def build_site(jd_span, site_lat, site_lon, site_alt):
r"""Create the site dictionary
site = build_site(jd_span, site_lat, site_lon, site_alt)
Parameters
----------
jd_span : array
Array of Julian date times for teh window
site_lat : float
site latitude in radians
site_lon : float
site longitude in radians
site_alt : float
site altitude in kilometers
Returns
-------
site : dictionary
site dicitonary holding data on the observation site
Author
------
Shankar Kulumani GWU [email protected]
"""
site_ecef = geodetic.lla2ecef(site_lat, site_lon, site_alt)
# loop over jd span
site = defaultdict(list)
site['lat'] = site_lat
site['lon'] = site_lon
site['alt'] = site_alt
site['ecef'] = site_ecef
for jd in jd_span:
gst, lst = time.gstlst(jd, site_lon)
# site_eci = geodetic.site2eci(site_lat, site_alt, lst)
# site_eci = attitude.rot3(gst).dot(site_ecef)
site_eci = transform.dcm_ecef2eci(jd).dot(site_ecef)
# test if site is in the dark
sun_eci, _, _ = planets.sun_earth_eci(jd)
# append site information to list
site['eci'].append(site_eci)
site['sun_eci'].append(sun_eci)
site['gst'].append(gst)
site['lst'].append(lst)
# turn into numpy arrays
for key, item in site.items():
site[key] = np.squeeze(np.array(item))
return site
def test_sun_eci_vallado():
jd, mjd = time.date2jd(1994, 4, 2, 0, 0, 0)
jd_vallado = 2449444.5
rsun_vallado = np.array([146241097,
28574940,
12389196])
ra_vallado, dec_vallado = np.deg2rad(11.056071), np.deg2rad(4.7529393)
rsun, ra, dec = planets.sun_earth_eci(jd)
np.testing.assert_allclose(jd, jd_vallado)
np.testing.assert_allclose(rsun, rsun_vallado, rtol=1e-4)
np.testing.assert_allclose((ra, dec), (ra_vallado, dec_vallado), rtol=1e-4)
def test_sun_earth_eci_usafa():
jd = 2453905.50000000
expected_rsun = [6371243.918400, 139340081.269385, 60407749.811252]
rsun, ra, dec = planets.sun_earth_eci(jd)
np.testing.assert_allclose(rsun, expected_rsun, rtol=1e-4)
def generate_solution(ifile='./data/example_tle.txt', ofile='./data/SAT_OUT_EXAMPLE.txt'):
ifile = os.path.abspath(ifile)
ofile = os.path.abspath(ofile)
site_lat = np.deg2rad(float(input("Site Latitude (38.925) : ") or "38.925"))
site_lon = np.deg2rad(float(input("Site Longitude (-77.057) : ") or "-77.057"))
site_alt = float(input("Site Altitude (0.054) : ") or "0.054")
site_ecef = geodetic.lla2ecef(site_lat, site_lon, site_alt)
# timespan
date_start = [float(i) for i in (input('Start Date UTC (2017 12 1 0 0 0) : ') or "2017 12 1 0 0 0").split()]
date_end = [float(i) for i in (input('End Date UTC (2017 12 5 0 0 0) : ') or "2017 12 5 0 0 0").split()]
jd_start, _ = time.date2jd(date_start[0], date_start[1], date_start[2], date_start[3],
date_start[4], date_start[5])
jd_end, _ = time.date2jd(date_end[0], date_end[1], date_end[2], date_end[3],
date_end[4], date_end[5])
jd_step = 2 / (24 * 60) # step size in minutes
jd_span = np.arange(jd_start, jd_end, jd_step)
# echo check some data
with open(ofile, 'w') as f:
f.write('PREDICT EXAMPLE RESULTS : Shankar Kulumani\n\n')
f.write('Check Input Data : \n\n')
f.write('Site Latitude = {:9.6f} rad = {:9.6f} deg\n'.format(site_lat, np.rad2deg(site_lat)))
f.write('Site Longitude = {:9.6f} rad = {:9.6f} deg\n'.format(site_lon, np.rad2deg(site_lon)))
f.write('Site Altitude = {:9.6f} km = {:9.6f} m\n'.format(site_alt, site_alt * 1000))
f.write('\nObservation Window :\n\n')
f.write('Start Date : {} UTC\n'.format(datetime.datetime(int(date_start[0]), int(date_start[1]), int(date_start[2]), int(date_start[3]), int(date_start[4]), int(date_start[5])).isoformat()))
f.write('End Date : {} UTC\n\n'.format(datetime.datetime(int(date_end[0]),int(date_end[1]),int(date_end[2]),int(date_end[3]),int(date_end[4]),int(date_end[5])).isoformat()))
f.write('Start Julian Date = {}\n'.format(jd_start))
f.write('End Julian Date = {}\n\n'.format(jd_end))
# loop over jd span
site = defaultdict(list)
site['lat'] = site_lat
site['lon'] = site_lon
site['alt'] = site_alt
site['ecef'] = site_ecef
for jd in jd_span:
gst, lst = time.gstlst(jd, site_lon)
# site_eci = geodetic.site2eci(site_lat, site_alt, lst)
# site_eci = attitude.rot3(gst).dot(site_ecef)
site_eci = transform.dcm_ecef2eci(jd).dot(site_ecef)
# test if site is in the dark
sun_eci, _, _ = planets.sun_earth_eci(jd)
# append site information to list
site['eci'].append(site_eci)
site['sun_eci'].append(sun_eci)
site['gst'].append(gst)
site['lst'].append(lst)
with open(ofile, 'a') as f:
f.write('Site Data:\n\n')
f.write('Start GST : {:9.6f} rad\n'.format(site['gst'][0]))
f.write('Start LST : {:9.4f} rad\n'.format(site['lst'][0]))
f.write('Site ECEF : {:9.6f} x {:9.6f} y {:9.6f} z km\n'.format(site['ecef'][0], site['ecef'][1], site['ecef'][2]))
f.write('Sun ECI_0 : {:9.6f} x {:9.6f} y {:9.6f} z km\n\n'.format(site['sun_eci'][0][0], site['sun_eci'][0][1], site['sun_eci'][0][2]))
f.write('{}\n\n'.format('*'*80))
# turn into numpy arrays
for key, item in site.items():
site[key] = np.squeeze(np.array(item))
# update the downloaded TLEs if necessary
# now we have to read the TLE
sats = tle.get_tle(ifile)
# now propogate and the check if each satellite is visible
for sat in sats:
sat.tle_update(jd_span)
sat.visible(site)
sat.output(ofile)
def generate_data(tle_file='./data/COMFIX_tle.txt',
outfile='./data/COMFIX_tle_measurement.txt'):
# define a time span
jd_start, _ = time.date2jd(2017, 12, 1, 0, 0, 0) # time in UTC
jd_end, _ = time.date2jd(2017, 12, 11, 0, 0, 0)
jd_step = 1 / (24 * 60)
jd_span = np.arange(jd_start, jd_end, jd_step)
# define the observing site
site_lat = np.deg2rad(38.8999),
site_lon = np.deg2rad(-77.0490)
site_alt = 0.020
site_ecef = geodetic.lla2ecef(site_lat, site_lon, site_alt)
# loop over jd span
site = defaultdict(list)
site['lat'] = site_lat
site['lon'] = site_lon
site['alt'] = site_alt
site['ecef'] = site_ecef
for jd in jd_span:
gst, lst = time.gstlst(jd, site_lon)
# site_eci = geodetic.site2eci(site_lat, site_alt, lst)
# site_eci = attitude.rot3(gst).dot(site_ecef)
site_eci = geodetic.eci2ecef(jd).T.dot(site_ecef)
# test if site is in the dark
sun_eci, _, _ = planets.sun_earth_eci(jd)
# append site information to list
site['eci'].append(site_eci)
site['sun_eci'].append(sun_eci)
site['gst'].append(gst)
site['lst'].append(lst)
# turn into numpy arrays
for key, item in site.items():
site[key] = np.squeeze(np.array(item))
# read some TLEs and get the state vector and write to a file
sats = tle.get_tle(tle_file)
f = open(outfile, 'w')
for sat in sats:
# propogate for several time periods and get the r, v vectors
sat.tle_update(jd_span)
sat.visible_radar(site)
jd_vis = sat.jd_vis
rho_vis = sat.rho_vis
az_vis = sat.az_vis
el_vis = sat.el_vis
drho_vis = sat.drho_vis
daz_vis = sat.daz_vis
dele_vis = sat.dele_vis
# write first line - site latgd, lon, alt (meters), JD obs time
f.write('{:9.6f} {:9.6f} {:9.6f} {:16.6f}\n'.format(
np.rad2deg(site['lat']), np.rad2deg(site['lon']),
site['alt'] * 1e3, jd_vis[0]))
# write second line rho, az, el, drho, daz, dele
f.write(
'{:5g} {:16.6f} {:16.6f} {:16.6f} {:16.6f} {:16.6f} {:16.6f}\n'.
format(sat.satnum, rho_vis[0], np.rad2deg(az_vis[0][0]),
np.rad2deg(el_vis[0]), drho_vis[0], np.rad2deg(daz_vis[0]),
np.rad2deg(dele_vis[0])))
f.close()
def visible(r_sat_eci, r_site_eci, lat, lon, GST, JD):
r"""Checks if visibility constraints are valid for satellite information
Inputs:
r_sat_eci :(vector) Given in ECI frame with units km
r_site_eci :(vector) Given in ECI frame with units km
lat :(angle) Given in units of radians
LST :(angle) Given in units of radians
JD :(time) Given as Julian Date
Outputs:
flag :(scalar) Given as unitless, 0 = Not Visible, 1 = Visible
Author: Thomas J Susi GWU [email protected]
"""
flag = 0
r_sun = planets.sun_earth_eci(JD)[0]
"""Range and Angle"""
p_eci = r_sat_eci - r_site_eci
ecef2eci = ecef2eci = np.array([[np.cos(GST), -np.sin(GST), 0],
[np.sin(GST), np.cos(GST), 0], [0, 0, 1]])
p_ecef = np.dot(np.transpose(ecef2eci), p_eci)
b2ecef = np.array([[np.cos(lon), -np.sin(lon), 0],
[np.sin(lon), np.cos(lon), 0], [0, 0, 1]])
sez2b = np.array([[np.cos(np.pi / 2 - lat), 0,
np.sin(np.pi / 2 - lat)], [0, 1, 0],
[-np.sin(np.pi / 2 - lat), 0,
np.cos(np.pi / 2 - lat)]])
sez2ecef = b2ecef.dot(sez2b)
p_sez = np.dot(np.transpose(sez2ecef), p_ecef)
rang = np.linalg.norm(p_sez)
elev = np.arcsin(p_sez[2] / rang)
elev_num = abs(float(elev))
p_mag = np.linalg.norm(p_eci)
"""Darkness"""
dark = np.dot(r_sun, r_site_eci)
"""In Sunlight"""
sin_angle = np.dot(
r_sun, r_sat_eci) / (np.linalg.norm(r_sun) * np.linalg.norm(r_sat_eci))
cos_angle = np.dot(
r_sun, r_sat_eci) / (np.linalg.norm(r_sun) * np.linalg.norm(r_sat_eci))
angle = np.dot(r_sun, r_sat_eci) / (np.linalg.norm(r_sun) *
np.linalg.norm(r_sat_eci)) + 2 * np.pi
dist = np.linalg.norm(r_sat_eci) * angle
dist_num = float(dist)
import pdb
pdb.set_trace()
"""If Statement"""
if (elev_num > np.deg2rad(10) and p_mag < 1500 and dark < 0
and dist_num > 6378.137):
flag = 1
return flag