International Journal
on Marine Navigation
and Safety of Sea Transportation
Volume 5
Number 4
December 2011
441
1 INTRODUCTION
The reflected transmission signal can interfere with
the direct signal from the satellite to produce unac-
ceptable levels of signal degradation. In addition to
fading, signal degradations can include intersymbol
interference, arising from delayed replicas. The im-
pact of the impairments depends on the specific ap-
plication, namely in the case of typical Land MSC
(LMSC) links, all measurements and theoretical
analysis indicate that the specular reflection compo-
nent is usually negligible for path elevation angles
above 20o.
Moreover, for handheld terminals, specular re-
flections may be important as the low antenna di-
rectivity increases the potential for significant specu-
lar reflection effects. For Maritime MSC (MMSC),
LMSC and Aeronautical MSC (AMSC) system
links, design reflection multipath fading, in combi-
nation with possible shadowing and blockage of the
direct signal from the satellite, is generally the dom-
inant system impairment.
2 REFLECTION FROM THE EARTH’S
SURFACE
Prediction of the propagation impairments caused by
reflections from the Earth’s surface and from differ-
ent objects (buildings, hills, vegetation) on the sur-
face is difficult because the possible impairment
scenarios are quite numerous, complex and often
cannot be easily quantified. For example, the degree
of shadowing in LMSC satellite links frequently
cannot be precisely specified.
Therefore, impairment prediction models for
some complicated situations, especially for LMSC
links, tend to be primarily empirical, while more an-
alytical models, such as those used to predict sea re-
flection fading, have restricted regions of applicabil-
ity. Nevertheless, the basic features of surface
reflections and the resultant effects on propagating
signals can be understood in terms of the general
theory of surface reflections, as summarized in the
following classification:
1 Specular Reflection from a Plane Earth Here,
this effect is less than or equal to the coefficient
for horizontal polarization. Thus the polarization
of the reflected waves will be different from the
polarization of the incident wave if the incident
Surface Reflection and Local Environmental
Effects in Maritime and other Mobile Satellite
Communications
S. D. Ilcev
Durban University of Technology (DUT), Durban, South Africa
ABSTRACT: This paper introduces the effects of surface reflections and local environmental as very im-
portant particulars for mobile and especially for Maritime Satellite Communications (MSC), because such
factors generally tend to impair the performance of satellite communications links, although signal enhance-
ments are also occasionally observed. Local environmental effects include shadowing and blockage from ob-
jects and vegetation near the Ship Earth Station (SES) and other mobile terminals. The advantages and disad-
vantages of those effects are discussed, the areas of surface reflection were examined and
the further
investigations of local environmental are provided. At this point, surface reflections are generated either in the
immediate vicinity of the SES terminals or from distant reflectors, such as mountains and large industrial in-
frastructures. Specific issues related to these challenges are concluded and a set of solutions is proposed to
maximize the availability of satellite communication capacity to the mobile user applications. The specific ef-
fects on propagation in the mobile environments are examined and explained important characteristics of the
Interference from Adjacent Satellite Systems, Specific Local Environmental Influence in MSC, different
Noise Contribution of Local Ships’ Environment, Blockages Caused by Ship Superstructures and Motion of
Ship’s Antenna.
442
polarization is not purely horizontal or purely ver-
tical. For example, a circularly polarized incident
wave becomes elliptically polarized after reflec-
tion.
2 Specular Reflection from a Smooth Spherical
Earth Here, the incident grazing angle is equal
to the angle of reflection. The amplitude of the re-
flected signal is equal to the amplitude of the in-
cident signal multiplied by the modules of the re-
flection coefficient.
3 Divergence Factor When rays are secularly re-
flected from a spherical surface, there is an effec-
tive reduction in the reflection coefficient, which
is a geometrical effect arising from the diver-
gence of the rays.
4 Reflection from Rough Surface In many practi-
cal cases, the surface of the Earth is not smooth.
Namely, when the surface is rough, the reflected
signal has two components: one is a specular
component, which is coherent with the incident
signal, while the other is a diffuse component,
which fluctuates in amplitude and phase with a
Rayleigh distribution.
5 Total Reflected Field The total field above a re-
flecting surface is a result of the direct field, the
coherent specular component and the random dif-
fuse component.
6 Reflection Multipath Owing to the existence of
surface reflection phenomena signals may arrive
at a receiver from multiple apparent sources.
Thus, the combination of the direct signal (line-
of-sight) with specular and diffusely reflected
waves causes signal fading at the receiver. The
resultant multipath fading, in combination with
varying levels of shadowing and blockage of the
line-of-sight components, can cause the received
signal power to fade severely and rapidly for
MES and is really the dominant impairment in the
Global Mobile Satellite Communications
(GMSC) service.
3 FADING IN MMSC AND AMSC SYSTEMS
DUE TO SEA SURFACE REFLECTION
Multipath fading due to sea reflection is caused by
interference between direct and reflected radio-
waves. The reflected radiowaves are composed of
coherent and incoherent components, namely specu-
lar and diffuse reflections, respectively, that fluctu-
ate with time due to the motion of sea waves. The
coherent component is predominant under calm sea
conditions and at low elevation angles, whereas the
incoherent becomes significant in rough sea condi-
tions. If the intensity of the coherent component and
the variance of the incoherent component are both
known, the cumulative time distribution of the signal
intensity can be determined by statistical considera-
tion.
In any event, a prediction model for multipath
fading due to sea reflection, however, was first de-
veloped for MMSC systems at a frequency near 1.5
GHz. Although the mechanism of sea reflection is
common for MMSC and AMSC systems, only with
the difference that fading characteristics for AMSC
are expected to differ from those for MMSC, this is
because the speed and altitude of aircraft so much
greater than those of ships. At this point, the effects
of refractions and scattering by the sea surface be-
come quite severe in case of MMSC and AMSC,
particularly where antennas with wide beam widths
are used.
The most common parameter used to describe sea
condition is the significant wave height (H), defined
as the average value of the peak-to-trough heights of
the highest one-third of all waves. Empirically, H is
related to the r.m.s. height (h
o
) by:
H = 4h
0
Hence, at 1.5 GHz the smaller-scale waves can be
neglected and the r.m.s. value of the sea surface
slopes appear to fall between 0.04 to 0.07 in the case
of wave heights less than 4 m.
Thus, with diminishing satellite elevation angle,
the propagation path increases, causing a decrease of
signal power at the Rx side. The noise level is ini-
tially constant; however, upon reaching some critical
value of the elevation angle, sea-reflection signals
appear at the Rx input, which begins to affect the
C/N value. To include the effect of multipath inter-
ference caused by sea-refracted signals, the recep-
tion quality would be more properly described by
the C/N plus M, where M is an interfering sea-
reflected signal acting as a disturbance. Thus, sea-
reflected signals differ in structure and can be divid-
ed into two categories:
1 Radio signals with the rapid continuous fluctua-
tions of amplitudes and phases and with a possi-
ble frequency shift due to the motion of small
portions of the specular cross-section relative to
the source of signals (noise or diffused compo-
nents).
2 Radiowaves with relatively slowly changing
phase close to the phase of the basic signal and
with an amplitude correlating with that of the
basic signal (specular component).
Consequently, within the overall specular cross-
section, an angle of arrival reflected radio signals
relative to the horizontal plane may be regarded as
constant and can be described by the following ex-
pression:
α = 90
o
γ
where α = angle of radio signals arrival in accord-
ance with Figure 1. and γ = reflection angle. The
modulus of sea reflection factor for L-band signals is
443
within 0.8 and 0.9, which means that the amplitude
of the specular reflected signal is nearly the same as
that of the direct signal. As measurements have
shown, the noise component depends only upon an
elevation angle and a wave height. Decreasing the
elevation angle and increasing the wave height result
in an increase in the total amplitude of the noise,
which includes the noise component. At elevation
angles below 5
o
, the amplitude component reaches a
peak value and is no longer affected by the wave
height. Now an increase of the wave height causes
primarily more frequent variations in the noise com-
ponent. The corresponding deviation of C.N meas-
ured in 1 kHz bandwidth amounts from 4.5 to 5 dB.
Figure 1. Geometry of Sea Reflection of Satellite Radio Signals
Courtesy of Book: “Global Mobile Satellite Communications”
by D.S. Ilcev
The specular component that appears at the Rx
input together with the direct signal causes fading in
the direct signal due to both the minor difference be-
tween their phases and the slow change of the pa-
rameters of the reflected signals. The ratio of the di-
rect to specular reflected signal can be described as:
C/M = (C + G
ε
) [C G
+ ε)
]
where C = direct signal; M = specular reflected sig-
nal power from the sea; G
ε
= maximum gain of the
receive SES antenna pointing towards the satellite; ε
= elevation angle and α, as is shown in Figure 1. In
addition, keeping accuracy sufficient for practical
purposes, the previous relation gives:
C/M = β
C/N
+ [G
ε
G
+ ε)
]
where β
C/N
= deviation of C/N ratio. With decreasing
elevation angle, the C/M diminishes monotonically,
except for the elevation angle range of 5
o
to 8
o
, with-
in which a rise in C/N is observed. This is obviously
due to the fact that at the said angles the difference
in path between the direct and the specular signal
becomes negligible, so that conditions appears close
to the summation of the similar signals at the receiv-
er input. An increase of the C/N plus M ratio is ob-
served simultaneously due to reaching a peak value
of amplitude in the noise (diffused) component. In
fact, experimental measurements show that as the
elevation angle decreases from 10
o
to 1
o
, the mean
C/N plus M diminishes from 2224 dB to 1718 dB,
with the deviation increasing from 1.52 dB to 4.55
dB.
4 MULTIPATH FADING CALCULATION
MODEL FOR REFLECTION FROM THE SEA
The amplitude of the resultant signal at the SES ter-
minal, being the sum of the direct wave component,
the coherent and the incoherent reflection compo-
nents, has a Nakagami-Rice distribution (see ITU R
P.1057). The cumulative distribution of fading de-
pends on the coherent-to-incoherent signal intensi-
ties. For example, in the case of rough sea conditions
at 1.5 GHz, the coherent reflection from the sea is
virtually non-existent and the coherent signal is
composed only of the direct component. Therefore,
the fading is determined by the Carrier-to-Multipath
ratio (C/M), i.e., the power ratio of the direct signal
and multipath component caused by incoherent re-
flection. The maximum fade depth
max
) occurs
when the coherent multipath signal is in anti-phase
with the direct signal, given by:
Φ
max
= – 20 log (1 – A
r
) [dB]
where A
r
= amplitude of the coherently reflected
component. The value decreases rapidly with in-
creasing wave height, elevation angle and RF. In
practice, due to the vertical motion of the ship an-
tenna relative to average sea surface height, the max-
imum fade value will seldom occur. By adding Φ
max
and Φ
i
(p) as signal fade due to the incoherent com-
ponent in the function of time percentage (p), a prac-
tical estimate of the combined fading effects of the
coherent and incoherent multipath signal for sea
conditions is obtained:
Figure 2. Estimates of Coherent Reflection and Multipath
Power
Courtesy of Book: “Mobile Antenna Systems Handbook” by
K. Fujimoto and J.R. James
Φ
c
= Φ
max
+ Φ
i
(p)
444
The maximum fade value due to the coherent
component will not occur constantly because of the
vertical motion of the ship antenna relative to aver-
age sea surface height; therefore, the estimate using
this equation seems to give the worst-case value. In
practice, for low elevation angles (les than 10
o
) at
around L-band frequencies, the maximum fading oc-
curs when the significant sea wave height is between
1.5 and 3 m, where the coherent reflected compo-
nent is negligible. Accordingly, the dependence of
fading depth on wave height in this range is relative-
ly small.
The amplitude level of the coherent component
decreases rapidly with increasing sea wave height,
elevation angle and frequency. Figure 2. (A) illus-
trates the relationship between coherent reflection
and significant wave height. Namely, estimates of
amplitude of the coherent component for an omnidi-
rectional antenna as a function of a significant wave
height for low elevation angles are illustrated; the
frequency is 1.5 GHz and polarization is circular.
Thus, the incoherent component is random in both
amplitude and phase, since it originates from a large
number of reflecting facets on the sea’s waves. The
amplitude of this component follows Rayleigh dis-
tribution and the phase has a uniform distribution.
Since the theoretical model concerning the inco-
herent components is not suitable for engineering
computations using a small calculator, simpler pre-
diction models are useful for the approximate calcu-
lation of fading. Such simple methods for predicting
multipath power or fading depth have been recently
developed. Thus, in Figure 2. (B) is presented the re-
lationship between multipath power and elevation
angle for different antenna gains. Although fading
depth depends slightly on sea surface conditions,
even if the incoherent is dominant, the simple model
is useful for a rough estimate of fading depth.
Fading depth, which is a scale of intensity of fad-
ing, is usually defined by the difference in decibels
between the direct wave signal level and the signal
level for 99% of the time. The fading depth can be
approximated by a 50% to 99% value for fading
where the incoherent component is fully developed.
Large fading depths usually appear in rough sea
conditions, where the incoherent component is dom-
inant. Thus, Figure 3. (A) shows the fading depth es-
timated by the simple method for antenna not ex-
ceeding for 99% of the time and the corresponding
C/M ratio for circular polarization at 1.5 GHz band
under the condition of significant wave heights from
1.5 to 3 m. The antenna gains of 24, 20, 15 and 8 dB
are functions of elevation angle with a fully-
developed incoherent component. The calculation is
based on the theoretical method, where the shaded
area covers the practical range of the sea wave slope,
which depends on fading depth in rough sea condi-
tions. Values estimated by this simple method give
the mean values of those given in Figure 3. (B).
On the other hand, as the theoretical model is not
suitable for engineering computations using a small
calculator, these simple prediction models are really
useful for the approximate calculation of fading or
interference. Such simple methods for predicting
multipath power or fading depth have been devel-
oped by Sandrin and Fang [1986] and by Karasawa
and Shiokawa [1988] for MMSS and Karasawa
[1990] for AMSS.
Furthermore, the frequency spectral bandwidth of
temporal amplitude variations enlarges with increas-
ing wave height and elevation angle. Figure 3. (B)
shows the probable range of 10 dB spectral band-
width (which is defined by the frequency corre-
sponding to the spectral power density of 10 dB
relative to the flat portion of power spectrum) of L-
band multipath fading obtained by the theoretical
fading model as a function of the elevation angle
under the usual conditions of MMSC; namely, sig-
nificant wave height of 1 m to 5 m, ship speed of 0
to 20 knots and rolling conditions of 0 to 30
o
.
Figure 3. Estimates of Fading Depth and Spectral Bandwidth
Courtesy of Book: “Mobile Antenna Systems Handbook” by
K. Fujimoto and J.R. James
5 OTHER ESTIMATIONS OF FADING FOR
MMSC AND AMSC SYSTEMS
The error pattern in digital transmission systems af-
fected by multipath fading is usually of the burst
type. Accordingly, a firm understanding of the fade
duration statistics of burst type fading is required.
Mean value of fade duration
D
) and fade occur-
rence interval
o
) for a given threshold level as a
function of time percentage, can be estimated from
the fading spectrum. A simple method for predicting
the mean value from the 10 dB spectral bandwidth
is available as a theoretical fading model.
Predicted values of (Φ
D
) and (Φ
o
) for 99% of the
time at an elevation angle from 5 to 10
o
are 0.05 to
0.4 sec for
D
) and 5 to 40 sec for
o
). The proba-
bility density function of
D
) and (Φ
o
) at any per-
centages ranging from 50% to 99% approximates an
exponential distribution.
445
1 Simple Prediction Method of Fading Depth Ac-
cording to theoretical analysis and experimental
results made by the mentioned researchers in Ja-
pan, the lowest elevation angle Earth-to-space
path at 1.5 GHz RF band satisfies the energy con-
servation law: [Power of coherent component] +
[Average power of incoherent component] ~
Constant. If this expression is satisfied, the max-
imum incoherent power can be estimated easily
by calculating the coherent power at u = 0. Oth-
erwise, for a more accurate estimation, small
modifications of some parameter dependencies
are necessary. The modified procedure has been
adopted in P.680 for MMSC and P.682 ITU-R
Recommendations for AMSC. Figure 4. (A)
shows a scattergram of measured and predicted
fading depths (i.e., fade for 99% of the time rela-
tive to that for 50%) in the case of MMSC sys-
tems between measured data and predicted values
derived from the simple calculation method with
the same conditions. In this figure, Φ
dp2
are values
from the method set out in ITU-R P.680, while
Φ
dp1
are those from an alternative procedure of
the prediction method for scattering angles. It is
evident that the values given by these methods
agree well with the experimental values although
the methods are rather approximate.
Figure 4. Scattergram and Altitude Dependence of Fading
Depth Courtesy of Handbook: “Radiowave Propagation Infor-
mation for Predictions for Earth-to-Space Path Communica-
tions” by ITU
Figure 5. Typical LMSC Propagation Environment
Courtesy of Book: “Mobile Satellite Communications” by S.
Ohmori and other
In Figure 4. (B) is shown the altitude dependence
of signal fade depth not exceeded for 99% of the
time vs. antenna height on board ships or aircraft.
This experiment was obtained from measure-
ments with a helicopter together with the calcu-
lated values from the simple estimation method of
the solid line and the theoretical model of the
shaded region in the figure. From the figure it can
be seen that the simple prediction method agrees
well with both the theoretical model and meas-
ured data even in the case of the AMSC system.
2 Fading Spectrum In system design, particularly
for digital transmission systems, it is important
not only to estimate the fading depth but also to
know the properties of temporal variation, such as
the frequency power spectrum. For MMSC sys-
tems, theoretical analyses were carried out in Ja-
pan and all parameters affecting the spectrum
such as wave height, wave direction, ship’s direc-
tion and velocity, path elevation angle and anten-
na height variations due to ship’s motion (rolling
and pitching) were taken into account. In general,
spectrum bandwidth is broader with increasing
wave height, elevation angle, ship velocity and
the relative motion of the ship borne antenna. The
dependence of the spectral shape on antenna po-
larization and gain is usually very small. Moreo-
ver, since the speed of aircraft is significantly
higher than that of ships, the fluctuation speed of
multipath fading in AMSC is much faster than
that in MMSC, depending on the flight elevation
angle measured from the horizontal plane. The
calculated 10 dB spectral bandwidth is between
20 and 200 Hz for elevation angles of 5
o
to 20
o
,
for flight elevation angles 0
o
to 5
o
at a speed of
1,000 km/h.
6 FADING IN LMSC SYSTEM DUE TO SIGNAL
BLOCKAGE AND SHADOWING
Recently, in the USA, Canada, Australia, Japan and
Europe, domestic LMSC and GMPSC services have
started. The main purpose of these systems is to ex-
tend MSC voice services to rural/remote areas where
terrestrial/cellular services are not provided. In a
typical urban environment, line-of-sight for cellular
systems sometimes is not available due to blockage
by buildings and other structures, when a MES can
receive many waves reflected from these structures
and conduct communication link using these signals.
446
Figure 6. Loss due to Knife-Edge Diffraction
Courtesy of Handbook: “Radiowave Propagation Information
for Predictions for Earth-to-Space Path Communications” by
ITU
Figure 7. Geometry of Knife-edge Diffraction Phenomena
Courtesy of Handbook: “Radiowave Propagation Information
for Predictions for Earth-to-Space Path Communications” by
ITU
The LMSC system can be expected to use the di-
rect line-of-sight signal from a satellite because of
the high elevation angles. When the line-of-sight is
blocked by any obstacle, MSC is not available, but
using path diversity the link is available because of
overlapping of two or more signal from adjacent sat-
ellites. At present, path diversity from separate satel-
lites is rarely used for GEO MSS, but Non-GEO
MSS have an inherent capability to exploit diversity,
because the number of satellites is large providing
path diversity. At this point, Figure 5. presents a
typical propagation environment for scattering, mul-
tipath fading, shadowing, diffusion, ect.
Therefore, to design LMSC system, one needs in-
formation about the propagation statistics of multi-
path fading and shadowing. A vehicle runs at a dis-
tance of 5 to 20 m from roadside obstacles using an
omnidirectional antenna, which has azimuthally uni-
form gain but elevation directivity, or a medium or
high-gain antenna with automatic tracking capabil-
ity. Thus, signal blockage and shadowing effects oc-
cur when an obstacle, such as roadside trees, over-
passes, bridges, tunnels, utility poles, high buildings,
hills or mountains, impedes visibility to the focus of
satellite. This results in the attenuation of the re-
ceived signal to such an extent that transmissions
meeting a certain quality of service may not be pos-
sible. At any rate, in the shadowing environments
the presence of the trees will result in the random at-
tenuation of the strength of the direct path signal.
Hence, the depth of the fade is dependent on a num-
ber of parameters including tree type, height, as well
as season due to the leaf density on the trees.
Whether a VES is transmitting on the left or right-
hand side of the road could also have a bearing on
the depth of the fade, due to the line-of-sight path
length variation through the tree canopy being dif-
ferent for each side of the road. In fact, fades of up
to 20 dB at the L-band may be presented due to
shadowing caused by roadside trees. This shadowing
by roadside trees cannot occur on modern highways
because they are free of trees, only sometimes can
shadowing appear by tunnels, very big construc-
tions, bridges and mountains or hills in narrow pas-
sages.
1 Tree Shadowing Attenuation due to trees near-
by the roads arises from absorption by leaves and
blockage by trunks and branches. Absorption by
leaves is a function of the type and size of leaves
and the water content therein. Blockage due to
trunks is primarily a function of their size. In ad-
dition to attenuation of the direct signal, trees also
cause an incoherent component due to signals re-
flected and diffracted off the tree surfaces.
The overall attenuation from different types of
fully foliated trees varies from 10.6 to 14.3 dB
and the attenuation coefficient is from 1.3 to 1.8
dB/m. Measurements were conducted with MES
Rx in a rural environment. Based on these aver-
age values, a frequency scaling law for the atten-
uation coefficient has been derived [Goldhirsh
and Vogel] by:
a
1
= a
0
√f
1
/f
0
[dB/m]
where a
1
and a
0
= attenuation coefficients at fre-
quencies f
1
and f
0
[GHz], respectively. Hence, the
range of variation for a
1
at 1.5 GHz is from 0.5 to
1.7 dB/m. Moreover, trees without foliage attenu-
ate less and the reduction in attenuation appears
to be proportional to the total attenuation experi-
enced when the tree is fully foliated. The received
strength of the direct signal behind a tree will de-
pend on the orientation of the signal path with re-
spect to the tree. The amount of absorbing matter
lying along the path will determine the degree of
attenuation and hence, on average, the length of
the signal path through the tree shield can be con-
sidered a major factor in determining the signal
level. The path length is a function of the eleva-
tion angle and the distance between the receiver
and the tree. At this point, the average attenuation
behind an isolated tree can be estimated as the
product of the attenuation coefficient and the path
length through the tree. The path length through
the tree canopy will depend on its shape and the
orientation of the signal path within the canopy.
Depending on the type being considered, the tree
canopy may be modeled as any one of the shapes.
447
Figure 8. Ocean Mean-Square Scatter Coefficients vs. Eleva-
tion
Courtesy of Handbook: “Radiowave Propagation Information
for Predictions for Earth-to-Space Path Communications” by
ITU
For the intermediate elevation angle (20
o
to 50
o
),
attenuation is almost independent of elevation
and dependence becomes important only at the
higher and lower ends of the elevation angle
range. By considering the path length variability
as a statistical parameter, however, a tree can be
modeled as giving an average attenuation and a
distribution around it. Both the coherent and in-
coherent components will vary with the receiver
position and complete decorrelation of the signal
is expected over distances in the order of a few
wavelengths.
2 Building Shadowing Signal reception behind
buildings takes place mainly through diffraction
and reflection. A direct line-of-sight component
does not usually exist and therefore shadowing
cannot be defined unambiguously, as in the case
of trees. However, shadowing may be loosely de-
fined as the power ratio between the average sig-
nal levels to the unscheduled direct signal level.
Otherwise, diffractions from buildings can be
studied using knife-edge diffraction theory, which
gives reasonable estimates. A concept view of
knife-edge diffraction phenomena is shown in
Figure 6. for all losses caused by the presence of
the obstacles as a function of a dimensionless pa-
rameter ν and in Figure 7., which illustrates the
geometry of the path for both the illuminated (A)
and shadowed cases (B), in order to calculate the
parameter ν, by using elevation and wavelength
as follows:
ν = ε √2/[λ(1/d
1
+ 1/d
2
)] but d
1
>> d
2
,
so: ν = ε
√2/λ (1/d
2
) = ε √2d
2
The signal strength at the shadow boundary is 6
dB below the line-of-sight level. In the illuminat-
ed region, the signal fluctuations are experienced
due to interference between the direct and the dif-
fracted components. Hence, once inside the shad-
owed region, the shadow increases rapidly. An
experimental investigation into building shadow-
ing loss conducted by Yoshikawa and Kagohara
in 1989 confirmed the applicability of the knife-
edge diffraction theory. Measured signal strength
behind a building at various distances was found
to follow the prediction made, assuming a single
diffraction edge. However, where the building is
narrow compared with its height, there may be
significantly less shadowing than predicted by the
above procedure. When the direct signal path is
blocked by a building, diffractions of the build-
ings are not expected to play a dominant role in
establishing the communication link, unless MES
is close to the shadow boundary. Reflections may
play a useful role in such situations, as happens in
cellular systems. Building penetration depends on
the type of exterior material of the building and
the location inside the building. Thus, the loss
through the outer structure, known as the penetra-
tion loss, is defined as the difference in median
signal levels between that measured immediately
outside the building at 1.5 m above the ground
and that immediately inside the buildings at some
reference level on the floor of interest.
Measurements made at 940 MHz in a medium-
size city in the USA indicate that on the ground
floor of typical steel-concrete-stone office build-
ings, the average penetration is about 10 dB with
a standard deviation of about 7 dB. While another
set of measurements in a large city resulted in av-
erage ground floor penetration loss of 18 dB with
a standard deviation of 7.7 dB. However, the
overall decrease of penetration loss with height
was about 1.9 dB per floor. The biggest average
attenuations are 12 dB and 7 dB and standard de-
viations are 4 db and 1 dB for metal and concrete,
respectively.
Figure 9. Basic Model for Intersatellite Interferences Phenom-
ena
Courtesy of Handbook: “Radiowave Propagation Information
for Predictions for Earth-to-Space Path Communications” by
ITU
Attenuation through glass ranges from about 2 to
6 dB depending on the type of glass, i.e., plain glass
produces less attenuation compared to tinted or coat-
ed glass, containing metallic components. Other-
wise, the smallest average attenuation is through of-
fice furnishings, aluminum and wood/brick of about
1, 2 and 3 dB, respectively. Losses within a building
are both of distance from the exterior wall blocking
the signal path, as well as the interior layout. Meas-
urements have resulted in an inverse distance power
448
law coefficient ranging from 2 to 4. The forthcoming
ICO system has conducted experiments with satel-
lite-borne signals whose final target is to improve
and even to eliminate building shadowing.
7 FADING IN AMSC SYSTEM DUE TO LAND
REFLECTION
An experiment aboard a helicopter over land was
carried out by receiving right-hand circularly polar-
ized 1.5 GHz beacon signals from an IOR Marisat
satellite at an elevation angle of 10
o
. Fading depths
measured over plains such as paddy fields were fair-
ly large (about 5 dB), nearly equal to that for sea re-
flection. However, fade depths measured over
mountainous and urban areas were less than 2 dB. In
the case of mountains, reflected waves are more
likely to be shadowed or diffused by the mountains.
As to urban areas, the shadowing and diffusing ef-
fects of reflected wave by buildings are also large.
For this reason, the ground reflected multipath fad-
ing in these cases is not generally significant.
Measurements of Sea-Reflection Multipath Effect
A study of multipath propagation at 1.5 GHz was
performed with KC-135 aircraft and the NASA
ATS-6 satellite. Otherwise, the signal characteristics
were measured with a two-element waveguide array
in the aircraft noise radome, with 1 dB beam width
of 20
o
in azimuth and 50
o
in elevation. Namely, data
was collected over the ocean and over land at a nor-
mal aircraft altitude of 9.1 km and with a nominal
speed of 740 km/h. Coefficients for horizontal and
vertical antenna polarization were measured in an
ATS-6 experiment, where values for r.m.s. sea sur-
face slopes of 3o and 12o were plotted versus eleva-
tion angle, in Figure 8., along with predictions de-
rived from a physical optics model. Sea slope was
found to have a minor effect for elevation angles
above about 10
o
. The agreement between measured
coefficients and those predicted for a smooth flat
Earth as modified by the spherical Earth divergence
factor increased as sea slope decreased.
The relationship between r.m.s. sea surface and
wave height is complex but conversion can be per-
formed. Namely, for most aeronautical systems, cir-
cular polarization will be of greater interest than lin-
ear. For the simplified case of reflection from a
smooth Earth, which should be a good assumption
for elevation angles above 10
o
, circular co-polar and
cross-polar scatter coefficients (S
c
and S
x
), respec-
tively, can be expressed in terms of the horizontal
and vertical coefficients (S
h
and S
v
), respectively by:
S
c
= (S
h
+ S
v
)/2 and S
x
+ (S
h
– S
v
)/2
For either incident RHCP or LHCP is employed.
Thus in general, the horizontal and vertical coeffi-
cients are complex values and phase information is
required to apply the last equitations to the curve, in
Figure 8.
8 INTERFERENCE FROM ADJACENT
SATELLITE SYSTEMS
In GMSC systems for ships, vehicles and aircraft,
small mobile antennas are essential for operational
and economic reasons. As a result, a number of low
G/T value MES terminals with smaller antennas
have been developed. However, such antenna sys-
tems are subject to the restriction of frequency utili-
zation efficiency, or coexistence between two or
more satellite systems in the same frequency band
and/or an overlap area where both satellites are visi-
ble.
Figure 10. Geometry of Blocking
Courtesy of Handbook: “Radiowave Propagation Information
for Predictions for Earth-to-Space Path Communications” by
ITU
For coordination between two different systems
in the same frequency band, a highly reliable inter-
ference evaluation model covering both interfering
and interfered with conditions is required. Investiga-
tion into this area has been undertaken in particular
by ITU-R Study Group 8. Advancement of such a
model is an urgent matter for the ITU-R considering
the number of MSC systems that are being devel-
oped in the meantime.
In GMSC systems, the desired signal from the
satellite and the interfering signal from an adjacent
satellite independently experience amplitude fluctua-
tions due to multipath fading, necessitating a differ-
ent treatment from that for fixed satellite systems.
The main technical requirement is a formulation for
the statistics of differential fading, which is the dif-
ference between the amplitude of the two satellite
signals. At this point, the method given in No 5 of
ITU-R P.680 Recommendation therefore presents a
practical prediction method for signal-to-
interference ratio where the effect of thermal noise
and noise-like interference is taken into account; as-
suming that the amplitudes of both the desired and
interference signal affected by the sea reflected mul-
tipath fading follow NakagamiRice distributions. In
449
fact, this situation is quite probable in MMSC sys-
tems.
The basic assumptions of the intersatellite model
are shown in Figure 9., as an example of interference
between adjacent satellite systems, where (A) is
downlink interference on the MES side and (B) is
uplink interference on the satellite side. This applies
to multiple systems sharing the same frequency
band. It is anticipated that the interference causes an
especially severe problem when the interfering satel-
lite is at a low elevation angle viewed from the ship
presented in this figure because the maximum level
of interference signal suffered from multipath fading
increases with decreasing elevation angle. Another
situation is interference between beams in multi-
spot-beam operation, where the same frequency is
repeatedly allocated.
9 SPECIFIC LOCAL ENVIRONMENTAL
INFLUENCE IN MMSC
Local environmental influence is important for SES
equipped with beam width antenna. Many factors,
with different kinds of noise sources, tend to make
disturbances in MMSC channels. Another factor that
affects communication links is RF emission from
different noise sources in the local environment.
Specific local ship environmental factors can be
noise contributions from various sources in the vi-
cinity of the SES and the influence of the ship’s su-
perstructure in the operation of maritime mobile
terminals. However, some of these local environ-
mental factors can affect SES when a ship is passing
nearby the coast and, some of these are permanent
noise sources. More exactly, these environmental
sources include broadband noise sources, such as
electrical equipment and motor vehicles and out-of-
band emission from powerful transmitters such as
radars and ships HF transmitters.
9.1 Noise Contribution of Local Ships’
Environment
Some of the noise contributions from the local ships’
environment are as follows:
1 Atmospheric Noise from Absorption Absorbing
atmospheric media, such as water vapor, precipi-
tation particles and oxygen emit thermal noise
that can be described in terms of antenna noise
temperature. These effects were discussed at the
beginning of this chapter.
2 Industrial Noise Heavy electrical equipment
tends to generate broadband noise that can inter-
fere with sensitive receivers. Therefore, a high
percentage of this noise originates as broadband
impulsive noise from ignition circuits. Namely,
the noise varies in magnitude by as much as 20
dB, depending on whether it is measured on a
normal working day or on weekends and holidays
when it is lower in magnitude.
3 Out of Band Emission from Radar Ship borne
and surveillance radars operating in pulse mode
can generate out of band emission that can inter-
fere with SES receivers. In general, such emis-
sions can be suppressed by inserting waveguide
or coaxial filters at the radar transmitter output.
Figure 11. Estimated Attenuation due to Blocking
Courtesy of Handbook: “Radiowave Propagation Information
for Predictions for Earth-to-Space Path Communications” by
ITU
4 Interference from High Power Communication
Transmitters High power ships and terrestrial
transmitters, for example HF ship radio transceiv-
ers; HF radio diffusion and TV broadcasting can
interfere with SES.
5 Interference from Vehicles Under certain opera-
tional conditions, RF emissions from vehicles
may impair Rx sensitivity. Accordingly, in one
measurement the noise emanating from heavy
traffic has to be about 150dB (mW/Hz) within
the frequency band 1.535 to 1.660 MHz.
6 Shipyard Noise Extremely high peak ampli-
tudes of noise of 141 dB (mW/Hz) were record-
ed from Boston Navy Yard, which was in full op-
eration at that time. Thus, this noise is also a
combination of city ambient noise and broadband
electromagnetic noise from industrial equipment.
9.2 Blockages Caused by Ship Superstructures
Ship’s superstructures can produce both reflection
multipath and blockage in the direction of the satel-
lite. For the most part, reflections from the ship’s
superstructure located on the deck can be considered
coherent with the direct signal. The fading depth due
to these reflections depends on a number of con-
struction parameters including shape of the ship, lo-
cation of the ship’s antenna, antenna directivity and
sidelobe level, axial ratio and orientation of the po-
larization ellipse, azimuth and elevation angles to-
wards the satellite, etc. Antenna gain has a signifi-
cant influence on the fading depth. In this case, low
gain antennas with broader beam widths will collect
450
more of the reflected radio signals, producing deeper
fades.
Blockage is caused by ship superstructures, such
as the mast and various types of antennas deployed
on the ship. The geometry of blockage by a mast is
presented in Figure 10. Signal attenuation depends
on several parameters including diameter of column,
size of antenna and distance between antenna and
column. Accordingly, estimated attenuation due to
blocking by a column type structure is shown in
Figure 11 for antenna gains of 20 dB (A) and 14 dB
(B), respectively.
9.3 Motion of Ship’s Antenna
The motion of mobile satellite antennas is an im-
portant consideration in the design of MMSC sys-
tems. The received signal level is affected by the an-
tenna off-beam gain because the antenna motion is
influenced by the ship’s motion. The random ship
motion must be compensated by a suitable stabiliz-
ing mechanism to keep the antenna properly pointed
towards the satellite. This is normally achieved ei-
ther through a passive gravity stabilized platform or
an active antenna tracking system. In either case, the
residual antenna pointing error can be significant
enough to warrant its inclusion in the overall link
calculation.
Earlier experimental evidence suggests that the
roll motion of a ship follows a zero mean Gaussian
distribution over the short-term of the sea waves.
The standard deviation of the distribution
s
)
is a
function of the vessel characteristics and the sea
state of the wave height. In Figure 12 is illustrated
the distribution of the instantaneous roll angle of a
ship under moderate to rough sea conditions. The
distribution of the ship motion approximates to a
Gaussian standard deviation of distribution with σ
s
=
5.42 value.
Also shown in the figure is the distribution of roll
angle of a passively stabilized antenna under the
same conditions, which also follows a zero mean
Gaussian distribution with a quantum of σs = 0.99.
Solid curves in Figure 5.17. represent measured val-
ues and dashed curves show calculated values for
stabilized antenna motion over the sea conditions
with wave heights of approximately 5 m.
Figure 12. Measured Stabilized Antenna Motion
Courtesy of Handbook: “Radiowave Propagation Information
for Predictions for Earth-to-Space Path Communications” by
ITU
Otherwise, the relation between the standard de-
viations of the two distributions depends on the de-
sign of the passive stabilizer. Although the ship’s an-
tenna motion is much reduced, depending on the
antenna beam width, the residual pointing error may
be large enough to produce appreciable signal fluc-
tuations. Over a long period of sea waves time σs
varies as a function of the sea surface conditions and
its distribution can be approximately by either a log
normal distribution or a Weibull distribution.
10 CONCLUSION
The common satellite channel environment affects
radiowave propagation in changeless ways. The dif-
ferent parameters influenced are mainly path attenu-
ation, polarization and noise. The factors to be con-
sidered are gaseous absorption in the atmosphere,
absorption and scattering by clouds, fog, all precipi-
tation, atmospheric turbulence and ionospheric ef-
fects. In this sense, several measurement techniques
serve to quantify these effects in order to improve
reliability in the system design. Because these fac-
tors are random events, GMSC system designers
usually use a statistical process in modeling their ef-
fects on radiowave propagation. To design an effec-
tive GMSC model it is necessary to consider the
quantum of all propagation characteristics, such as
signal lost in normal environment, path depolariza-
tion causes, transionospheric contribution, propaga-
tion effects important for mobile systems, including
reflection from the Earth’s surface, fading due to sea
and land reflection, signal blockage and to the dif-
ferent local environmental interferences for all mo-
bile and handheld applications. At any rate, the local
propagation characteristics on the determinate geo-
451
graphical position have very specific statistical pro-
prieties and results for ships, vehicles and aircraft.
REFERENCES
[01] Evans B.G., “Satellite communication systems”, IEE,
London, 1991.
[02] Freeman R.L., “Radio systems design for telecommunica-
tions (1-100 GHz)”, John Wiley, Chichester, 1987.
[03] Fujimoto K. & other, “Mobile antenna systems hand-
book”, Artech House, London, 1994.
[04] Galic R., “Telekomunikacije satelitima”, Skolska knjiga,
Zagreb, 1983.
[05] Group of authors, “Handbook - Mobile Satellite Service
(MSS)”, ITU, Geneva, 2002.
[06] Group of authors, “Handbook on Satellite Communica-
tions”, ITU, Geneva, 2002.
[07] Group of authors, “Morskaya radiosyaz”, Transport, Len-
ingrad, 1985.
[08] Group of authors, “Radiowave propagation information
for predictions for earth-to-space path communications”,
ITU, Geneva, 1996.
[09 Ilcev D. St. “Global Mobile Satellite Communications for
Maritime, Land and Aeronautical Applications”, Book,
Springer, Boston, 2005.
[10] Maral G. & other, “Satellite communications systems”,
John Wiley, Chichester, 1994.
[11] Novik L.I. & other, “Sputnikovaya svyaz na more”, Su-
dostroenie, Leningrad, 1987.
[12] Ohmori S. & other, “Mobile satellite communications”,
Artech House, BostonLondon, 1998.
[13] Richharia M., “Mobile Satellite Communications Prin-
ciples and Trends”, Addison-Wesley, Harlow, 2001.
[14] Sheriff R.E. & other, “Mobile satellite communication
networks”, Wiley, Chichester, 2001.
[15] Zhilin V.A., “Mezhdunarodnaya sputnikova sistema mor-
skoy svyazi Inmarsat”, Sudostroenie, Leningrad, 1988