RMPC-Based Visual Servoing for Trajectory Tracking of Quadrotor UAVs With Visibility Constraints

Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebased visual servoing(IBVS) method, a virtual camera is constructed to express image moments of the tracking target.

High-visibility ghost imaging with phase-controlled discrete classical light sources

We take phase modulation to create discrete phase-controlled sources and realize the super-bunching effect by a phasecorrelated method. From theoretical and numerical simulations, we find the space translation invariance of the bunching effect is a key point for the ghost imaging realization. Experimentally, we create the orderly phase-correlated discrete sources which can realize high-visibility second-order ghost imaging than the result with chaotic sources. Moreover, some factors affecting the visibility of ghost image are discussed in detail.

Newspaper Visibility of Members of Parliament in Kenya

This research investigates variables that predicted news coverage of 212 members of parliament （MPs） in Kenya by four national newspapers in 2009. The 10 variables examined are： ordinary MP, cabinet minister, powerful ministry, parliamentary committee chairmanship, seniority, big tribe identity, major party affiliation, presidential ambition, commenting on contentious issues, and criticizing government. Findings indicate that commenting on contentious issues, criticizing government, cabinet minister, ordinary MP, powerful ministry, and seniority significantly predicted visibility of the parliamentarians in newspaper news. However, a multiple regression analysis shows that the strongest predictors are commenting on contentious issues, cabinet minister, criticizing government, and big tribe identity. While commenting on controversial issues was the strongest predictor, major party identification and committee leadership were found not to predict MPs＇ visibility.

Visibility的航空遥感相机自动焦面检测方法

为了解决航空遥感相机自动焦面检测的问题,提出了一种利用空间滤波测速(SFV)原理进行航空遥感相机自动焦面检测的方法。首先,在焦面检测过程中,采集线阵CCD输出图像的Visibility值,利用SFV信号的Visibility值与离焦量之间的关系,通过搜寻SFV信号Visibility最大值找出最佳的成像焦面位置;其次,对空间滤波测速原理及Visibility与离焦量的关系进行了介绍;最后,对设计的实验装置在5～53.2 mm/s的典型像移速度下进行了20次焦面检测,结果表明最大测量误差均方值为46.25μm,小于航空遥感相机光学系统的检焦误差宽容度(76.8μm),能够满足航空遥感相机的自动焦面检测精度要求。

Analysis of the Low Visibility and Air Pollution Process in Shanghai during December 14-15,2006

A process of continuous heavy fog and air pollution occurred in the eastern China including Shanghai,Nanjing,Hefei,etc.during December 14-15,2006.Based on the GTS synoptic data,sounding data and NCEP/NCAR reanalyzed dataset,from the aspects of the weather situation,vapor condition,dynamic factor,temperature stratification,and air quality the contribution of foggy conditions and air pollution in the fog process to continuous heavy fog were analyzed.The results showed that 1 000 hPa fluid flux divergence (FD),vertical velocity (ω) and divergence difference(△DIV) between 1 000 hPa and 500 hPa had not significantly correlative with visibility,while relative humidity (RH) near ground had significant negative correlative,temperature lapse rate (γ) near ground had significant positive correlation,therefore,RH≥85%,γ<0.2 ℃/100m could be regarded as the necessary conditions of fog formation.In addition,the lowest air visibility had intense negative correlation with daily averaged API in the meantime,'API rising up to 150' could be an important criterion of fog formation in Shanghai Hongqiao international airport.

Comparison of Visibility Measurements over Horizontal Path by Micro-pulsed Lidar and Visibility Meter

As a powerful tool to scan the atmosphere, the I idar can derive visibility values by directly collecting the backscattering laser light from the atmosphere. Simultaneous measurements of atmospheric visibility by Micro-pulsed lidar （MPL） and a commercial visibility meter （VM） NQ-1 have been performed to evaluate the feasibility of the MPL system designed by the Ocean Remote Sensing Laboratory （ORSL） of the Ocean University of China （OUC） from October 21 2005 to November 21 2005 in the Shilaoren Sightseeing Garden on the Qingdao coast. All the 880 data samples obtained by the two instruments have high correlation coefficients （up to 0.86）, which indicates it is feasible to utilize MPL to measure atmospheric visibility.

Characteristics and Application of Self-Developed Fast-Response Visibility Meter

The measuring principle and development process of self-developed fast-response visibility meter was introduced,and the comparative test with FD12 visibility meter was carried out.Meanwhile,by using the observational data from automatic weather station from October 2004 to March 2005,the evolution characteristics of visibility and its relationship with relative humidity,wind speed and temperature in autumn and winter in northern Beijing were discussed.The results showed that self-developed visibility meter could reflect the variation trend of visibility,with good comparison results,and could be used to measure visibility,while its frequency response was over 1 Hz,meeting the fast-response requirement of atmospheric visibility measurement and relevant detection.In northern Beijing,atmospheric visibility was significantly negatively correlated with relative humidity but significantly positively correlated with wind speed,while temperature could affect visibility indirectly by changing relative humidity and atmospheric stability.Gale and heavy fog had important effects on visibility.

Rethinking on Translator's Invisibility and Visibility

Translator’s Invisibility is Lawrence Venuti’s most famous book.In this book we can conclude his translation theory:translators should be invisible(transparent)or visible in his translation.We will analyze in his opinion which kind of translation is perfect to readers,and how should the translator be visible in his translation by comparing the theories of Friedrich Schleiermacher and Norman Shapiro.Finally we can get a good translator should use foreignizing translation in order to be visible in his translation.

Quantitative relationship between visibility and mass concentration of PM2.5 in Beijing

The pollution of particulate matter less than 2.5μm （PM2.5） is a serious environmental problem in Beijing. The annual average concentration of PM2.5 in 2001 from seasonal monitor results was more than 6 times that of the U,S, national ambient air quality standards proposed by U.S. EPA. The major contributors to mass of PM2.5 were organics, crustal elements and sulfate. The chemical composition of PM2.5 varied largely with season, but was similar at different monitor stations in the same season. The fine particles （PM2.5） cause atmospheric visibility deterioration through light extinction, The mass concentrations of PM2.5 were anti-correlated to the visibility, the best fits between atmospheric visibility and the mass concentrations of PM2.5 were somehow different： power in spring, exponential in summer, logarithmic in autumn, power or exponential in winter. As in each season the meteorological parameters such as air temperature and relative humidity change from day to day, probably the reason of above correlations between PM2.5 and visibility obtained at different seasons come from the differences in chemical compositions of PM2.5.

Daily Visibility and Hospital Admission in Shanghai, China

Objective The study is to investigate the associations between visibility, major air pollutants and daily counts of hospital admission in Shanghai, China. Methods Daily data on hospital admission, visibility, and air pollution during 2005‐2008 were obtained from the Shanghai Insurance Bureau （SHIB）, Shanghai Meteorological Bureau, and Shanghai Environmental Monitoring Center, respectively. The generalized additive model （GAM） with penalized splines was used to examine the associations between daily visibility and hospital admission. Results Among various pollutants, PM 2.5 showed strongest correlation with visibility. Decreased visibility was significantly associated with increased risk of hospital admission in Shanghai. An inter‐quartile range decrease in the 2‐day （L01） moving average of visibility corresponded to 3.66% （95%CI： 1.02%, 6.31%）, 4.06% （95%CI： 0.84%, 7.27%）, and 4.32% （95%CI： 1.67%, 6.97%） increase of total, cardiovascular, and respiratory hospitalizations, respectively. Conclusion Our analyses provide the first piece of evidence in China, demonstrating that decreased visibility has an effect on hospital admission, and this finding strengthens the rationale for further limiting air pollution levels in Shanghai.

Effects of Additional HONO Sources on Visibility over the North China Plain

The objective of the present study was to better understand the impacts of the additional sources of nitrous acid （HONO） on visibility, which is an aspect not considered in current air quality models. Simulations of HONO contributions to visibility over the North China Plain （NCP） during August 2007 using the fully coupled Weather Research and Forecasting/Chemistry （WRF/Chem） model were performed, including three additional HONO sources： （1） the reaction of photo-excited nitrogen dioxide （NO~） with water vapor; （2） the NO2 heterogeneous reaction on aerosol surfaces; and （3） HONO emissions. The model generally reproduced the spatial patterns and diurnal variations of visibility over the NCP well. When the additional HONO sources were included in the simulations, the visibility was occasionally decreased by 20%-30% （3-4 km） in local urban areas of the NCP. Monthly-mean concentrations of NO3, NH＋, SO]- and PM2.5 were increased by 20%-52% （3-11μg m-3）, 10%-38%, 6%-10%, and 6%-11% （9-17 μg m-3）, respectively; and in urban areas, monthly-mean accumulation- mode number concentrations （AMNC） and surface concentrations of aerosols were enhanced by 15%-20% and 10%-20%, respectively. Overall, the results suggest that increases in concentrations of PM2.5, its hydrophilic components, and AMNC, are key factors for visibility degradation. A proposed conceptual model for the impacts of additional HONO sources on visibility also suggests that visibility estimation should consider the heterogeneous reaction on aerosol surfaces and the enhanced atmospheric oxidation capacity due to additional HONO sources, especially in areas with high mass concentrations of NOx and aerosols.

Visibility in differential phase-contrast imaging with partial coherence source

This paper gives theoretical analysis of visibility of fringes, which is influenced by distances, temporal and spatial coherence of source, in hard x-ray differential phase-contrast imaging with microfocus x-ray source. According to the character of longitudinal periodicity of the interferogram, the setup is insensitive to mechanical drift and vibrations. The effect of temporal coherence of x-ray source is investigated and its related bandwidth is derived. Based on the theory of partially coherent light, it shows that the requirement for the spatial coherence of x-ray source is not strict and can be met by the general microfocus x-ray tube for x-ray differential phase-contrast imaging.

Trends in sunshine duration and atmospheric visibility in the Yunnan-Guizhou Plateau,1961-2005

Using the observed data from 184 stations over the Yunnan-Guizhou Plateau （YGP） from 1961 to 2005, the long-term trends in sunshine duration, cloud amount, dry visibility （Vd）, dry extinction, and water vapor over the YGP are analyzed. The results show that 85% of the stations recorded shortening annual sunshine duration, with the decrease rates between -12.2 and -173.7 h/10yr. Results of Mann-Kendall tests indicate that, among the stations with decreasing sunshine duration, 63.7% of them experienced an abrupt change that started in the 1970s and peaked in the 1980s. This decreasing trend has reversed in the early years of the 21st century. The cloud cover and water vapor content in the mid and lower levels over the YGP had no obvious changes during the study period. The annual averages of Vd declined from 34 km in the 1960s to 27 km at present. The annual mean dry extinction coefficient trended upward, from 0.176 to 0.190, on the YGP from 1980 to 2005. Analyses of cloud cover, water vapor, atmospheric visibility, and dry extinction coefficient revealed that emitted tropospheric aerosols （including air pollutants） resulting from increased energy consumption over the YGP could be a major Factor influencing the reductions of sunshine duration and atmospheric visibility.

Detection and recognition of LPI radar signals using visibility graphs

The detection and recognition of radar signals play a critical role in the maintenance of future electronic warfare(EW).So far,however,there are still problems with signal detection and recognition,especially in the low probability of intercept(LPI)radar.This paper explores the usefulness of such an algorithm in the scenario of LPI radar signal detection and recognition based on visibility graphs(VG).More network and feature information can be extracted in the VG two-dimensional space,this algorithm can solve the problem of signal recognition using the autocorrelation function.Wavelet denoising processing is introduced into the signal to be tested,and the denoised signal is converted to the VG domain.Then,the signal detection is performed by using the constant false alarm of the VG average degree.Next,weight the converted graph.Finally,perform feature extraction on the weighted image,and use the feature to complete the recognition.It is testified that the proposed algorithm offers significant improvements,such as robustness to noise,and the detection and recognition accuracy,over the recent researches.

Specific Emitter Identification Based on Visibility Graph Entropy

The specific emitter identification （SEI） technique some external feature measurements of the signal. determines the unique emitter of a given signal by using It has recently attracted a great deal of attention because many applications can benefit from it. This work addresses the SEI problem using two methods, namely, the normalized visibility graph entropy （NVGE） and the normalized horizontal visibility graph entropy （NHVGE） based on treating emitters as nonlinear dynamical systems. Firstly, the visibility graph （VG） and the horizontal visibility graph （HVG） are used to convert the instantaneous amplitude, phase and frequency of received signals into graphs. Then, based on the information captured by the VG and the HVG, the normalized Shannon entropy （NSE） calculated from the corresponding degree distributions are utilized as the rf fingerprint. Finally, four emitters from the same manufacturer are utilized to evaluate the performance of the two methods. Experimental results demonstrate that both the NHVGE-based method and NVGE-based method are quite effective and they perform much better than the method based on the normalized permutation entropy （NPE） in the case of a small amount of data. The NVGE-based method performs better than the NHVGE-based method since the VG can extract more information than the HVG does. Moreover, our methods do not distinguish between the transient signal and the steady-state signal, making it practical.

A new GIS-compatible methodology for visibility analysis in digital surface models of earth sites

As a GIS tool,visibility analysis is used in many areas to evaluate both visible and non-visible places.Visibility analysis builds on a digital surface model describing the terrain morphology,including the position and shapes of all objects that can sometimes act as visibility barriers.However,some barriers,for example vegetation,may be permeable to a certain degree.Despite extensive research and use of visibility analysis in different areas,standard GIS tools do not take permeability into account.This article presents a new method to calculate visibility through partly permeable obstacles.The method is based on a quasi-Monte Carlo simulation with 100 iterations of visibility calculation.Each iteration result represents 1%of vegetation permeability,which can thus range from 1%to 100%visibility behind vegetation obstacles.The main advantage of the method is greater accuracy of visibility results and easy implementation on any GIS software.The incorporation of the proposed method in GIS software would facilitate work in many fields,such as architecture,archaeology,radio communication,and the military.

Retrieval of Atmospheric Horizontal Visibility by Statistical Regression from NOAA/AVHRR Satellite Data

Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated. Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression （PCR） method. A sample of retrieved visibility distribution was discussed with a sea fog process. The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.9% confidence level by statistical test. The rate of successful retrieval is 94.98% of the 458 cases during 2001 2002. The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.

Prediction of visibility in the Arctic based on dynamic Bayesian network analysis

With the accelerated warming of the world,the safety and use of Arctic passages is receiving more attention.Predicting visibility in the Arctic has been a hot topic in recent years because of navigation risks and opening of ice-free northern passages.Numerical weather prediction and statistical prediction are two methods for predicting visibility.As microphysical parameterization schemes for visibility are so sophisticated,visibility prediction using numerical weather prediction models includes large uncertainties.With the development of artificial intelligence,statistical prediction methods have received increasing attention.In this study,we constructed a statistical model with a physical basis,to predict visibility in the Arctic based on a dynamic Bayesian network,and tested visibility prediction over a 1°×1°grid area averaged daily.The results show that the mean relative error of the predicted visibility from the dynamic Bayesian network is approximately 14.6%compared with the inferred visibility from the artificial neural network.However,dynamic Bayesian network can predict visibility for only 3 days.Moreover,with an increase in predicted area and period,the uncertainty of the predicted visibility becomes larger.At the same time,the accuracy of the predicted visibility is positively correlated with the time period of the input evidence data.It is concluded that using a dynamic Bayesian network to predict visibility can be useful over Arctic regions for projected climatic changes.

A Correction Algorithm for Atmospheric Visibility Based on Fog Droplet Size Data Obtained on a Moving Ship During 2016 Arctic Cruise

In this study, we measured the droplet size distribution(DSD) and visibility of sea fog using a fog droplet spectrometer and visibility meter, respectively, during the July 23-August 3 and August 22-September 13 periods of the 2016 Chinese National Arctic Research Expedition. We calculated the visibility using the Mie theory and the DSD data and then compared the calculated with the observed visibility. The comparison shows that the deviations in the calculated visibility caused by DSD data sampling errors cannot be ignored. During navigation, wind and ship speeds tended to push or pull the sampled air and cause turbulence pulsation, which influenced the sampling of the fog droplet spectrometer. This influence is weak when the liquid water content(LWC) is high but becomes stronger as the LWC decreases. Taking the sailing speed and heading into consideration, the wind speed component parallel and perpendicular to the air inlet of the fog droplet spectrometer exhibit different laws in the deviation. By performing a fitting analysis of the calculated and observed visibilities under different wind speeds and wind directions, here, we present two sets of correction coefficients for the two wind-speed components and a method for correcting the calculated visibility. This correction method shows excellent results.

Automatic radar antenna scan type recognition based on limited penetrable visibility graph

To address the problem of the weak anti-noise and macro-trend extraction abilities of the current methods for identifying radar antenna scan type,a recognition method for radar antenna scan types based on limited penetrable visibility graph(LPVG)is proposed.Firstly,seven types of radar antenna scans are analyzed,which include the circular scan,sector scan,helical scan,raster scan,conical scan,electromechanical hybrid scan and two-dimensional electronic scan.Then,the time series of the pulse amplitude in the radar reconnaissance receiver is converted into an LPVG network,and the feature parameters are extracted.Finally,the recognition result is obtained by using a support vector machine(SVM)classifier.The experimental results show that the recognition accuracy and noise resistance of this new method are improved,where the average recognition accuracy for radar antenna type is at least 90%when the signalto-noise ratio(SNR)is 5 dB and above.