find that according to color consistency and physical properties, fog and highlight appear to share the same chromatic properties. Based on this observation, the DRM can approximate the fog map. The maximum a posteriori formulation can also be utilized to robustly refine the fog map and remove black noise. We employ the fog map to compute atmospheric light and predict transmission rate in order to obtain haze-free images. Our results show that this method outperforms existing methods in regards to both efficiency and dehazing ability.

Performance Limits of FSO Based SAC-OCDMA System Under Weather Conditions

AbstractIn this paper, the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) is investigated in Free Space Optics (FSO) using Zero Cross Correlation (ZCC) codes to evaluate its performance limits in terms of link range. The system is analyzed under clear, haze, moderate fog and dense fog weather conditions. This system has been evaluated numerically and by simulation analysis by maintaining the transmitted power at 10 dBm, for safety reason, according to International Telecommunication Union (ITU) and minimum acceptable BER of10{10}–9. The simulation results shown that the present system can transmit 622 Mbps/1 Gbps up to maximum link range of 1450 m/1100 m and 61 m/54 m under clear and dense fog conditions, respectively.

Performance of Free Space Optical Terrestrial Link under Dense Fog Conditions

Performance of Free Space Optical Terrestrial Link under Dense Fog Conditions

濃霧多発域の太陽光発電への影響の調査

濃霧多発域の太陽光発電への影響の調査

Enhancing the Atmospheric Visibility and Fog Attenuation Using a Controlled FSO Channel

In this letter, two methods for characterizing fog attenuation in terms of atmospheric visibility V in free space optics (FSO) communications are analyzed and compared. Both methods measure the fog attenuation based on V using a charge-coupled device (CCD) camera and a laser-diode at 0.55 μm. The methods are evaluated in a laboratory controlled FSO atmospheric chamber operating at individual wavelengths of 0.83, 1.31, and 1.55 μm using a continuous optical spectrum range 0.6-1.6 μm. The CCD technique shows great accuracy for V <; 50 m and the laser technique for the range 100 m, thus allowing enhancement of the characterization of FSO links in thick and dense fog conditions. The experimental results also show a wavelength dependency for V <; 0.5 km where the attenuation decreases from 52 dB/km at visible wavelengths to 46 dB/km at near infrared wavelengths.

Modeling of Fog and Smoke Attenuation in Free Space Optical Communications Link Under Controlled Laboratory Conditions

This paper theoretically and experimentally investigate the spectrum attenuation of free space optical (FSO) communication systems operating at visible and near infrared (NIR) wavelengths $(0.6 \mu{\rm m} under fog and smoke in a controlled laboratory condition. Fog and smoke are generated and controlled homogeneously along a dedicated atmospheric chamber of length 5.5 m. A new wavelength dependent empirical model is proposed to predict the fog and smoke attenuation operating at visible and NIR wavelengths. Comparison of the new proposed model with the measured continuous attenuation spectrum from visible—NIR in the fog and smoke channels shows a close relationship than the semi-empirical Kim and Kruse fog models. The experimental results also show the selection for the possible appropriate wavelengths from visible—NIR for FSO links to achieve the maximum link span in dense fog conditions.

Designing of high-speed inter-building connectivity by free space optical link with radio frequency backup

This study presents the design of high-speed inter-building connectivity in medical services by free-space optical (FSO) link with wireless backup, which will operate at gigabit rates. The two buildings in medical campus are ∼500 m apart. The FSO link normally uses 1550 nm wavelength but has a radio frequency (RF) link operating at 2.4 GHz as the back-up. In this, 99.999% availability is achieved by combining the optical laser beam with an alternate path RF solution. The laser beam of 1550 nm provides high-bandwidth connectivity in majority of the time, whereas the RF path maintains critical network connectivity during extreme weather events that are detrimental to the FSO link, such as thick fog. Optical wireless links suffer from atmospheric loss mainly because of fog, scintillation and precipitation. The authors investigate here the impact of fog, rain and snow effects and evaluate their performances for the optical propagation through the atmosphere. The wireless back-up link is used only in very dense fog conditions. Hybrid FSO/RF systems have also been examined as a means to provide high-bandwidth point-to-point links in the access network over larger distances.

The electric potential gradient in mist, haze, and fog

The variation of potential gradient in mist, haze, and fog has been studied. During the formation of these hydrometers the potential gradients were found to increase. Large positive potential gradients were observed during dense fog conditions. Possible charge generation mechanisms responsible for these potential gradients during fog formation are discussed.