Humidity contribution to the refractive index structure function C<sup>2</sup>n .

Font, Carlos O.; Chang, Mark P. J. L.; Oh, Eunha; Gilbreath, Charmaine

doi:10.1117/12.665892

“…The variations of temperature in the FSOC channel are functions of atmospheric and geographical parameter variations. This effect is commonly known as optical turbulences or scintillation effects [2]. The atmospheric scintillations can be defined as the changing of light intensities in time and space at the plane of a receiver that detects a signal from a transmitter located at a distance.…”

Section: Introductionmentioning

confidence: 99%

Real‐time measurement of meteorological parameters for estimating low‐altitude atmospheric turbulence strength ( C _n ² )

Raj¹,

Selvi

²

,

Raghavan

³

2014

IET Science, Measurement & Technology

View full text Add to dashboard Cite

The major factor that limits the performance of Free Space Optical Communication is atmospheric turbulence which fluctuates over time in accordance with the variations in local meteorological parameters. Estimating the atmospheric turbulence strength C n 2 with the measurement data becomes significant to find the data rate the system is capable of operating under different outdoor local environmental conditions. Hence, a low cost customised system for continuously measuring the local meteorological data is developed and presented in this study. A field test scintillometer setup is established for a link range of 0.5 km at an altitude of 15.25 m. Specialised sensors are interfaced to the digital architectures to acquire the real-time data corresponding to atmospheric changes. The accuracy and performance of the measurement system are tested against standard instruments and the maximum correlation coefficients of 99.92, 99.63, 99.73 and 99.88% are achieved for wind speed, temperature, relative humidity and pressure, respectively. An experimental model to estimate C n 2 using measured meteorological data is developed and the atmospheric turbulence strength is estimated. The validations of the estimated results with the scintillometer measurement are also analysed. The weather profile and corresponding C n 2 variations at our test field for different seasons in 1 year period are presented and the results are analysed.

show abstract

“…Such a question is prompted by many situations, often associated to the automated collection of data. We are motivated to address this question by our experimental field work to record the behaviour of the strength of optical turbulence parameter, C 2 n , over time intervals of several weeks, under different climate conditions [1,2,3,4,5]. The data of interest to us are path integrated measures of C 2 n measured across the visible to near infrared region.…”

Section: Introductionmentioning

confidence: 99%

Turbulence time series data hole filling using Karhunen-Lòeve and ARIMA methods

Chang¹,

Nazari²,

Font³

et al. 2007

J. Phys.: Conf. Ser.

0

View full text Add to dashboard Cite

Measurements of optical turbulence time series data using unattended instruments over long time intervals inevitably lead to data drop-outs or degraded signals. We present a comparison of methods using both Principal Component Analysis, which is also known as the Karhunen-Loève decomposition, and ARIMA that seek to correct for these eventinduced and mechanically-induced signal drop-outs and degradations. We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition. The data studied are optical turbulence parameter time series from a commercial long path length optical anemometer/scintillometer, measured over several hundred metres in outdoor environments.

show abstract

“…Such a question is prompted by many situations, often associated to the automated collection of data. We are motivated to address this question by our experimental field work to record the behaviour of the strength of optical turbulence parameter, C 2 n , over time intervals of several weeks, under different climate conditions [1,2,3,4,5]. The data of interest to us are path integrated measures of C 2 n measured across the visible to near infrared region.…”

Section: Introductionmentioning

confidence: 99%

Turbulence Time Series Data Hole Filling using Karhunen-Loeve and ARIMA methods

Chang¹,

Nazari²,

Font³

et al. 2007

0

View full text Add to dashboard Cite

Measurements of optical turbulence time series data using unattended instruments over long time intervals inevitably lead to data drop-outs or degraded signals. We present a comparison of methods using both Principal Component Analysis, which is also known as the Karhunen-Loève decomposition, and ARIMA that seek to correct for these eventinduced and mechanically-induced signal drop-outs and degradations. We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition. The data studied are optical turbulence parameter time series from a commercial long path length optical anemometer/scintillometer, measured over several hundred metres in outdoor environments.

show abstract

Humidity contribution to the refractive index structure function C²n .

Cited by 10 publications

References 8 publications

Real‐time measurement of meteorological parameters for estimating low‐altitude atmospheric turbulence strength ( C _n ² )

Real‐time measurement of meteorological parameters for estimating low‐altitude atmospheric turbulence strength ( C _n ² )

Turbulence time series data hole filling using Karhunen-Lòeve and ARIMA methods

Turbulence Time Series Data Hole Filling using Karhunen-Loeve and ARIMA methods

Contact Info

Product

Resources

About

Humidity contribution to the refractive index structure function C2n .

Cited by 10 publications

References 8 publications

Real‐time measurement of meteorological parameters for estimating low‐altitude atmospheric turbulence strength ( C n 2 )

Real‐time measurement of meteorological parameters for estimating low‐altitude atmospheric turbulence strength ( C n 2 )

Turbulence time series data hole filling using Karhunen-Lòeve and ARIMA methods

Turbulence Time Series Data Hole Filling using Karhunen-Loeve and ARIMA methods

Contact Info

Product

Resources

About

Humidity contribution to the refractive index structure function C²n .

Real‐time measurement of meteorological parameters for estimating low‐altitude atmospheric turbulence strength ( C _n ² )

Real‐time measurement of meteorological parameters for estimating low‐altitude atmospheric turbulence strength ( C _n ² )