Roberto J. Acosta and James A. Nessel

Glenn Research Center, Cleveland, Ohio

Jacquelynne R. Morse

Arizona State University, Tempe, Arizona

Path Length Fluctuations Derived From 

Site Testing Interferometer Data

NASA/TM—2010-216355

July 2010
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Roberto J. Acosta and James A. Nessel

Glenn Research Center, Cleveland, Ohio

Jacquelynne R. Morse

Arizona State University, Tempe, Arizona

Path Length Fluctuations Derived From 

Site Testing Interferometer Data

NASA/TM—2010-216355

July 2010

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135
Available from

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Level of Review: This material has been technically reviewed by technical management. 
Path Length Fluctuations Derived From 

Site Testing Interferometer Data 

Roberto J. Acosta and James A. Nessel 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Jacquelynne R. Morse 

Arizona State University 

Tempe, Arizona 85287 

Abstract 

To evaluate possible sites for NASA’s proposed Ka-band antenna array, the NASA Glenn Research 

Center has constructed atmospheric phase monitors (APM) which directly measure the tropospheric phase 

stability. These instruments observe an unmodulated 20.2 GHz beacon signal broadcast from a 

geostationary satellite (Anik F2) and measure the phase difference between the signals received by the 

two antennas. Two APM’s have been deployed, one at the NASA Deep Space Network (DSN) Tracking 

Complex in Goldstone, California, and the other at the NASA White Sands Complex, in Las Cruces, New 

Mexico. Two station-years of atmospheric phase fluctuation data have been collected at Goldstone since 

operations commenced in May 2007 and 0.5 station-years of data have been collected at White Sands 

since operations began February 2009. With identical instruments operating simultaneously, we can 

directly compare the phase stability at the two sites. Phase stability is analyzed statistically in terms of the 

root-mean-square (rms) of the tropospheric path length fluctuations over 10 min blocks. Correlation 

between surface wind speed and relative humidity with interferometer phase are discussed. For 2 years, 

the path length fluctuations at the DSN site in Goldstone, California, have been better than 757 μm (with 

reference to a 300 m baseline and to Zenith) for 90 percent of the time. For the 6 months of data collected 

at White Sands, New Mexico, the path length fluctuations have been better than 830 μm (with reference 

to a 300 m baseline and to Zenith) for 90 percent of the time. This type of data analysis, as well as many 

other site quality characteristics (e.g., rain attenuation, infrastructure, etc.), will be used to determine the 

suitability of both sites for NASA’s future communication services at Ka-band using an array of antennas. 

1.0 Introduction 

As NASA progresses into the 21st century, NASA’s communications network systems (e.g., deep 

space and near earth) are expected to transition into the use of the Ka-band spectrum. These network 

systems operating at Ka-band, will be required to provide services with a system availability higher than 

99 percent (currently at ~ 90 percent) and gigabyte data rates (currently ~ Megabyte rates) for human 

exploration. If all proceeds as planned, the aging monolithic 70-m antennas of the Deep Space Network 

(DSN) are expected to be replaced (~ 2020) with a ground-based array of smaller aperture antennas (e.g., 

34 m or possibly 12 m). The new system will provide the flexibility and reliability necessary for the 

demands of NASA’s upcoming mission roster, reduce single-point failures, and allow electronic steering 

and multi-beam operational capabilities. However, the atmospheric phase stability of a particular site 

must be known before implementation of a ground-based array can proceed. The statistical knowledge of 

the atmospheric fluctuations will lead to mitigation techniques to further improve system margin and 

reduce cost. 

Atmospheric phase instability (decorrelation of a propagating plane wave phase front) arises because 

earth’s upper atmosphere (troposphere) contains large amounts of inhomogeneous distributions of water 

vapor exposed to turbulent air flow conditions. This property induces variations in the precipitable water 

NASA/TM—2010-216355 1 
vapor content that changes the refractivity of the medium, which directly leads to variations in the 

effective electrical path length of an electromagnetic wave propagating through this layer of the 

atmosphere (See Fig. 1). Such variations are seen as “randomly modulated phase noise” by radio arrays 

and will inherently degrade the performance of widely distributed ground-based antenna systems. A twoelement interferometer is the optimal system to directly measure atmospheric phase stability at any given 

site (Ref. 1). 

NASA Glenn Research Center, in collaboration with the Jet Propulsion Laboratory and Goddard 

Space Flight Center, has constructed and deployed two APM’s (two-element interferometer). The first 

APM was deployed at Goldstone, California, and we have collected over 2 years of phase fluctuation 

measurements (operation started May 2007). The second APM was deployed at White Sands, New 

Mexico, where we have collected over 6 months of data (operation started February 2009). The results of 

this data analysis will directly determine the necessary system design parameters and identify possible 

mitigation techniques to optimally operate a Ka-band array system at both locations. 

NASA/TM—2010-216355 2 
2.0 Field Deployment and Measured Performance 

Two APM’s have been constructed (Ref. 2). The first interferometer was deployed in May 2007 at 

3408 ft altitude on an east-west baseline of 252 m at the Goldstone DSN Complex, near Barstow, 

California. A similar interferometer was installed at 4821 ft on a north-south baseline of 208 m at The 

White Sands Tracking and Data Relay Satellite (TDRS) Complex, near Las Cruces, New Mexico. Both 

interferometers receive the Anik F2 20.2 GHz beacon signal. A signal-to-noise ratio (SNR) of 

approximately 80 dB·Hz was measured at both locations at the beginning of operation. Before 

deployment, the instrument performance was evaluated in the laboratory environment (no atmospheric 

contributions) and constantly showed a root-mean-square (rms) of 1.5° over 600-s integration intervals. 

A sample time series of measured interferometer phase fluctuations observed from February 5 to 9, 

2009 by the White Sands Interferometer is depicted in Figure 2. These time series illustrate a typical 

instrument’s operational performance. 

NASA/TM—2010-216355 3 
In the upper portion of Figure 2, we can see the large phase swings (variations) that are due mainly to 

satellite motion. The lower portion of Figure 2 depicts the corresponding time series of the rms of the 

phase fluctuations computed in 600-s intervals after calibration of the phase data has been performed (see 

Section 3.0). Notice that most of the energy (proportional to the rms) are above the system phase noise of 

1.5° rms, indicating the presence of atmospheric fluctuations on scales much shorter than 600-s. What is 

also evident is the presence of a diurnal variation of the phase fluctuations (rms). This is an expected 

result since the atmosphere is quieter at night than it is during the day. 

With identical instruments operating simultaneously, we can directly compare the phase stability at 

Goldstone and White Sands. With only 6 months of data collected simultaneously, it is too premature to 

draw firm conclusions about the site differences, which will require measurements extending over several 

seasons and even several years. The White Sands and Goldstone interferometers both receive the 

20.2 GHz satellite signal (ANIK F2) at two different elevation angles (51.8° and 48.5° respectively) and 

at two different interferometer baselines (208 and 252 m, respectively) and it is necessary to extrapolate 

the measured rms results to an observation angle of zenith (90°) and to a common baseline of 300 m 

(Ref. 1). A preliminary look at the data results for the month of February 2009, from simultaneous site 

testing, is presented in Figure 3. This preliminary assessment of the data indicates that the daily mean rms

of the path length fluctuations (directly proportional to the site phase stability) at White Sands is slightly 

better than at Goldstone for this particular month. 

3.0 Data Processing 

Before the data can be statistically analyzed, the phase fluctuations induced by the atmosphere must 

be isolated from those introduced by the system (i.e., motion of the satellite, slow varying system drift, 

and random system thermal noise). The foundation for (and validation of) this calibration procedure can 

be found in (Ref. 3), and a summary of the steps is provided below. 

First, the recorded data (1-s) is unwrapped (the interferometer records relative phase within a ± 180° 

range), so that a continuous differential phase curve is established (see Fig. 2, upper). The 24-hr data is 

then divided into 144 blocks of 600 s (10 min) intervals. Blocks containing bad data (e.g., data recorded 

during maintenance visits, system-induced phase jumps, etc.) are removed. Within each good 10 min 

block, a 2nd order polynomial is fit to the data using a least mean square approach and subtracted. The 

final result of this process is the phase fluctuations due solely to the atmosphere and system noise over 

10 min intervals in a given 24-hr period. Figure 4 shows the corresponding 1-s phase fluctuations after the 

satellite motion was removed for the data collected from the February 5 to 9, 2009 (compare with Fig. 2, 

upper). 

NASA/TM—2010-216355 4 
4.0 Statistical Results 

The overall cumulative distributions derived from all the measured phase fluctuations (rms) at the 

two sites are presented in Figure 5. The Goldstone cumulative distribution functions (CDF) include 

22 months of data while the White Sands distribution only includes 6 months of data. The CDF is derived 

from a histogram of observations that included the rms (obtained by averaging the 1-s measured phase 

over 600-s). 

The distributions are summaries for line-of-sight first-order statistics. The 90th percentile for 

Goldstone is about 22° and for White Sands is about 19° (6 months). 

If the 90 percent rms phase fluctuations at line-of-sight are converted to path length and referenced to 

zenith we obtain 615 μm for White Sands and 680 μm for Goldstone. These results seem to be consistent 

from the results obtained during simultaneous site testing discussed in Section II. However, when the 

fluctuations are extrapolated to a common baseline (i.e., 300 m), we observe that in actuality, the 

Goldstone site (757 μm) slightly outperforms the White Sands site (830 μm). This result is a more direct 

comparison of the characteristics of the two locations. 

In order to make an assessment of the seasonal variations (summer versus winter, etc.) we derived the 

monthly median phase rms for both sites. The derived statistics are presented in Figure 6. The results of 

the seasonal variation at Goldstone are as expected. The summer months (June to September) tend to 

promote higher phase fluctuation rms than winter months (November to February). In the summer months 

the atmosphere is more turbulent (high heat, more storms, abundance of clouds, high humidity) than in 

the calm winter months (low heat, little cloud coverage, lower humidity). These are expected results that 

have been seen by other site test interferometers at sites around the world (Refs. 1 and 4). 

The site comparisons done by using the seasonal variations statistics above cannot be fully analyzed 

at this point since the White Sands site does not have enough data for evaluating all the seasonal 

variations. 

In order to statistically evaluate the hour-to-hour variations (diurnal) at each site we derived the 

hourly 25th, 50th, 75th and 90th percentiles from the measured phase fluctuation (rms) at both sites. The 

statistical results are presented in Figure 7. From these results we can see a clear variation between night 

and day. This general result is consistent with other interferometer measurements taken at the Very Large 

Array (VLA) (Ref. 4) and indicates similar atmospheric patterns. The results so far indicate that the 

afternoons in Goldstone are slightly better than those of White Sands. During the night the performance at 

both sites was about the same. 

NASA/TM—2010-216355 5 
NASA/TM—2010-216355 6 
NASA/TM—2010-216355 7 
5.0 Phase Fluctuations and Ground Weather Statistics 

Simultaneous measurements (February 5 to 9, 2009) of the phase fluctuations (rms), wind speed, and 

relative humidity for the White Sands Site is presented in Figure 8. Notice that there is a weak correlation 

between phase fluctuations and wind speed. This is typical to both sites. 

Relative humidity appears to be the best (not a strong) indicator of the presence of water vapor 

molecules close to the antenna. The diurnal variation (middle portion of Fig. 8) of the wind speed 

observed is typical for both sites, with stronger winds in the afternoons. The relative humidity (lower 

portion of Fig. 8) shows some degree of diurnal variation, as well, increasing drastically on February 9, 

with the onset of a rain event. Further analysis must be performed to ascertain the degree of this 

correlation. 

NASA/TM—2010-216355 8 
6.0 Conclusive Remarks and Future Work 

From the results of the first 2 years of data collection in Goldstone, California, and 6 months at White 

Sands, New Mexico, the following conclusions can be made regarding the phase stability of the site and 

its potential to support a widely distributed ground-based array: 

NASA/TM—2010-216355 9 
NASA/TM—2010-216355 10 

• Phase fluctuations (rms) tend to be the worst during the summer months, best during winter 

months, and generally worse during the day than during the evening. This phenomenon is likely 

due to the decreased level of atmospheric turbulence at night, and especially in the wintertime. 

• Though surface meteorological measurements are not proven to be accurate predictors of weather 

patterns aloft, relative humidity appears to provide the best level of correlation between observed 

phase fluctuations and surface data. Wind speed and other surface measurements do not appear to 

show any significant correlation. 

A statistically meaningful comparison between the two sites is not possible with the amount of data 

collected at White Sands. A more comprehensive comparison will be done at the end of 1 year of 

simultaneous data collection. 

References 

1. Thompson, A.R., Moran, J.M. and Swenson. G.W., Interferometer and Synthesis in Radio 

Astronomy, 2nd edition, John Wiley & Sons, 2001. 

2. R.J. Acosta, B. Frantz, J.A. Nessel, D.D. Morabito, “Goldstone Site Test Interferometer,” 13th Ka 

and Broadband Communications Conference, Turin, Italy, Sep. 24–26, 2007. 

3. R.J. Acosta, J.A. Nessel, D.D. Morabito, “Data Processing for Atmospheric Phase Interferometers,” 

14th Ka and Broadband Communications Conference, Matera, Italy, Sep. 

4. B. Butler and K. Desai, “Phase Fluctuations at The VLA Derived From One Year of Site Testing 

Interferometer Data,” VLA Test Memo. No. 222, National Radio Astronomy Observatory, Oct. 1999. 
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13. SUPPLEMENTARY NOTES

14. ABSTRACT

To evaluate possible sites for NASA’s proposed Ka-band antenna array, the NASA Glenn Research Center has constructed atmospheric 

phase monitors (APM) which directly measure the tropospheric phase stability. These instruments observe an unmodulated 20.2 GHz

beacon signal broadcast from a geostationary satellite (Anik F2) and measure the phase difference between the signals received by the two 

antennas. Two APM’s have been deployed, one at the NASA Deep Space Network (DSN) Tracking Complex in Goldstone, California, and

the other at the NASA White Sands Complex, in Las Cruces, New Mexico. Two station-years of atmospheric phase fluctuation data have 

been collected at Goldstone since operations commenced in May 2007 and 0.5 station-years of data have been collected at White Sands 

since operations began February 2009. With identical instruments operating simultaneously, we can directly compare the phase stability at 

the two sites. Phase stability is analyzed statistically in terms of the root-mean-square (rms) of the tropospheric path length fluctuations over 

10 min blocks. Correlation between surface wind speed and relative humidity with interferometer phase are discussed. For 2 years, the path 

length fluctuations at the DSN site in Goldstone, California, have been better than 757 μm (with reference to a 300 m baseline and to Zenith) 

for 90 percent of the time. For the 6 months of data collected at White Sands, New Mexico, the path length fluctuations have been better 

than 830 μm (with reference to a 300 m baseline and to Zenith) for 90 percent of the time. This type of data analysis, as well as many other 

site quality characteristics (e.g., rain attenuation, infrastructure, etc.), will be used to determine the suitability of both sites for NASA’s 

future communication services at Ka-band using an array of antennas. 

15. SUBJECT TERMS

Antenna arrays; Deep space network; Directivity; Phase noise; Atmosphere 

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