def test_single_location(self):
# Location of the receiver ground stations
lat = 41.39
lon = -71.05
# Link parameters
el = 60 # Elevation angle equal to 60 degrees
f = 22.5 * itur.u.GHz # Frequency equal to 22.5 GHz
D = 1 * itur.u.m # Receiver antenna diameter of 1 m
p = 0.1 # We compute values exceeded during 0.1 % of
# the average year
# Compute atmospheric parameters
hs = itur.topographic_altitude(lat, lon)
T = itur.surface_mean_temperature(lat, lon)
P = itur.models.itu835.pressure(lat, hs)
rho_p = itur.surface_water_vapour_density(lat, lon, p, hs)
rho_sa = itur.models.itu835.water_vapour_density(lat, hs)
T_sa = itur.models.itu835.temperature(lat, hs)
V = itur.models.itu836.total_water_vapour_content(lat, lon, p, hs)
# Compute rain and cloud-related parameters
R_prob = itur.models.itu618.rain_attenuation_probability(
lat, lon, el, hs)
R_pct_prob = itur.models.itu837.rainfall_probability(lat, lon)
R001 = itur.models.itu837.rainfall_rate(lat, lon, p)
h_0 = itur.models.itu839.isoterm_0(lat, lon)
h_rain = itur.models.itu839.rain_height(lat, lon)
L_red = itur.models.itu840.columnar_content_reduced_liquid(lat, lon, p)
A_w = itur.models.itu676.zenit_water_vapour_attenuation(lat,
lon,
p,
f,
h=hs)
# Compute attenuation values
A_g = itur.gaseous_attenuation_slant_path(f, el, rho_p, P, T)
A_r = itur.rain_attenuation(lat, lon, f, el, hs=hs, p=p)
A_c = itur.cloud_attenuation(lat, lon, el, f, p)
A_s = itur.scintillation_attenuation(lat, lon, f, el, p, D)
A_t = itur.atmospheric_attenuation_slant_path(lat, lon, f, el, p, D)
def ITU_loss(self,
frequency,
link,
location=[41.39, -71.05],
percentage=0.1):
# calculate the matching dish diameter - assume efficiency of 65%
if link == 'downlink':
effective_diameter = (scipy.constants.c /
(np.pi * frequency)) * np.sqrt(
10**(self.gs_rx_antenna_gain / 10) /
0.65) * itur.u.m
else:
effective_diameter = (scipy.constants.c /
(np.pi * frequency)) * np.sqrt(
10**(self.gs_tx_antenna_gain / 10) /
0.65) * itur.u.m
elevation = self.elevation
# convert frequency to GHz
frequency_ghz = (frequency / 1e9) * itur.u.GHz
# Compute atmospheric parameters
hs = itur.topographic_altitude(41.39, -71.05)
T = itur.surface_mean_temperature(41.39, -71.05)
P = itur.models.itu835.pressure(41.39, hs)
rho_p = itur.surface_water_vapour_density(location[0], location[1],
percentage, hs)
rho_sa = itur.models.itu835.water_vapour_density(location[0], hs)
T_sa = itur.models.itu835.temperature(location[0], hs)
V = itur.models.itu836.total_water_vapour_content(
location[0], location[1], percentage, hs)
# Compute rain and cloud-related parameters
R_prob = itur.models.itu618.rain_attenuation_probability(
location[0], location[1], elevation, hs)
R_pct_prob = itur.models.itu837.rainfall_probability(
location[0], location[1])
R001 = itur.models.itu837.rainfall_rate(location[0], location[1],
percentage)
h_0 = itur.models.itu839.isoterm_0(location[0], location[1])
h_rain = itur.models.itu839.rain_height(location[0], location[1])
L_red = itur.models.itu840.columnar_content_reduced_liquid(
location[0], location[1], percentage)
A_w = itur.models.itu676.zenit_water_vapour_attenuation(location[0],
location[1],
percentage,
frequency_ghz,
h=hs)
# Compute attenuation values
A_g = itur.gaseous_attenuation_slant_path(frequency_ghz, elevation,
rho_p, P, T)
A_r = itur.rain_attenuation(location[0],
location[1],
frequency_ghz,
elevation,
hs=hs,
p=percentage)
A_c = itur.cloud_attenuation(location[0], location[1], elevation,
frequency_ghz, percentage)
A_s = itur.scintillation_attenuation(location[0], location[1],
frequency_ghz, elevation,
percentage, effective_diameter)
A_t = itur.atmospheric_attenuation_slant_path(location[0], location[1],
frequency_ghz, elevation,
percentage,
effective_diameter)
# rain attenuation plus all other attenuations
rain = A_r
atmosphere = A_g + A_c + A_s
return float(rain.value), float(atmosphere.value)
import itur
# Location of the receiver ground stations
lat = 41.39
lon = -71.05
# Link parameters
el = 60 # Elevation angle equal to 60 degrees
f = 22.5 * itur.u.GHz # Frequency equal to 22.5 GHz
D = 1 * itur.u.m # Receiver antenna diameter of 1 m
p = 0.1 # We compute values exceeded during 0.1 % of the average
# year
# Compute atmospheric parameters
hs = itur.topographic_altitude(lat, lon)
T = itur.surface_mean_temperature(lat, lon)
P = itur.models.itu835.pressure(lat, hs)
rho_p = itur.surface_water_vapour_density(lat, lon, p, hs)
rho_sa = itur.models.itu835.water_vapour_density(lat, hs)
T_sa = itur.models.itu835.temperature(lat, hs)
V = itur.models.itu836.total_water_vapour_content(lat, lon, p, hs)
print(('The ITU recommendations predict the following values for the point '
'located at coordinates ({0}, {1})').format(lat, lon))
print(
' - Height above the sea level [ITU-R P.1511] {0:.1f}'.
format(hs.to(itur.u.m)))
print(
' - Surface mean temperature [ITU-R P.1510] {0:.1f}'.