T he Bureau of Mines has conducted field studies in 

coal mines throughout the United States to determine the effectiveness of electromagnetic techniques in 

locating miners trapped underground following a mine 

accident. Data from these tests have been used to 

generate models of expected signal and noise distributions as found above these mines. These distributions 

have aided in placing the expected performance of a 

through-the-earth electromagnetic communications 

technique into a probabilistic framework. p6Bfl!WmO@ 

#t@t"t 'tiT% fik$pktr fif fat dI t!'@-e,iip.@d-pi'oQabilH y of&, ! efling:a*mer's..sEnal %om adepthpflbWR S 

,?YY~? at 500 ft it is 95%. These depths exceed the actual 

depths of 90 and 50%, respectively, of United States 

Electromagnetic 

Detection of 

' Trapped Miners 

The value of communications with miners trapped 

underground following a mine disaster has been recognized since the 1921)'s (1,2]. Tests were performed where 

underground reception was made of signals from the 

first commercial radio station, KDKA, approximately ten A report on 94. field tests using miles from the mine. The investigators concluded narrowband EM transmitters to I'ocate 

correctly that the reception of the radio signal was aided 

by metallic conductors located within and around the trapped miners 

mine. Interest in through-the-earth communications to 

trapped miners continued to grow. 

Earth conductivity measurements were made and 

transmission loss tests for radio frequency (RF) propagation through-the-earth were conducted. Ilsey et al. 

[3] performed experiments in such communications and 

concluded that low frequencies penetrated the earth 

more efficiently than higher frequencies and that much 

greater reception distances were obtained when metallic 

conductors were present. By the end of the 19201s, it was 

concluded that no practical system for through-theearth radio comrnunicatians was possible because of the 

large power requirements necessary to establish them 

effectively. 

During the 1930's, interest in through-the-earth propagation was renewed when investigators became 

aware of the potential in using radio waves for 

geophysical exploration [4]. They found that the electric 

and magnetic field intensitiesfrom electromagnetic (EM) 

radiation from distant thunderstorms varied with local 

underground geology. However, little effort was placed 

on through-the-earth communications until the 19401s, 

when renewed efforts were made in South Africaand the 

IJnited States, 

The South Africans were concerned with establishing 

communications between the surface and a rescue team. 

Wadley [5] showed that if low frequencies were used, 

communications could be established through several 

hundred meters of earth. Later, during the 19601s, the 
South Africans developed and tested medium frequency 

(MF) hardware [6]. The results demonstrated that 

communications could be obtained over a large range, 

mainly due to coupling with metallic conductors; the 

equipment, however, proved too bulky for practical 

applications. These units were later modified and 

miniaturized, and placed in operation in a deep gold mine 

near Johannesburg [7]. 

In the United States, the Bureau of Mines maintained a 

modest effort to develop through-the-earth communications until after World War 11, when Bureau investigators 

Coggleshall and Felegy [8,9] performed a series of tests 

at two bituminous and three anthracite mines in 

Pennsylvania, and at a salt mine and iron mine in New 

York. They also worked with MF hardware and, like the 

South Africans, found good success when conductors 

were available. 

During the 1960's, the military began to realize the 

potential for secure through-the-earth communications. 

Most of the research considered electric field antennas 

operating at very-low frequencies (VLF) or extremelylow frequencies (ELF) [lo-131. Similar to the findings of 

earlier investigators, these studies showed that effective 

communications ranges decreased as transmission 

frequency and earth conductivity increased. Also, the 

overall effectiveness of the communications link was 

highly variable and required large amounts of transmitter power. 

The problem of through-the-earth communications 

gained a new urgency as the result of a mine disaster at 

Farmington, WV, on November 20,1968. A dust and gas 

explosion at Mountaineer Coal Co.'s Consol. No. 9 mine 

killed 78 miners. For some time following the disaster, 

the fate of the miners was unknown. The void created by 

the absence of emergency communications was obvious. 

The following year, the Bureau of Mines contracted with 

the National Academy of Engineering [14] to assess the 

technological capabilities that could be applied to 

improving repair techniques and miner survival following mine disasters. An important area of consideration 

by the Academy was post-disaster communications. The 

Academy recommended that the Bureau of Mines 

conduct research leading towards the development of 

equipment for the location of and communication with 

trapped miners through EM techniques. The Academy, 

drawing upon the results of the earlier studies previously 

discussed, concluded that the most promising avenue of 

investigation would be development of narrowband EM 

transmitters, which could be used by the trapped miner 

to transmit a pulsed EM signal to the surface. There, 

rescue team members could both detect the signal and 

establish its place of origin. 

During the 1970's, the Bureau of Mines developed 

narrowband EM transmitters [15,16] and performed field 

tests at ninety-four different coal mines to determine 

the effectiveness of this technique for locating trapped 

miners [17,18]. This report discusses the results of 

these tests. 

Earth Transmission Loss 

To predict the surface signal level produced from an 

underground transmitter, it is necessary to understand 

the expected loss the signal incurs when transmitted 

through the earth. Unfortunately, the geological structure of the overburden above coal mines differs from 

mine to mine. This gives rise to differing electrical 

conductivity structures. Therefore, for a given mine 

depth, it can .be expected that signal transmission 

characteristics will vary from mine to mine. One 

approach for attaining information on the earth's 

transmission loss is through statistical analysis of 

through-the-earth transmission tests. A major objective 

of the94-mine field test was to obtain enough data on the 

earth's transmission loss, as found over a large 

population of representative coal mines, and over a 

range of frequencies, to confidently characterize expected 

signal loss from an underground transmitter. A detailed 

description of equipment configurations and procedures 

used in the field-test program is given in [17]. 

To ensure success in obtaining data during the field 

tests, magnetic moments of the underground transmitter 

were used which were higher than would be expected 

from a transmitter to be used by a miner; this ensured 

that earth transmission loss data would be obtained. A 

strategy was then formed to predict the expected surface 

signal strength based upon a given magnetic moment. 

It should also be mentioned that the position of the 

underground transmitter was determined by measuring 

the horizontal signal field at different locations and, by 

finding the null in the field, the underground location was 

found by triangulation. This location measurement 

technique had the added benefit of ensuring that the 

,transmitted signal was actually traversing the earth 

medium and was not conducted along pipes, wires, or 

other conductors. 

The root-mean-square (rms) values of the vertical 

magnetic field, Hz, of all of the data taken were 

normalized to a transmitter magnetic moment (M) of M= 

1 amp-m2. Since the surface field is directly proportional 

to the magnetic moment of the underground transmitter, 

the expected level of the surface field for a given 

transmitter could then be found by accounting for the 

actual magnetic moment used. Following this normalization, statistical studies were performed to relate the 

surface field strength and mine depth at each frequency 

tested. 

Each normalized data point can be denoted as S,,, 

where i represents the specific frequency and j represents the specific depth of test for each mine. Thus, each 

surface measurement Sij taken can be considered as a 

single observation of signal strength at a predetermined 

frequency and overburden depth level at a particular 

mine. 

The relationship between field strength and mine 

depth was found through regression analysis. This work 

assumes that the errors are normally distributed and the 
variance is equal across the independent variable.These S,, = (Y~ + pi log (depth ,) + fjj. 

assumptions were considered, and it was concluded that (1) 

meaningful statistical inferences from the regression 

analysis could be made. Several linear regression Here, Sij is the normalized vertical magnetic field signal 

models were hypothesized and tried. The model found to strength (expressed in dB re 1 pamp/m-rms for the ith 

best fit the behavior of the data is one in which the mean frequency and depth j for a transmitter magnetic 

value of the normalized signal strength S,, is linearly moment of M = 1 amp-m2). 

related to the logarithm of overburden depth. This is The parameters and Pi were estimated from the 

shown in (1): data, where depth is in meters. The parameter ei, 

30 1 I I I "'I ' I '"11111 

Normalized to transmit moment of M=l Amp-m2 - 

f95-pct prediction interval - 

- 

- 

Free-space curve 

- 

V,-JO - prediction interval 0 

1 

W-60 - LL 

w 95-pct confidence interval 

0-70 - 3 

5-80 - 2010g S ~97.62-61.97 log(depth) V, 

-90 

-100 

30 I I I I 111 I 1'1"" 

Normalized to transmit moment of M-l Amp-m2 - 

- 

95-pct prediction interval - 

Free-space curve - 

1-30 - I- 

(3 

0 

_J 

W-60 - 

w 0-70 - 

9 

[L 20 log S= 108.01- 67 Il.log (depth) 3 -80 - m R~ =.85 

~'=.83 - - 

I I I I I I ,I / I, ,111,, 

-90 

100 150 200 250 300 500 700 1,000 1,500 

OVERBURDEN DEPTH, ft 

Fig. 1. Uplink regression results for 630-Hz-normalized verticai 

signal strength vs. depth. 

30 I I I 1 '" ' I"1"" 

Normalized to transmit moment of M=l Amp-m2 - 

95-pct prediction interval - 

- 

- Free-space curve 

- 

- 

(3 

n 

J 

W-60 - LI 

w 95-pct confidence internal 0-70 - 

9 - 

m 20 log S =109.05 - 68.31 log (depth) 

-100 

- 

100 

1 

I50 200 250 300 500 700 ID00 1,500 

OVERBURDEN DEPTH, ft 

Fig. 3. Uplink regression results for 1950-Hz-normalized 

vertical signal strength vs. depth. 

- - 

100 I 1 I I / I II I I1 1111,1 

100 150 ZOO 250 300 500 700 1,000 1,500 

OVERBURDEN DEPTH, ft 

Fig. 2. Uplink regression results for 1050-Hz-normalized 

vertical signal strength vs. depth. 

I I I '('I ' 1'111111 

- 

95-pct prediction interval 

- 

Free-space curve - 

1-30 - + 

(3 

_J 

W-60 - 

LL 95-pct confidence internal 

w 

U -70 - 

2 

5 _80 - 20 log S = 124.94 - 76.71 log (depth) m R~ =.80 

-90 - 

-100 I I 1 1 I I1 II I, 4 I,,,, 

100 150 ZOO 250 300 500 700 1,000 1,500 

OVERBURDEN DEPTH, ft 

Fig. 4. Uplink regression results for 3030-Hz-normalized 

vertical signal strength vs. depth. 

A 
10 

0 

- .. 

- I" -10 

L b E-20 Z\ Free-space curve 

E: 

I- a -30 

0- 

z-40 W Lg! 

W -50 

3 

fY -60 3 

V) 

- 70 

-80 150 200 250 300 400 500 700 1,000 1.500 2,000 

OVERBURDEN DEPTH, ft 

Fig. 5. Normallzed overburden response curves-uplink regresslon results: Average surface vertlcal slgnal strength vs. 

overburden depth by frequency. 

F 

represents a random variable that is normally distributed, with expected value zero and variance a2,,, which 

is the same for all values of j. 

The derived regression lines for each of the four 

frequencies are plotted in Figs. 1-4. The R2 statistic, a 

measure of goodness of fit, indicates that the log-linear 

relationship of (1) is appropriate. Also shown in these 

figures are confidence and prediction intervals. 

Figure 5 summarizes the normalized average overburden response as afunction of depth and frequency by 

plotting the four regression lines and the free space 

curve on one graph. This figure shows that the frequency 

dependence of signal strength is relatively insignificant 

for depths less than 500 ft, and that the change across 

the band is only about 10dB even at the maximum depth 

of 1500 ft. 

These summary normalized overburden response 

plots, together with the confidence and prediction levels 

in this section, can be used to generate estimates of 

signal strength produced on the surface above coal 

mines as a function of overburden depth and operating 

frequency for transmitters having any prescribed magnetic moment vs. frequency characteristics in the 630- to 

3030-Hz band. These results assume that, for a fixed 

magnetic moment, the size of the transmitting loop has 

no influence on the surface field. It is recognized that this 

assumption is not totally valid, as demonstrated by Wait 

[19], but it is considered that the size of loop used during 

the tests and the typical offsets for measuring the 

surface field were not severe enough to greatly influence 

the results. 

General Instrument (GI) fabricated an EM trapped 

miner transmitter [20]. This instrument was designed to 

be lightweight, worn on the belt, and capable of 

deploying a loop of wire 300 ft in length. The expected 

surface signal strengths produced by this transmitter 

can be predicted by computing the expected magnetic 

movement at each frequency and then translating each 

of the overburden response curves of Fig. 5 upwards by 

an amount equal to the values of the magnetic moment 

expressed in dB re 1 amp-m2. 

The assumed loop configuration of the GI transmitter 

is a square. This loop configuration was chosen because 

it best represents the practical implementation of the 

procedure that the miners will be instructed to follow. 

Figure6shows the predicted surface field strength when 

the GI transmitter is used. Also shown are the expected 

magnetic moments for each frequency. 

Surface EM Noise 

During the field tests at 27 of the mines tested, tape 

recordings were made of the vertical magnetic noise 

(receiver loop lying flat on earth) on the surface. These 

recordings were later used to obtain data on the noise at 

the four frequencies of interest. These data were 

obtained by performing a Fast-Fourier-Transform of the 

recorded noise. 

For the purposes of signal detectability, the rms value 

of the vertical magnetic field noise is of interest. The 

statistical distribution of this noise, using the Bureau 

data base from 27 mines, at each frequency for a 30-Hz 

bandwidth is shown in Figs. 7-10. The 30-Hz bandwidth 

was chosen because it represents the bandwidth of a 

typical receiver which would be used in this application. 

Surface SNR Ratio 

In the previous sections, the behavior of signal and 

noise data obtained in this study has been characterized 

I OVERBURDEN DEPTH,\ft \ 

i 

\ ', I 1 

Fig. 6. Predicted uplink response curves for 

ments transmitter: average surface vertical 

slgnal strength vs. depth by frequency. 

i - ' - '5 ) 

- -------- r, 2 -1 -5 .=>%I , 

TABLE l 

ESTIMATED PARAMETERS CHARACTERIZING SIGNAL AN0 NOISE O~STR~BUT~ONS ABOVE COAL MINES 

Overburden depth, ft. 630 Hz 1050 Hz 1950 Hz 3030 Hz 

Estimated Mean Signal in dB re 1 pA/m for GI Transmitter --- 

250. ............................... 37.50 

500 ................................ 18.84 

1000.. .............................. 0.19 

1500. ............................... -10.72 

Standard deviation. .................. 06.65 

Estimated Mean Noise in dB re 1 pA/ml a 

All depths.. ..................... 

Standard deviation.. ............. 

by statistical relationships. It has been found that both 

the signal and noise data are log-normally distributed. 

To develop an understanding of detection probability, it 

is necessary to characterize the probability distributions 

of the surface rrns SNR at each frequency. The basic 

input for the derivation of rms-SNR estimates on the 

surface is summarized in Table I. Mean rrns signal 

strength and standard deviation values adjusted to 

pertain to the GI transmitter are given at each frequency 

for different mine depths. Mean rrns noise strengths and 

their standard deviations are also given at each 

frequency. 

The independence of signal and noise distributions, in 

addition to the property of normality exhibited by each 

distribution, permits straightforward combination of the 

two distributions to generate SNR probability estimates. 

The SNR distributions are conveniently plotted using 

normal probability paper and are given in Figs. 11-14for 

five different overburden depths at each of the four 

frequencies. These four figures provide a straightforward method of estimating the probability of having 

various SNR's in actual practice. The vertical axis 

represents the area under the normal curve from minus 

infinity to some SNR value R, and provides the 

probability of achieving an SNR value less than or equal 

to R,. Figure 15 gives the probability that the rrns signal 

is at least greater than the rrns noise as a function of 

depth. 

Probability of Detection Estimate 

The success of a rescue effort when using a trappedminer transmitter rests on the ability of surface 

personnel to confidently detect the signal from the 

underground transmitter. The pulsed signals from the 

underground transmitters are detected by searchers 

carrying rescue receivers equipped with a hand-held 

loop antenna and headsets. The mode of detection is 

aural, based on the headset signals perceived by the ear. 

It is thus necessary to establish a relationship between 

the nature of the signal, SNR, and the probability of aural 

signal detection. 

> 

30 

- II 1-1 IIIIIII I I Ill I 

20- - - 

I 

- 

- 

wa 

IL E 

a -10 - w 3. - 

cn - - 

- 

-40 I IIIIIII I I Ill I 

1.0 2 5 10 20 30 40 50 60 70 80 90 95 98 99 99.5 99.9 

CUMULATIVE NORMAL PROBABILITY, pct 

Fig. 10. Statistical distribution of rrns surface noise at 3030 Hz for a 30-Hz bandwidth. 
98 - 

97 - 

96 - 

- 95 - 

U - 6 - 

- a - - 

Ro= SNR, dB 

Fig. 11. Cumulative probability distribution of SNR expected 

above United States underground coal mines at 630 Hz. 

98 - 

97 - 

96 - 

95 - - - 

aO - 

& 70- 

W - 

RO= SNR, dB 

Fig. 13. Cumulative probablllty distribution of SNR expected 

above United States underground coal mines at 1950 Hz. 

98 - 

97 - 

- a - - _ 90 - m 

-0 

9 - 

Ro= SNR, dB 

Fig. 12. Cumulative probabllity distribution of SNR expected 

above United States underground coal mines at 1050 Hz. 

98 - 

97 - 

96 - 

1 - 

Ro= SNR, dB 

Fig. 14. Cumulative probablllty distribution of SNR expected 

above United States underground coal mines at 3030 Hz. 
1 .o 

.9 - KEY - 

X---X 1950 Hz 

.8 - D.--O 3030 Hz - 

.7 - 

- 

5 - 

cn .5 - 

.4 - 

.3 - 

.2 - 

I 

0 2 50 500 750 1,000 1,250 1,500 

OVERBURDEN DEPTH, ft 

Fig. 15. Probability that mean rms signal is greater than or 

equal to rms noise lor the General instruments transmitter. 

The GI transmitters have a fixed pulse duration of 

100 ms and a repetition rate of once per second. The 

present receiver mixes the received signal with an 

internal oscillator to a higher frequency for purposes of 

narrowband filtering, and then remixes the filtered 

signal to present a listening signal of 978 Hz to the 

operator. 

In the work by Ristenbatt [21], tests were performed to 

verify the signal detectability performance of the present 

system. Tests were made using nine observers and the 

actual transmitter and receiver. The signal from the 

transmitter was mixed with wideband white noise and 

entered into the receiver at input SNR's of 0, 3, and 

6 dB. The acoustic output of the receiver was then 

connected to a headset worn by the observer. Each 

observer was exposed to a series of 100 trials at each 

input SNR. Each trial lasted for 15s. After each 15-s test, 

the observer was asked to note each test during which a 

signal might have been presented on a four-point rating 

scale; for example: 

0-Confident, signal absent; 

1-Less confident, signal absent; 

2-Less confident, signal present; 

3-Confident, signal present. 

These data were then used to determine the expected 

probability of detection (PD) and probability of false 

alarm (PFA) at the different SNR's. This testing provides 

the receiver operating characteristics (ROC) for the 

present receiver, and the results are shown in Fig. 16. 

The shaded area around SNR's of 0 and 6 dB shows the 

variability in the data obtained. The variability around 

the SNR = 3 dB curve is similar to that of the 0-dB curve 

but is not shown in the interest of retaining clarity in the 

figure. Therefore, for a particular input SNR and 

preassigned PFn, it is possible to determine the expected 

PD of the observer. 

The practical effect of false alarms is increased delay 

due to added search time. Hence, false alarms are 

important not only for comparing different receivers but 

also for understanding the practical impact a receiver 

may have in a search-and-find mission. A reasonable 

operating point for the false alarms of this system would 

be PFA = 0.10. For this PFA, Fig. 16 can be used to obtain 

the expected Po for the observer at different SNR's. 

It is now possible to calculate the probability of 

detecting the trapped miner's signal based upon the ROC 

of the receiver. The probability of detection curve in Fig. 

16 actually represents a conditional probability; that is, 

the likelihood that detection will occur given the 

presence of a fixed rms SNR. As a consequence, the 

chance of detecting a signal transmitted through the 

earth can be calculated according to 

P(D and Rk) = P(Rk) x P(DI Rk) (2) 

where P(D and Rk) represents the probability of achieving 

an SNR of size Rk and also detecting the signal in the 

noise. P(Rk) is the probability of the occurrence of an 

SNR of size Rk, and P(DI Rk) is the conditional probability 

of detecting a signal given an SNR of size Rk. 

Figure 16givesP(DIRk), and Figs. 11-14show the SNR 

probability distributions. The latter figures show that 

these probabilities depend on frequency and depth. 

Using additional subscripts to account for these 

parameters, the probability of achieving an SNR of size 

Rk and detecting the signal transmitted from a depth j at 

frequency i is 

Pjjk (D and Rk) = P,, (Rk) x P(DI Rk). 

However, the primary result is the expected probability 

of detecting a signal transmitted at a specified depth and 

99 

98 

97 

96 

95 

90 

80 

70 

60 

an so 

40 

30 

20 

10 

5 

4 

3 

2 

I 2 3 4 5 10 20 30 40 50 60 70 80 90 

'F. A. 

Fig. 16. Receiver operating characteristic curve for trappedminer receiver. 
a known frequency summed over all possible Rk's. This 

is given as 

Using this formulation, Fig. 17 shows the expected 

probability of signal detection as a function of depth for 

the different frequencies. From Fig. 17, it can be seen that 

1950 Hz is the frequency most likely to be detected. For 

this frequency, the expected probability of detecting a 

miner's signal from a depth of 1000 ft is 54%, and from 

500 ft is 95%. These depths exceed the actual depths of 

90 and 50%, respectively, of United States coal mines. 

Performance Improvement 

It is informative to observe the amount of increase in 

probability of signal detection for increases in SNR of the 

trapped-miner signal on the surface of the mine. Insight 

is provided by way of Fig. 18, where the detection 

probabilities are shown for each frequency at a depth of 

1000 ft as the SNR is improved. To obtain a detection 

probability of 90% at 1000 ft, an SNR improvement of 

approximately 18 dB would be needed for the 1950-Hz 

case. A rough estimate shows that, for all frequencies, 

the probability of detection increases approximately 2% 

at 1000 ft for every dB improvement in SNR. 

Various areas of investigation may lead to improved 

performance. The obvious first choice is to increase the 

strength of the signal source. However, inherent constraints due to intrinsic safety considerations would 

limit any gain by this technique to only a few dB. 

Correlation techniques could be used, employing an 

array of receiving antennas to improve detectability. 

This is the objective of a current project [22]. Incoherent 

integration of the present signal has been suggested by 

Ristenbatt [23] and is the technique proposed by General 

Instrument Corp. [24] in an adaptation to the present 

receiver. 

I OVERBURDEN DEPTH, fl 

Fig. 17. Predicted probability of signal detection vs. overburden depth by frequency for the GI transmitter as found by 

the ROC method. 

Noise cancellation through correlation techniques, 

involving the noise at the receiving antenna and a 

distant antenna outside the signal's range, is an area for 

future study. 

The parameters of the signal that affect an observer's 

ability to detect a pulsed continuous wave signal in noise 

could be studied to improve detectability. However, 

these studies must also be conscious of the efficient use 

of the power of the transmitter battery and of schemes 

used in search procedures. 

Possibly the most promising venture to improve signal 

detectability is a project under investigation by Develco 

[25]. Here, the underground transmitter is similar to the 

one discussed in this report, though the signal is not 

pulsed, but is transmitted continuously. The surface 

receiver uses a microcomputer which coherently integrates the transmitted signal. The principal idea is to 

exchange time for signal detectability. The receiver 

continually monitors the signal, and if it exists and is 

within the detectable range of the receiver, it will 

eventually be detected. This system was originally 

designed to detect signals transmitted from a depth of 

3000 ft and should be able to easily detect signals at a 

depth of 1000 ft in a few minutes of operation. Location is 

performed by vector calculation of the signal at a 

number of receiving-antenna locations. 

I0 I I I I I 

m 

- 

Summary 

J Q 

5 

m 

This paper has discussed the results of an extensive 

field-testing program to evaluate the performance of the 

EM trapped-miner transmitter. Analysis of the data 

obtained has provided a probabilistic framework from 

which signal detection can be predicted. It was found 

that for a 10% false alarm rate the probability of 

detection at 1000 and 500 ft is 54 and 95%, respectively. 

This information is vital for the future formulation and 

promulgation of new regulations written for the use of 

the EM system. Studies are underway to improve the 

detection capability by providing signal-processing 

capability to the receiver. 

2.- - PF& - 0 I0 

I I I I I 0 3 6 9 12 15 18 

SNR IMPROVEMENT, dB 

Fig. 18. Predicted probability of signal detection vs. SNR 

improvement by frequency for the GI transmitter lor a mine 

depth of 1000 ft. 
References 

C. L. Colburn, C. M. Bouton, and H. B. Freeman, "Underground 

Sianalincl With Radio Sets," Bureau of Mines Rept. of Investigations 

2437, 4 pp., 1922. 

J. J. Jakoskv. "Radio as a Method of Underaround Communications," Bureau of Mines Rept. of lnvestigatihs 2599, 4 pp., 1924. 

L. C. Ilsley, H. B. Freeman, and D. N. Zellers, "Experiments in 

Underground Communications Through Earth Strata," Bureau of 

Mines Tech. Progress Rept. 433, 60 pp., 1928. 

B. J. Howell, "Some effects of geologic structure on radio 

reception," Geophysics, vol. 8, no. 2, pp. 165-176, 1943. 

T. L. Wadley, "Radio Communication Through Rock in the 

Witwatersrand Mines," Council Sci. Ind. Res. (South Africa), 

Telecom. Research Lab. Rept. ETR-4, Aug. 1949. 

D. J. Vermeulen and P. J. Blignant, "Underground radio communication and its application for use in mine emergencies," Trans. S. 

Africa Inst. Elec. Eng., vol. 52, pt. 4, pp. 94-106, April 1961. 

B. A. Austin, "Underground Radio Communications Techniques 

and Systems in South African Mines," (NTIS PB289742/AS), March 

1978. 

E. J. Coggleshall, E. W. Felegy, and L. H. Harrison. "Some Studies 

in Emergency Mine Communications," Bureau of Mines Rept. of 

lnvestigations 4135, 44 pp., 1948. 

E. W. Felegy and E. J. Coggleshall, "Applicability of Radio to 

Emergency Mine Communication," Bureau of Mines Rept. of 

lnvestigations 4294, 57 pp., 1948. 

K. H. Carson and J. T. DeBettencourt, "Subsurface radio 

propagation experiments," Radio Sci., vol. 3, no. 11, pp. 

1039-1044, NOV. 1968. 

J. T. DeBettencourt and R. A. Sutcliffe, "Studies in Deep Strata 

Communications," Air Force Cambridge Res. Lab., Final Rept., 

Contract No. AF 19(604)-8359 Cambridge, MA, Oct. 1962. 

G. R. Dunn, P. F. Kuhnle, and R. D. Smith, Experimental Research, 

"Investigation of Extremely Low Frequency Propagation," Space 

General Corp., Final Rept., Contract No. AF 19 628 1603, 1964. 

R. N. Ghose, "Subsurfacecommunicationsfor survival," Electron., 

vol. 34, no. 3, pp. 43-45, 1961. 

National Academy of Engineering, "Mine Rescue and Survival," 

(NTIS PB 191-691), March 1970. 

Collins Radio, "Waveform Generator for EM Location of Trapped 

Miners," (NTIS PB 240 4811AS), 17 pp., 1974. 

David B. Large, Lawrence Ball, and Arnold J. Farstad, "Radio 

transmission to and from underground coal mines-theory and 

measurement,"lEEE Trans. Commun., COM-21, no. 3, pp. 194-202, 

March 1973. 

[I71 Westinghouse Corp.. "Reliability and Effectiveness Analysis of 

the USBM Electromagnetic Location System for Coal Mines," Final 

Re~t.. Bureau of Mines Contract J0166060. (NTIS PB82-201385). 

15i pp., Dec. 1978. 

[18] R. L. Lagace, J. Dobbie, T. Doerfler, W. Hawes, and R. Spencer. 

Technical SUDDO~~ of Throuah-the-Earth "Detection of Tra~~e

Miner ~lectromagnetic Signgs Above Coal Mines," ~ransmission 

Measurement Program, Arthur D. Little, Inc., Final Rept., Bureau 

of Mines Contract J0188037, (NTIS PB82-244732), 188 pp., June 

1980. 

[I91 J. Wait, "Subsurface electromagnetic fields of a circular loop of 

current located above the ground," IEEE Trans. Antennas 

Propagat., pp. 520-522, July 1972. 

[20] General lnstrument Corp., "Design to Specification and Fabrication of VF Transmitters and Baseband Receivers," Final Rept., 

Bureau of Mines Contract J0395017, (NTIS PB82-244260), Dec. 

1978. 

[21] M. D. Ristenbatt, Post-Disaster Communication Techniques," 

Univ. of Mich.. Final Rept., for Bureau of Mines Contract J0199109. 

99 pp., Dec. 1980. 

[22] Univ. Pittsburgh, "A Study for the Detection of Weak Electromagnetic Signal Bursts with Hard-Limited Arrays," Final Rept., 

Bureau of Mines Contract J0318033, Dec. 1980. 

[23] M. D. Ristenbatt, Personal correspondence, available for consultation at Pittsburgh Research Center, Bureau of Mines, 

Pittsburgh, PA, Feb. 3, 1980. 

[24] General lnstrument Corp., "Proposal to Improve Detection Capability of Trapped Miner EM Receiver," Proposal QR9067, available 

for consultation at Pittsburgh Research Center, Bureau of Mines, 

Pittsburgh, PA. March 1980. 

[25] Develco, "EM Rescue System for Deep Mines," Final Rept., Bureau 

of Mines Contract J0199009, May 1979. 

John Durkin received his B.S. degree in Electrical Engineering from 

Pennsylvania State University, and his M.S. and Ph.D. degrees in 

Electrical Engineering from the University of Pittsburgh. 

He joined the United States Bureau of Mines, Pittsburgh Research 

Center, Bruceton, PA, in 1970, and until 1975 worked in the area of 

instrumentation research in the fields of acoustic noise and nuclear 

radiation. Since 1975, he has been involved in the research and design 

of through-the-earth communications systems. More recently, his 

interest has been in the study of robotic visidn systems and artificial 

intelligence. 

Dr. Durkin is a Senior Member of the IEEE.