a set of script to predict passes and make automated recordings of satellites. Intended to be run headless on an SoC.
Original forked from https://github.com/va7eex/Pi_WXRX
Improvements made for https://keet.space
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
89 lines
2.7 KiB
89 lines
2.7 KiB
import predict
|
|
import json
|
|
import sys
|
|
import datetime
|
|
|
|
#Frequencies that satellites transmit on.
|
|
frequencies = {'NOAA-15':'137.620M', 'NOAA-18':'137.9125M', 'NOAA-19':'137.10M'} #Meteor M2 is also on 137.1M
|
|
|
|
tle_data = json.load(open('sat_tle.txt'))
|
|
default_predictions = 1 #how many predictions do we want to predict in advance
|
|
default_min_elevation = 15 #how low the angle of the satellitie pass is allowed to be if we want to record a pass
|
|
suppress_low_passes = False #Less console spam if you enable this.
|
|
|
|
#You can change the default elevation with the first parameter
|
|
pass_elevation = default_min_elevation
|
|
if( len(sys.argv) > 1 ):
|
|
pass_elevation = int(sys.argv[1])
|
|
|
|
if( pass_elevation == '' ):
|
|
pass_elevation = default_min_elevation
|
|
|
|
#you can change the number of predictions per satellite with the second parameter
|
|
predictions = default_predictions
|
|
if( len(sys.argv) > 2):
|
|
predictions = int(sys.argv[2])
|
|
|
|
if( predictions == '' ):
|
|
predictions = default_predictions
|
|
|
|
#anything in the third parameter will turn off console spam
|
|
if( len(sys.argv) > 3 ):
|
|
suppress_low_passes = True
|
|
|
|
#format a unix timestamp in a time appropriate for the 'at' command
|
|
def convert_time( unixtime ):
|
|
return datetime.datetime.fromtimestamp(
|
|
int(unixtime)
|
|
).strftime('%H:%M %Y-%m-%d')
|
|
|
|
#format the unix timestamp for minutes, used to determine length of recording
|
|
def convert_time_short( unixtime ):
|
|
return datetime.datetime.fromtimestamp(
|
|
int(unixtime)
|
|
).strftime('%M')
|
|
|
|
def get_sat( sat ):
|
|
return sat + '\n' + tle_data[sat]
|
|
|
|
#Where on the earth you are. Change this to your location
|
|
qth = (52.08, 5.17, 5) # lat (N), long (W), alt (meters)
|
|
|
|
data = {}
|
|
|
|
for sat, freq in frequencies.iteritems():
|
|
|
|
name = predict.observe(get_sat(sat), qth)['name'].strip()
|
|
t = predict.transits(get_sat(sat), qth)
|
|
|
|
count = 0
|
|
while ( count < predictions ):
|
|
p = t.next()
|
|
# p_nw = t_nw.next()
|
|
# p_se = t_se.next()
|
|
|
|
#peak check. PEAK CHECK!
|
|
while (p.peak()['elevation'] < default_min_elevation):
|
|
p = t.next()
|
|
# p_nw = t_nw.next()
|
|
# p_se = t_se.next()
|
|
if( not suppress_low_passes ):
|
|
print name, "pass too low, recalculating"
|
|
|
|
#this is the data we want to pass on to the rest of the program
|
|
data[name] = {}
|
|
data[name]['frequency'] = freq
|
|
data[name]['start_unix'] = p.start
|
|
data[name]['start'] = convert_time(data[name]['start_unix'])
|
|
data[name]['duration_seconds'] = int(p.duration())
|
|
data[name]['duration_minutes'] = convert_time_short(data[name]['duration_seconds'])
|
|
data[name]['elevation'] = p.peak()['elevation']
|
|
|
|
print name, 'next pass at:', data[name]['start'], 'at', data[name]['elevation'], 'degrees.'
|
|
count = count + 1
|
|
|
|
import json
|
|
|
|
with open('satpredict.txt', 'w') as fp:
|
|
json.dump(data, fp, indent=4)
|
|
|
|
|