NTIA Report 97-337

Field Strength Measurements

of DGPS and FAA Beacons in the

285- to 325-kHz Band

J.R. Hoffman

J.J. Lemmon

R.L. Ketchum

U.S. DEPARTMENT OF COMMERCE

William M. Daley, Secretary

Larry Irving, Assistant Secretary

for Communications and Information

June 1997

iii

PRODUCT DISCLAIMER

Certain commercial equipment, instruments, or materials are identified in this paper to specify adequately

the technical aspects of the reported results. In no case does such identification imply recommendation or

endorsement by the National Telecommunications and Information Administration, nor does it imply that

the material or equipment identified is the best available for the purpose. 

All Maps in this report were produced with MapExpert software from DeLorne Mapping. TM

CONTENTS

Page

v

PRODUCT DISCLAIMER ........................................ iii

FIGURES .................................................. vii

TABLES ................................................... xi

ABSTRACT .................................................. 1

1. PURPOSE ............................................... 1

2. STRATEGY .............................................. 1

3. MEASUREMENT SYSTEM ................................... 5

4. MEASUREMENT PROCEDURE ................................ 8

5. DATA PROCESSING ........................................ 11

6. ANALYSIS .............................................. 11

7. MEASUREMENT RESULTS ................................... 12

8. COMPARISON OF MEASUREMENTS WITH MODELS ................ 15

9. CONCLUSIONS ........................................... 17

10. ACKNOWLEDGMENT ...................................... 39

11. REFERENCES ............................................ 39

APPENDIX A: SIGNAL FIELD STRENGTH COMPUTATIONS .............. 41

APPENDIX B: NOISE FIGURE AND SENSITIVITY COMPUTATIONS ........ 43

APPENDIX C: CORRECTION FACTORS FOR THE EATON 94592-1 ANTENNA . . 45

APPENDIX D: COMPUTATION OF EXPECTED ELECTIC FIELD STRENGTH ... 47

FIGURES

Page

vii

Figure 1. Transmitter at Aransas Pass, Texas .......................... 3

Figure 2. Measurement route at Aransas Pass, Texas ..................... 3

Figure 3. Measurement route between Aransas Pass, Texas and 

Mobile Point, Alabama .................................. 4

Figure 4. Transmitter at Mobile Point, Alabama ........................ 4

Figure 5. Measurement route at Mobile Point, Alabama ................... 5

Figure 6. Measurement routes for Cape Mendocino, California;

Point Blunt, California; and Pigeon Point, California ............... 6

Figure 7. Measurement route at Fort Stevens, Oregon ..................... 7

Figure 8. Measurement route for the FAA beacon ....................... 7

Figure 9. Block diagram of the measurement system ...................... 8

Figure 10. Signal strength vs. distance for the beacon at Aransas Pass, Texas ...... 18

Figure 11. Signal strength vs. distance for the beacon at Galveston, Texas ........ 18

Figure 12. Signal strength vs. distance for the beacon at English Turn, Louisiana ... 19

Figure 13. Signal strength vs. distance for the beacon at Mobile Point, Alabama .... 19

Figure 14. Signal strength vs. distance for the beacon at Pigeon Point, California

- daytime measurements ................................ 20

Figure 15. Signal strength vs. distance for the beacon at Pigeon Point, California

- nighttime measurements ............................... 20

Figure 16. Signal strength vs. distance for the beacon at Point Blunt, California

- daytime measurements ................................ 21
FIGURES (Cont'd)

Page

viii

Figure 17. Signal strength vs. distance for the beacon at Point Blunt, California

- nighttime measurements ............................... 21

Figure 18. Signal strength vs. distance for the beacon at Cape Mendocino, California

- moving north toward the transmitter ........................ 22

Figure 19. Signal strength vs. distance for the beacon at Cape Mendocino, California

- moving north away form the transmitter ..................... 22

Figure 20. Signal strength vs. distance for the beacon at Fort Stevens, Oregon. .... 23

Figure 21. Signal strength vs distance for the Bennett FAA beacon at

Bennett, Colorado - en route to Cheyenne, Wyoming .............. 23

Figure 22. Signal strength vs. distance for the Bennett FAA beacon at

Bennett, Colorado - en route to Grand Junction, Colorado ........... 24

Figure 23. Cumulative distribution of deviation from 

the least squares fit for Aransas Pass, Texas .................... 25

Figure 24. Histogram of deviation from

the least squares fit for Aransas Pass, Texas .................... 25

Figure 25. Cumulative distribution of deviation from 

the least squares fit for Galveston, Texas ...................... 26

Figure 26. Histogram of deviation from

the least squares fit for Galveston, Texas ...................... 26

Figure 27. Cumulative distribution of deviation from

the least squares fit for English Turn, Louisiana ................. 27

Figure 28. Histogram of deviation from

the least squares fit for English Turn, Louisiana ................. 27

Figure 29. Cumulative distribution of deviation from

the least squares fit for Mobile Point, Alabama .................. 28
FIGURES (Cont'd)

Page

ix

Figure 30. Histogram of deviation from

the least squares fit for Mobile Point, Alabama .................. 28

Figure 31. Cumulative distribution of deviation from the least squares fit for 

Pigeon Point, California - nighttime acquisition ................. 29

Figure 32. Histogram of deviation from the least squares fit for 

Pigeon Point, California - nighttime acquisition ................. 29

Figure 33. Cumulative distribution of deviation from the least squares

fit for Point Blunt, California - nighttime acquisition .............. 30

Figure 34. Histogram of deviation from the least squares

fit for Point Blunt, California - nighttime acquisition .............. 30

Figure 35. Cumulative distribution of deviation from the least squares fit for 

Cape Mendocino, California moving north toward the transmitter ...... 31

Figure 36. Histogram of deviation from the least squares fit for 

Cape Mendocino, California moving north toward the transmitter ...... 31

Figure 37. Cumulative distribution of deviation from the least squares fit for 

Cape Mendocino, California moving north away from the transmitter ... 32

Figure 38. Histogram of deviation from the least squares fit for 

Cape Mendocino, California moving north away from the transmitter ... 32

Figure 39. Cumulative distribution of deviation from

the least squares fit for Fort Stevens, Oregon ................... 33

Figure 40. Histogram of deviation from

the least squares fit for Fort Stevens, Oregon ................... 33

Figure 41. Cumulative distribution of deviation from the least squares 

fit for the FAA beacon en route to Cheyenne, Wyoming ............ 34

Figure 42. Histogram of deviation from the least squares 

fit for the FAA beacon en route to Cheyenne, Wyoming ............ 34

Figure 43. Comparison of measured and predicted field strength

vs. distance for Aransas Pass, Texas - smooth earth ............... 35
FIGURES (Cont'd)

Page

x

Figure 44. Comparison of measured and predicted field strength

vs. distance for Galveston, Texas - smooth earth ................. 35

Figure 45. Comparison of measured and predicted field strength

vs. distance for English Turn, Louisiana - smooth earth ............ 36

Figure 46. Comparison of measured and predicted field strength

vs. distance for Mobile Point, Alabama - smooth earth ............. 36

Figure 47. Comparison of measured and predicted field strength vs. distance 

going west from the FAA beacon at Bennett, Colorado - smooth earth ... 37

Figure 48. Comparison of measured and predicted field strength vs. distance 

going west from the FAA beacon at Bennett, Colorado- irregular terrain . . 37

Figure 49. Comparison of measured and predicted field strength vs. distance 

going north from the FAA beacon at Bennett, Colorado - smooth earth . . 38

Figure 50. Comparison of measured and predicted field strength vs. distance 

going north from the FAA beacon at Bennett, Colorado - irregular terrain . 38

Figure D-1. Signal radiating isotropically into a hemisphere .................. 47
TABLES

Page

xi

Table 1. Beacon Characteristics ................................... 2

Table 2. Measurement Procedures for Noise and DGPS Signals ............... 10

Table 2. Y-intercept and Slope of Least Squares Fit ...................... 13

Table 3. Error Bounds on the Sample Cumulative Distributions ............... 14

Table 4. Model Input Parameters .................................. 17

Table C-1. Antenna Correction Factors ................................ 45
xii
 The authors are with the Institute for Telecommunication Sciences, National 1

Telecommunications and Information Administration, U.S. Department of Commerce, Boulder,

CO 80303

 This effort was sponsored by the Federal Highway Administration, Department of 2

Transportation.

FIELD STRENGTH MEASUREMENTS OF DGPS AND FAA BEACONS IN THE

285- TO 325-kHz BAND

J. Randy Hoffman, John J. Lemmon, Ronald L. Ketchum 1

Signal strength measurements in the 285- to 325-kHz band were conducted on eight

U.S. Coast Guard differential global positioning system beacons along the Gulf

and West Coast, and on a Federal Aviation Administration beacon in Bennett,

Colorado. Data were acquired continually en route between sites and tagged with

geographical position. Field strength of each individual signal was plotted against

distance from the transmitter. Cumulative distributions and histograms of deviation

from the least squares fit were also plotted. Results of the measurements were used

as model inputs and to compare results to model predictions.

Key words: differential GPS (DGPS); global positioning system (GPS); signal strength

measurements; U.S. Coast Guard beacon; FAA beacon; propagation models

1. PURPOSE

The purpose of this study was to determine absolute differential global positioning system (DGPS)

signal strengths at various distances from eight different U.S. Coast Guard beacons transmitting

DGPS signals and to measure signal strength at various distances from a Federal Aviation

Administration (FAA) beacon located in the same frequency band. Four of the measured DGPS 2

beacons are located along the Gulf Coast and four are on the West Coast. The measured FAA

beacon is located in Bennett, Colorado, east of Denver. Each of the transmitters are described

in Table 1. Results of the measurements are used to provide model inputs and to compare results

to actual model predictions.

2. STRATEGY

Measurements in the southern region were conducted by driving along the Gulf Coast between

Corpus Christi, Texas and Mobile, Alabama. On the first day, the measurement van was driven

to the U.S. Coast Guard station at Aransas Pass, Texas (see Figure 1). Starting approximately

17 km from the transmitter, signal strength measurements (304-kHz band only) were performed
2

Location Frequency

(kHz)

Antenna Transfer Rate

(bps)

Latitude

(N)

Longitude

(W)

Aransas Pass,

Texas

304 PA90B 100 27 50'18'' 97 03'33''

English Turn,

Louisiana

293 PA90B 200 29 52'44'' 89 56'31''

Galveston, 

Texas

296 PA90B 100 29 19'45'' 94 44'10''

Mobile Point,

Alabama

300 150 ft

Tower

100 30 13'38'' 88 01'24''

Pigeon Point,

California

287 PA90B 100 37 10'55'' 122 23'35'

'

Point Blunt,

California

310 PA90B 200 37 51'12'' 122 25'04'

'

Cape

Mendocino,

California

292 PA90B 100 40 26'29'' 124 23'56'

'

Fort Stevens,

Oregon

287 PA90B 100 46 12'18'' 123 57'21'

'

Bennett,

Colorado

321 Unknown N/A 39 47'31'' 104 26'03'

'

Table 1. Beacon Characteristics

as the measurement vehicle was driven along the southwest edge of the bay; through Corpus

Christi, circling around the bay to the north (see Figure 2). On the second day, measurements

were conducted between Corpus Christi, Texas and Lafayette, Louisiana while traveling along

Highways 77, 59, and Interstate 10. All four U.S. Coast Guard transmitters were monitored

continuously (except for a short break taken as the vehicle came in close proximity to the

Galveston, Texas site). The vehicle was driven to the town of Galveston via Highway 6 and then

transported by ferry across the bay. Measurements resumed on the opposite shore. Data were

acquired to within 5 km of the Galveston transmitter. For the remainder of the distance between

Galveston, Texas and Lafayette, Louisiana, data were acquired at nighttime. On the third day,

measurements were conducted continuously on all four Gulf State transmitters as the vehicle

traveled between Lafayette, Louisiana and Mobile, Alabama along Interstate 10. En route, the

measurement vehicle came within 11 km of the English Turn, Louisiana transmitter (see
3

Figure 1. Transmitter at

Aransas Pass, Texas.

Figure 2. Measurement route at Aransas Pass, Texas.

Figure 3). On the fourth day, measurements were

conducted near the Mobile Point transmitter (300-kHz

band only) as the vehicle was driven to the transmitter site

from the west side of the bay. Data were acquired to

within 10 km of the transmitter (see Figures 4 and 5).

On the West Coast, signal strength measurements were

conducted on each of the four DGPS transmitters by

driving the following routes: Data were acquired on the

DGPS signal from the transmitter at Cape Mendocino,

California while driving north from Santa Rosa,

California along Highway 101 within 12 km of the

transmitter and continuing north to Crescent City,

California. From there, the measurement vehicle was

driven along Highway 199 to Grants Pass, Oregon. Cape

Mendocino is located approximately halfway between

Santa Rosa and Grants Pass along Highway 1 (see

Figure 6). Data were acquired on the DGPS signal from
4

Figure 3. Measurement route between Aransas Pass, Texas and Mobile Point, Alabama.

Figure 4. Transmitter at

Mobile Point, Alabama.

the transmitter at Fort Stevens, Oregon starting at a

distance of 10 km from the transmitter on Highway 30,

traveling along the Columbia River east to The Dalles,

Oregon (see Figure 7). Both nighttime and daytime data

were acquired on the Pigeon Point, California and Point

Blunt, California transmitters. Pigeon Point is located

approximately 45 km north of Santa Cruz, California

along Highway 1, and Point Blunt is located on Angel

Island in the San Francisco Bay. Nighttime data were

acquired by driving south from Willits, California along

Highway 101 to the Golden Gate Bridge and continuing

along Highway 1 to Santa Cruz. Daytime data were

acquired by starting 6 km south of the Pigeon Point

transmitter traveling south to Santa Cruz, across the

coastal mountains on Highway 17, north on the eastern

border of the bay along Interstate 680, east along

Interstate 80, over the Sierra Nevada Mountains, and past

Reno, Nevada (see Figure 6).

Data on the FAA beacon at Bennett, Colorado were

acquired on two different routes. The first route started

at the transmitter traveling west along Interstate 70 over
5

Figure 5. Measurement route at Mobile Point, Alabama.

the Rocky Mountains to Grand Junction, Colorado. The second route started at the transmitter

traveling west along Interstate 70 to Interstate 25 and then north to approximately 50 km north

of Cheyenne, Wyoming (see Figure 8). The primary reason for measuring the signal strength on

the FAA beacon was to examine the propagation characteristics through the Rocky Mountains west

of Denver. The data collected on the second route was used to compare propagation

characteristics for flat terrain in the same approximate vicinity.

 3. MEASUREMENT SYSTEM

The measurement system (see Figure 9) consists of a receiving antenna, low pass filter, amplifier,

spectrum analyzer, global positioning system (GPS)/dead-reckoning (DR) receiver, and a

computer. The antenna was calibrated for antenna-correction factors at 2-kHz intervals between

285 kHz and 325 kHz (see Appendix C). The low pass filter serves to filter out all frequencies
6

Figure 6. Measurement routes for Cape Mendocino, California; Point Blunt, California; and

Pigeon Point, California.
7

Figure 7. Measurement route at Fort Stevens, Oregon.

Figure 8. Measurement route for the FAA beacon.
8

Figure 9. Block diagram of the measurement system.

above 400 kHz, particularly the AM broadcast bands. The computer is used to control the

spectrum analyzer, download raw data, gather GPS information, and perform various

computations. The overall gain of the system between the output of the antenna and the measured

output of the spectrum analyser is approximately 24 dB. The noise figure of the system is 9.6 dB,

giving a sensitivity of 7.85 dB μV/m for a bandwidth of 300 Hz (see Appendix B). The GPS

receiver has a dead-reckoning system such that, if satellite lock is lost, the proper coordinate

information is maintained.

4. MEASUREMENT PROCEDURE

The computer controlled the acquisition of data using GPIB and RS232 commands sent to the

spectrum analyzer and GPS receiver, respectively. Data also were downloaded via GPIB and

RS232. Both noise and DGPS signal strength data were acquired. 

Prior to acquiring data on the DGPS signal, the power of the noise was determined by making

measurements 500 Hz offset from the DGPS carrier frequency. The noise was measured to

determine if the signal, as a whole, could be detected against the noise background. The purpose

of measuring noise was not to determine environmental noise, even though, in many cases, this

may have been the primary source of noise. Three types of measurement procedures were used:

type 1 in the Gulf States, type 2 for Cape Mendocino, California, and type 3 for all the remaining
9

beacons along the West Coast and Colorado. The three measurement types are described in

Table 2. Note that for type 2 noise measurements, the spectrum analyser was set to zero span and

swept in time as opposed to the other two types which were swept in frequency. To avoid

measuring power from the adjacent DGPS signal itself, the resolution bandwidth of type 1 and 2

measurements was kept relatively small. For noise measurements, a single sweep was performed;

after which, the mean, the standard deviation, and the peak noise power were determined from

601 data points evenly spaced across the sweep. Type 2 and 3 measurements also collected 50

samples evenly spaced across the 601 data points of the sweep. Because the filters on the HP8563

spectrum analyzer are gaussian with a gentle roll-off and the measured signals are only 500 Hz

offset from the locations of the noise measurements, type 2 measurements resulted in an upward

bias due to the contribution of power by the adjacent signal. Therefore, the measurement

technique was changed to a type 3 noise measurement shortly after completing data acquisition

on the Cape Mendocino beacon. For all three techniques, there was an upward bias when the

noise measurements were conducted in close physical proximity to the transmitter because the

signal could contribute significantly to the power received within the bandwidth. This, again, is

because the filters in the HP8563 spectrum analyzer have a gentle roll-off and the measured

signals are only 500 Hz offset from the location of the noise measurements.

The DGPS signal strength was measured by performing 50 separate sweeps of a 500-Hz span

spaced between 1-5 s apart. After each sweep, the signal power was determined and recorded in

the data file. For a type 1 acquisition, the peak power over the entire span was determined and

recorded. For type 2 and 3 acquisitions, the power was determined at the DGPS center frequency.

The power determination at center frequency is believed to be better since the determination of

peak power over an entire span may cause a slight upward bias from spurious noise spikes. Based

on the antenna-correction factor and the known frequency, the signal field strength was calculated

as described in Appendix A. With each sweep, a data string from the GPS was downloaded and

placed in the file to mark the location of the acquisition. Each of the four parameters (frequency,

power, field strength, and GPS coordinate string) were recorded for each of the 50 sweeps. The

DGPS transmission rates are either 100 or 200 bps with minimum shift keyed modulation (MSK).

For MSK, 99% of the power is contained within a bandwidth equal to 1.17 times the bit rate.

Therefore, the resolution bandwidth of the spectrum analyzer was set at 300 Hz when acquiring

DGPS signal strength data. When more than one band was monitored, the system acquired noise

data and DGPS signal strength data (on the 50 sweeps for a particular frequency band) and then

performed the same operations on each of the successive bands. After completing the data

acquisition on each of the bands, the entire process was repeated continuously.

Two calibration procedures were performed before acquiring data. The first procedure was used

to determine the total gain between the output of the antenna and the measured power determined

by the spectrum analyzer. This gain was subtracted from the measured power to determine the

power at the output of the antenna. The procedure amounted to putting a signal of known power

into the cable which was normally connected to the antenna, and then the power was measured

on the spectrum analyzer. The difference between the known power and the measured power is
10

Table 2. Measurement Procedures for Noise and DGPS Signals

Noise Measurements

Parameters Type 1 Type 2 Type 3

Locations Gulf States Cape Mendocino,

California

Remaining beacons

on West Coast and

the FAA beacon in

Colorado

Span of Spectrum

Analyser

500 Hz Zero Span 200 Hz

Resolution

Bandwidth

30 Hz 300 Hz 10 Hz

Sweep Type Frequency Time Frequency

Sweep Time 360 ms 700 ms 350 ms

Parameters Measured Mean, standard

deviation, & peak

Mean, standard

deviation, & peak

Mean, standard

deviation, & peak

Additional Data

Acquired

None 50 samples across the

sweep

50 samples across the

sweep

DGPS Signal Measurements

Parameters Type 1 Type 2 Type 3

Location Gulf States Cape Mendocino,

California

Remaining beacons

on West Coast and

the FAA beacon in

Colorado

Span of Spectrum

Analyser

500 Hz 500 Hz 500 Hz

Power Measured Over the entire

frequency span

At the DGPS signal

center frequency

At the DGPS signal

center frequency

Resolution

Bandwidth

300 Hz 300 Hz 300 Hz
 The equivalent noise power P expressed in terms of a given bandwidth B is given by 3

e e

where Pm is the power measured at bandwidth Bm.

11

the gain of the system, which in this case is approximately 24 dB.

The second calibration procedure was used to determine any differences in antenna characteristics

between those measured in a laboratory (during which the antenna-correction factor was

determined) and the characteristics of the antenna when placed on the measurement van. First,

the antenna was placed at the center of a 1.3-m round backplane which, in turn, was mounted on

a tripod approximately 1 m above ground. This backplane configuration was used to simulate the

measurement conditions in the laboratory. The power of a known transmitted signal (such as a

DGPS signal) was measured. Then the antenna was mounted on the measurement van and the

power of the same signal was measured at eight different azimuth orientations by the van

(approximately 45 apart). Results showed essentially no difference between the two different o

antenna mounts and among the eight different azimuth orientations.

5. DATA PROCESSING

Data processing consisted of ordering the data and placing the results in an ASCII file for plotting.

Since the distance between a specific transmitter and the receiver does not necessarily

monotonically increase or decrease with each successive data point, the data was processed by

ordering the data according to distance. This was performed for each of the nine transmitters

listed in Table 1. After ordering the data, several parameters were written to an ASCII file:

distance, DGPS field strength, and noise field strength for an equivalent 300-Hz bandwidth.

6. ANALYSIS

Results showing the signal strength as a function of distance from each of the transmitter sites can

be seen in Figures 10-22 (pp. 18-24). The noise is represented as an equivalent field strength for

a 300-Hz bandwidth. An additional 10 and 15 dB are added to noise data acquired at 30- and

10-Hz bandwidths, respectively. The signal strength and equivalent average noise (for a 300-Hz 3

bandwidth) are plotted against the distance on the abscissa. For the Gulf Coast measurements,

the average noise was determined from successive groups of 50 data points. In other words, the
12

first point on the plot represents the average of the first group of 50 data points, the second point

on the plot represents the average of the second group of 50 data points, and so on. For all West

Coast and FAA beacon measurements, each point on the plot represents a moving average of the

data. This was accomplished by determining the average of the previous 50 data points for each

successive data point. The least squares fit for signal strength as a linear function of the log

base 10 of the distance also was determined for each of the transmitter sites shown in Table 3.

As a check of the system calibrations, expected signal levels at a specified distance from the

transmitter can be compared against measured values. At the Galveston site, the U.S. Coast

Guard reported an antenna efficiency of 15-20% with a signal input to the antenna of 1 kW. This

is consistent with the approximate measured signal level of 80 dB μV/m at 10 km (see

Appendix D).

Cumulative distribution curves and histogram plots for deviation from the least squares fit are

shown in Figures 23-42 (pp. 25-34). The same data points used to calculate the least squares fit

were used for these plots. Negative numbers represent signal strength occurring below the least

squares fit. The upper and lower bounds for the 99% confidence interval are included on each

of the cumulative distribution curves [1]. The numerical values for the 80% and 99% confidence

interval are shown in Table 4.

Separate plots and statistical summaries were generated for the different approaches to the Cape

Mendocino transmitter. Analysis in which all data were grouped together for this transmitter

showed a bimodal distribution related to the direction of approach. This is because the terrain is

significantly different when approaching the transmitter from the south or north. South of the

transmitter, the terrain is characterized by rolling hills separated by relatively flat regions. North

of the transmitter, there are cliffs, heavy forests, deep ravines, and mountainous areas.

 7. MEASUREMENT RESULTS

When plotted against the log of the distance, most of the DGPS signal data appear relatively linear

with a roll-off of 20 dB per decade. Deviations from this linearity appear in several cases.

Aransas Pass and Mobile Point data both show higher than expected signal levels between 300 and

500 km (see Figures 10 and 13). The cause of this is probably due to excess noise. Both the

Pigeon Point and Point Blunt daytime data show patterns of deviation that are similar (see

Figures 14 and 16). There are two regions of signal attenuation, both of which are located

physically in areas of rough terrain. The first dip coincides with crossing the coastal mountain

range between Santa Cruz and San Jose on Highway 17 (92 km from Point Blunt and 33 km from

Pigeon Point). The second dip coincides with crossing the Sierra Nevada mountain range east on

Interstate 80 (200 km from Point Blunt and 250 km from Pigeon Point). It is interesting to note

that the Sierra Nevada Mountains behave much like an attenuator. As the rough terrain is

traversed, the signal strength drops at a much faster rate, but once the relatively flat terrain of

Nevada is approached, the signal drops off at approximately the same slope as before. What
13

Location Y-intercept

(dB μV/m)

Slope

(dB μV/m) / log(km)

Data Points Used

Aransas Pass, Texas 99.35 -20.17 All points < 350 km

Galveston, Texas 100.42 -20.09 All points < 200 km

English Turn, Louisiana 116.44 -26.10 All data points

Mobile Point, Alabama 95.09 -19.05 All points < 350 km

Pigeon Point, California -

night

106.02 -27.88 All data points

Point Blunt, California -

night

96.91 -23.92 All data points

Cape Mendocino,

California - south

138.17 -53.76 All points < 100 km

Cape Mendocino,

California - north

123.15 -37.01 All points < 130 km

Fort Stevens, Oregon 100.75 -29.12 All data points

FAA Beacon at Bennett,

Colorado, en route to

Cheyenne, Wyoming

82.71 -19.05 All data points

Table 3. Y-intercept and Slope of Least Squares Fit

appears to be a very strong signal at approximately 400 km from both transmitters is, in actuality,

noise from a relatively severe but short-lived spring storm that occurred while crossing the plains

of Nevada. This elevated environmental noise was prolonged (lasting several minutes) and was

as strong or stronger than the DGPS signals at any time during the measurement; this

demonstrated the need to use Type 9 messaging for broadcasting corrections. The Fort Stevens

data (see Figure 20) show a relatively wide deviation from a 20 dB per decade roll-off. Much of

these data were acquired in areas of rough terrain, rolling hills, and in the gorge of the Columbia

River. The FAA beacon data going north to Cheyenne, Wyoming have a narrow deviation from

the least squares fit (see Figures 41 and 42) and track very closely to a roll-off of 20 dB per

decade (see Figure 21). Data collected on the same signal going west across the Rocky

Mountains, however, look quite different (see Figure 22). In this case, the signal shows

considerable attenuation when the mountainous terrain was crossed. It is interesting to note that

when acquiring data through the Denver area (between 20 and 70 km from the transmitter) the

environmental noise was considerably higher. All four of the Gulf Coast beacons show higher
14

Table 4. Error Bounds on the Sample Cumulative Distributions

Location Sample Size

Error Bounds (in probability units)

 80%

Confidence

 99%

Confidence

Aransas Pass, 

Texas

5018 ±0.015 ±0.023

Galveston, 

Texas

2449 ±0.022 ±0.033

English Turn, Louisiana 6200 ±0.014 ±0.021

Mobile Point, Alabama 5750 ±0.014 ±0.021

Pigeon Point, California

- night

2749 ±0.020 ±0.032

Point Blunt, California

- night

2658 ±0.021 ±0.032

Cape Mendocino,

California - south

1400 ±0.0286 ±0.0436

Cape Mendocino,

California - north

1500 ±0.0276 ±0.0421

Fort Stevens, Oregon 4950 ±0.015 ±0.023

FAA Beacon at

Bennett, Colorado

2999 ±0.020 ±0.030

signal strengths, but this may be due in part to the upward bias caused by picking the peak power

across a 500-Hz span (previously mentioned).

Cumulative distributions of the deviation from the least squares fit are relatively consistent among

the four different transmitter sites in the Gulf States (see Figures 23-30). There is a 0.98

probability in this case, that the DGPS signal will be greater than 10 dB below the least squares

fit. There is a slightly greater spread for nighttime data acquired on Pigeon Point and Point Blunt,

and daytime data for Cape Mendocino and Fort Stevens (see Figures 31-40). 
15

8. COMPARISON OF MEASUREMENTS WITH MODELS

As mentioned before, one purpose of carrying out the field strength measurements described in

this report is to compare the measurements with the signal strength predictions generated from

propagation models. Agreement between the measurements and model predictions serves to

validate the models and provides confidence in the use of the models to predict field strengths in

regions where measurements have not been performed. Disagreements between the measurements

and model predictions can provide insight regarding limitations of the models or indicate a need

to modify the models.

Predictions of field strength versus distance have been generated for the four DGPS beacons along

the Gulf Coast and for the FAA beacon in Bennett, Colorado. The propagation models are

described by Haakinson et al. [2] and references contained therein. The model inputs include

transmitter location, frequency, measured field strength at a reference distance, time of day, and

ground conductivity. Three types of field strength predictions are possible: smooth earth, which

neglects terrain and uses a fixed value of conductivity along the path; smooth earth mixed path,

which also neglects terrain but allows the user to construct a path along which the conductivity

varies; and irregular terrain, which uses a mixed path and also takes into account terrain features

from a terrain database.

Predictions generated from the propagation model were not developed for the beacons on the West

Coast. This is because the complicated routes and irregularities in terrain and ground conductivity

would make a comparison between predicted and measured field strengths quite tedious, although

in principle such a comparison could be made. For the Gulf Coast beacons, the relatively high

values of ground conductivity and absence of terrain features result in field strengths (versus

distance) that are nearly independent of the direction from the beacon. For this reason, the model

predictions could be accurately compared to data measured in multiple directions from the beacon.

Because of insignificant variation in terrain and ground conductivity, model predictions were made

using the smooth earth model. For the FAA beacon, there are dramatic variations in both terrain

and ground conductivity, but the routes were quite simple (essentially due north and due west),

so that mixed paths of ground conductivity could be developed for both routes using a conductivity

database; model predictions were made using both the smooth earth mixed path and irregular

terrain models.

The model predictions and measured values of field strengths versus distance for the four DGPS

beacons along the Gulf Coast are shown in Figures 43-46 (pp. 35-36). Values of the measured

field strengths and corresponding reference distances, used as model inputs, are listed in Table 5.

The values of conductivity that were used are the values at the transmitter location, obtained from

a conductivity database. The model predictions were generated for daytime hours, since most of

the data were obtained during the day. The model and measurements show good agreement at

most distances, although the measured values are somewhat larger than the predicted values at

large distances. This could be due to noise, which is expected to have a greater upward bias on

the measured field strengths when the signal is weak (greater distances), because the scale is
16

logarithmic (dB). It also could be due to the fact that the field strength data for these beacons were

acquired by recording the peak power over an entire span, as described in Section 4, resulting in

an upward bias of the measured signal strengths.

The measured field strengths and model predictions for the FAA beacon are shown in

Figures 47-50 (pp. 37-38). Again, measured field strengths that were used as model inputs are

listed in Table 5, and the models were used to generate predicted signal strength for daytime

hours. Comparisons have been made for both routes that were driven (Bennett, Colorado to

Cheyenne, Wyoming and Bennett, Colorado to Grand Junction, Colorado) using both the smooth

earth mixed path model and the irregular terrain model; thus, the effects of varying ground

conductivity and irregular terrain can be separated. Not surprisingly, both models make similar

predictions and are in good agreement with the data for the route from Bennett to Cheyenne, over

which the terrain is relatively flat. However, the measured field strengths show considerable

attenuation when crossing the Rocky Mountains between Bennett and Grand Junction. This is

partly due to the relatively poor ground conductivity in the mountains (rock), as can be seen from

the smooth earth mixed path model predictions, which neglect terrain. However, the deviations

between this model and the measured field strengths, which are as large as 15 dB or more,

indicate that terrain features also play a role in the large propagation losses that were observed in

this region. Note that these propagation losses are fairly well described by the irregular terrain

model. The magnitude of these deviations was somewhat unexpected, because the effects of terrain

features on field strengths are not generally this large at these frequencies. For example, the report

by DeMinco [3] contains numerous comparisons of predictions of the smooth earth and irregular

terrain models for various path profiles and frequencies; these comparisons do not show deviations

as large as 15 dB, although deviations as large as 10 dB do occasionally occur.

To further investigate the effects of irregular terrain, comparisons between the smooth earth and

irregular terrain models were made for a path going west from Colorado Springs, Colorado, over

the continental divide in the Rocky Mountains, and for a path going northeast from Sacramento,

California, into the Sierra Nevada Mountains. In both cases, the differences between the field

strength predictions of the two models are not more than 0.1 dB. However, it has been shown by

Furutsu et al. [4] that deviations as large as 15 dB or more can, in principle, occur in extremely

irregular terrain for certain configurations of the transmitter and receiver.

We conclude that irregular terrain is unlikely to have a significant effect on field strength

predictions at these frequencies; however, the effects need to be investigated on a case-by-case

basis in extremely irregular terrain. The fact that the model predictions and measured field

strengths are generally in good agreement provides confidence in the use of these models.
17

Location Measured Field Strength (dBμV/m)/

Reference Distance (km)

Aransas Pass, Texas 75/20 

Galveston, Texas 80/10

English Turn, Louisiana 80/20

Mobile Point, Alabama 80/10 

Bennett, Colorado to 

Grand Junction, Colorado

66/10 

Bennett, Colorado to 

Cheyenne, Wyoming

66/10

Table 5. Model Input Parameters

9. CONCLUSIONS

Signal strength measurements were conducted on eight DGPS beacons along the Gulf and West

Coast, and an FAA beacon in Colorado. The purpose was to provide model inputs and compare

measurement propagation characteristics with model predictions. To the extent that they could

be compared, the measured data are in good agreement with the model for most distances. At

large distances, the measured values are somewhat larger than the predicted values. The

difference is believed to be due to the contribution of noise during measurements.
18

Figure 10. Signal strength vs. distance for the beacon at

Aransas Pass, Texas.

Figure 11. Signal strength vs. distance for the beacon at

Galveston, Texas.
19

Figure 12. Signal strength vs. distance for the beacon at English

Turn, Louisiana.

Figure 13. Signal strength vs. distance for the beacon at Mobile

Point, Alabama.
20

Figure 14. Signal strength vs. distance for the beacon at Pigeon

Point, California - daytime measurements.

Figure 15. Signal strength vs. distance for the beacon at Pigeon

Point, California - nighttime measurements.
21

Figure 16. Signal strength vs. distance for the beacon at Point

Blunt, California - daytime measurements. 

Figure 17. Signal strength vs. distance for the beacon at Point

Blunt, California - nighttime measurements. 
22

Figure 18. Signal strength vs. distance for the beacon at Cape

Mendocino, California - moving north toward the

transmitter.

Figure 19. Signal strength vs. distance for the beacon at Cape

Mendocino, California - moving north away form

the transmitter.
23

Figure 20. Signal strength vs. distance for the beacon at Fort

Stevens, Oregon.

Figure 21. Signal strength vs. distance for the FAA beacon at

Bennett, Colorado - en route to Cheyenne,

Wyoming.
24

Figure 22. Signal strength vs. distance for the FAA beacon at

Bennett, Colorado - en route to Grand Junction, 

Colorado.
25

Figure 23. Cumulative distribution of deviation from the least

squares fit for Aransas Pass, Texas.

Figure 24. Histogram of deviation from the least squares fit for

Aransas Pass, Texas.
26

Figure 25. Cumulative distribution of deviation from the least

squares fit for Galveston, Texas.

Figure 26. Histogram of deviation from the least squares fit for

Galveston, Texas.
27

Figure 27. Cumulative distribution of deviation from the least

squares fit for English Turn, Louisiana.

Figure 28. Histogram of deviation from the least squares fit for

English Turn, Louisiana.
28

Figure 29. Cumulative distribution of deviation from the least

squares fit for Mobile Point, Alabama.

Figure 30. Histogram of deviation from the least squares fit for

Mobile Point, Alabama.
29

Figure 31. Cumulative distribution of deviation from the least

squares fit for Pigeon Point, California - nighttime

acquisition.

Figure 32. Histogram of deviation from the least squares fit for

Pigeon Point, California - nighttime acquisition.
30

Figure 33. Cumulative distribution of deviation from the least

squares fit for Point Blunt, California - nighttime

acquisition.

Figure 34. Histogram of deviation from the least squares fit for

Point Blunt, California - nighttime acquisition.
31

Figure 35. Cumulative distribution of deviation from the least

squares fit for Cape Mendocino, California moving

north toward the transmitter.

Figure 36. Histogram of deviation from the least squares fit for

Cape Mendocino, California moving north toward the

transmitter.
32

Figure 37. Cumulative distribution of deviation from the least

squares fit for Cape Mendocino, California moving

north away from the transmitter.

Figure 38. Histogram of deviation from the least squares fit for

Cape Mendocino, California moving north away from

the transmitter.
33

Figure 39. Cumulative distribution of deviation from the least

squares fit for Fort Stevens, Oregon.

Figure 40. Histogram of deviation from the least squares fit for

Fort Stevens, Oregon.
34

Figure 41. Cumulative distribution of deviation from the least

squares fit for the FAA beacon en route to Cheyenne,

Wyoming.

Figure 42. Histogram of deviation from the least squares fit for

the FAA beacon en route to Cheyenne, Wyoming.
35

Figure 43. Comparison of measured and predicted field

strength vs. distance for Aransas Pass, Texas -

smooth earth.

Figure 44. Comparison of measured and predicted field

strength vs. distance for Galveston, Texas - smooth

earth.
36

Figure 45. Comparison of measured and predicted field

strength vs. distance for English Turn, Louisiana -

smooth earth.

Figure 46. Comparison of measured and predicted field

strength vs. distance for Mobile Point, Alabama -

smooth earth.
37

Figure 47. Comparison of measured and predicted field

strength vs. distance going west from the FAA

beacon at Bennett, Colorado - smooth earth.

Figure 48. Comparison of measured and predicted field

strength vs. distance going west from the FAA

beacon at Bennett, Colorado - irregular terrain.
38

Figure 49. Comparison of measured and predicted field

strength vs. distance going north from the FAA

beacon at Bennett, Colorado - smooth earth.

Figure 50. Comparison of measured and predicted field

strength vs. distance going north from the FAA

beacon at Bennett, Colorado - irregular terrain.
39

10. ACKNOWLEDGMENT

The authors wish to thank James A. Arnold of the Federal Highway Administration,

Department of Transportation for funding this work.

11. REFERENCES

[1] W.J. Dixon, and F.J. Massey, Introduction to Statistical Analysis, New York: 

McGraw-Hill, Inc., 1969, pp. 345-347.

[2] E. Haakinson, S. Rothschild, and B. Bedford, “MF broadcasting system performance

model,” NTIA Report 88-237, Aug. 1988.

[3] N. DeMinco, “Ground-wave analysis model for MF broadcast systems,” NTIA Report

86-203, Sep. 1996.

[4] K. Furutsu, R.E. Wilkerson, and R.F. Hartmann, “Some numerical results based on

the theory of radio wave propagation over inhomogeneous earth,” Radio Science 68D,

No. 7, pp. 827-846, Jul. 1964.
40
41

(A1)

(A2)

(A3)

(A4)

(A5)

APPENDIX A: SIGNAL FIELD STRENGTH COMPUTATIONS

Field strength is measured in dBμV/m as seen by the receiving antenna. This is calculated from

the peak-power value and the antenna-correction factor using the following equations:

where is the gain of the antenna in dBi, fmHz is the frequency in MHz, and ACF is the antenna

correction factor in dB;

where A is the aperture of the antenna in units of m , and is the wavelength of the carrier 2

frequency in meters; 

where c is the speed of light in m/s (3e8 m/s), and f is the carrier frequency in Hz; Hz

where P is the power density in watts/m , and P is the power in watts measured at the output d m(watts)

2

of the antenna;

where is the E field in dBμV/m measured at the antenna, and 377 is the impedance of free

space measured in ohms.
42
43

(B1)

(B2)

(B3)

APPENDIX B: NOISE FIGURE AND SENSITIVITY COMPUTATIONS

For a multistage amplifier that has stage power gains G1, G3, G3,... (linear form), and stage noise

figures F , F , F ,... (linear form), respectively, the overall noise figure is [1] 1 3 3

The measurement system seen in Figure 9, has a single stage gain of 22.4 dB (Mini-Circuits

amplifier) with a typical noise figure of 2.9 dB. Cable losses and the insertion loss of the low pass

filter are negligible. The noise figure of the spectrum analyzer is 31 dB. From Equation (B1),

the overall noise figure of the system is 9.6 dB.

The bandwidth and overall noise figure of the system determine the smallest signal that can be

detected; it is computed from the following equation: 

where NP is the noise power in dBm, -174 is the thermal noise in a 1-Hz bandwidth at room

temperature (300 K), B is the bandwidth of the system in Hz, and FdB is the overall noise figure

of the system in dB. The quantity NP is the minimum signal power that can be detected at the

output of the antenna. In this case, the bandwidth of the system is 300 Hz. Therefore, using

Equation (B2), NP is calculated to be -139.6 dBm, or expressed in watts,

Knowing NP, one can calculate the sensitivity of the system at the input to the antenna using

Equations (A1) through (A5) (see Appendix A). Assuming a typical carrier frequency of 300 kHz

and the corresponding antenna-correction factor of 40.5 dB, the minimum power density at the

input to the antenna must be 16.18e-15 watts/m in order to be detected. This corresponds to a 2

field strength of 7.85 dB μv/m.
44

REFERENCE

[1] F.G. Stremler, Introduction to Communication Systems, Reading, Massachusetts: AddisonWesley Publishing Company, 1997, pp. 173-174.
45

APPENDIX C: CORRECTION FACTORS FOR THE EATON 94592-1 ANTENNA

Table C-1 lists the antenna correction factors for the Eaton 94592-1 monopole antenna used during

measurements. The antenna was measured to an absolute accuracy of 2 dB.

Table C-1. Antenna Correction Factors

Frequency

(kHz)

Antenna Correction

Factor (dB)

285.0 41.2

287.0 41.2

289.0 41.0

291.0 40.9

293.0 40.9

295.0 40.7

297.0 40.7

299.0 40.6

301.0 40.5

303.0 40.5

305.0 40.4

307.0 40.4

309.0 40.4

311.0 40.4

313.0 40.2

315.0 40.1

317.0 40.1

319.0 40.1

321.0 40.0

323.0 39.9

325.0 39.9
46
47

Figure D-1. Signal radiating

isotropically into a hemisphere.

(D1)

(D2)

APPENDIX D: COMPUTATION OF EXPECTED ELECTRIC FIELD STRENGTH 

For a known power into a transmitting antenna and a

given antenna efficiency, the expected signal strength

in dB μV/m can be determined at a specified distance

from the transmitter. Assuming the signal is radiating

isotropically into a hemisphere (see Figure D-1), the

power is evenly distributed over a surface equal to

(where r is the distance from the transmitter in

meters). The power density at the receiver expressed in

watts/m can be determined by 2

where e is the efficiency of the transmitting antenna and P is the input power. t

The electric field E in dB μV/m is determined by

where 377 is the impedance of free space measured in ohms.

As an example, a transmitter with an antenna efficiency e between 15 and 20% and signal power

Pt into the antenna of 1000 W, the expected power density Pd at 10 km would be between

238.7e-9 and 318.3e-9 watts/m (Equation D1). The expected electric field strength E at the same 2

distance is between 79.5 and 80.8 dB μV/m (Equation D2).