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
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91 lines
2.5 KiB
91 lines
2.5 KiB
import predict
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import json
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import sys
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import datetime
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frequencies = {'NOAA-15':'137.620M', 'NOAA-18':'137.9125M', 'NOAA-19':'137.10M', 'METEOR-M2':'137.925M', 'ISS':'145.80M' } #Meteor M2 is also on 137.1M
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tle_data = json.load(open('sat_tle.txt'))
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default_predictions = 1
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default_min_elevation = 30
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suppress_low_passes = False
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pass_elevation = default_min_elevation
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if( len(sys.argv) > 1 ):
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pass_elevation = int(sys.argv[1])
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if( pass_elevation == '' ):
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pass_elevation = default_min_elevation
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predictions = default_predictions
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if( len(sys.argv) > 2):
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predictions = int(sys.argv[2])
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if( predictions == '' ):
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predictions = default_predictions
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if( len(sys.argv) > 3 ):
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suppress_low_passes = True
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def convert_time( unixtime ):
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return datetime.datetime.fromtimestamp(
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int(unixtime)
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).strftime('%H:%M %Y-%m-%d')
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def convert_time_short( unixtime ):
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return datetime.datetime.fromtimestamp(
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int(unixtime)
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).strftime('%M')
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def get_sat( sat ):
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return sat + '\n' + tle_data[sat]
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qth = (49.32, 123.42, 49) # lat (N), long (W), alt (meters)
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qth_nw = (51.32, 125.42, 49)
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qth_se = (47.32, 121.42, 49)
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data = {}
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for sat, freq in frequencies.iteritems():
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name = predict.observe(get_sat(sat), qth)['name'].strip()
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t = predict.transits(get_sat(sat), qth)
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t_nw = predict.transits(get_sat(sat), qth_nw)
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t_se = predict.transits(get_sat(sat), qth_se)
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count = 0
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while ( count < predictions ):
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p = t.next()
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p_nw = t_nw.next()
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p_se = t_se.next()
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while (p.peak()['elevation'] < default_min_elevation):
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p = t.next()
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p_nw = t_nw.next()
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p_se = t_se.next()
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if( not suppress_low_passes ):
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print name, "pass too low, recalculating"
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data[name] = {}
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data[name]['frequency'] = freq
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data[name]['start_unix'] = p.start
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data[name]['start'] = convert_time(data[name]['start_unix'])
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data[name]['duration_seconds'] = int(p.duration())
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data[name]['duration_minutes'] = convert_time_short(data[name]['duration_seconds'])
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data[name]['elevation'] = p.peak()['elevation']
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#This actually means nothing, feel free to ignore it
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data[name]['direction'] = 'S' #Assume northbound
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if( int(p_nw.start) > int(p.start) and int(p.start) > int(p_se.start) ): #This is the direction the satellite is travelling TO, not from.
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data[name]['direction'] = 'N'
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print name, 'next pass at:', data[name]['start'], 'at', data[name]['elevation'], 'degrees.', data[name]['direction'] + '-bound'
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count = count + 1
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import json
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with open('satpredict.txt', 'w') as fp:
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json.dump(data, fp, indent=4)
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