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multi_beampark_pointing_planner.py
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from pathlib import Path
import numpy as np
import scipy.optimize as sciopt
import scipy.signal as scisig
from astropy.time import TimeDelta
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from tqdm import tqdm
import sorts
import pyorb
import pyant
'''
STEPS:
get the kosmos TLEs
./space_track_download.py 24h 2021-11-15 \
/home/danielk/git/antisat_analysis/projects/output/russian_asat/kosmos-1408-2021-11-15.tle \
-k space-track -n "COSMOS 1408"
configure below
run this
'''
base_path = Path(__file__).parent
# tle_file = base_path/'projects'/'output'/'russian_asat'/'kosmos-1408-2021-11-15.tle'
tle_file = [
(
'1 54236U 22151B 22319.31717231 .00000322 00000+0 17837-3 0 9998',
'2 54236 98.8227 324.3982 0028030 342.4420 17.5784 14.17951913 464',
)
]
# output_folder = base_path/'projects'/'output'/'russian_asat'/'dual_beampark_planner'
output_folder = base_path/'projects'/'output'/'CZ_6A_RB'/'dual_beampark_planner'
output_folder.mkdir(parents=True, exist_ok=True)
radars = [
sorts.radars.eiscat_uhf,
sorts.radars.eiscat_esr,
]
total_systems = len(radars)
names = [
'EISCAT UHF',
'EISCAT ESR',
]
fixed_pointing = 1
azimuth = 185.5
elevation = 82.1
elevation_limits = [
30.0,
]
station_inds = [
(0, 0),
(0, 0),
]
dt = 1.0
rotation_offset_limits = (0., 24*3600.0)
rotation_offset_num = 24*60
rotation_offset = TimeDelta(
np.linspace(
rotation_offset_limits[0],
rotation_offset_limits[1],
rotation_offset_num
),
format='sec',
)
# Set which states to find pass pointing for
for radar, (txi, rxi) in zip(radars, station_inds):
radar.tx = [radar.tx[txi]]
radar.rx = [radar.rx[rxi]]
# set static pointing
radar_fixed = radars[fixed_pointing]
radar_fixed.tx[0].beam.sph_point(azimuth, elevation)
print(f'Setting pointing to: \n\
azimuth = {radar_fixed.tx[0].beam.azimuth} deg\n\
elevation = {radar_fixed.tx[0].beam.elevation} deg')
pop = sorts.population.tle_catalog(tle_file, kepler=True)
pop.unique()
print(f'TLEs = {len(pop)}')
tle_obj = pop.get_object(0)
print(tle_obj)
print(tle_obj.epoch.isot)
epoch0 = tle_obj.epoch
ecef_point = radar_fixed.tx[0].pointing_ecef
ecef_st = radar_fixed.tx[0].ecef
tle_obj.out_frame = 'TEME'
teme_state0 = tle_obj.get_state([0])
orb0 = pyorb.Orbit(
M0=pyorb.M_earth, m=0,
num=1,
degrees=True,
type='mean',
)
orb0.cartesian = teme_state0[:, :1]
period = orb0.period[0]
t_samp = np.arange(0, period, dt)
print(f'Sampling {len(t_samp)} times epoch + t={0/3600.0} h -> {period/3600.0} h')
teme_states = tle_obj.get_state(t_samp)
tle_obj.out_frame = 'ITRS'
best_ind = np.empty((rotation_offset_num, ), dtype=np.int64)
best_ang = np.empty((rotation_offset_num, ), dtype=np.float64)
best_t = np.empty((rotation_offset_num, ), dtype=np.float64)
def get_offaxis(epc):
ecef_states = sorts.frames.convert(
epc + TimeDelta(t_samp, format='sec'),
teme_states,
in_frame = 'TEME',
out_frame = 'ITRS',
)
ecef_states = ecef_states[:3, :] - ecef_st[:, None]
off_axis_ang = pyant.coordinates.vector_angle(
ecef_point,
ecef_states,
radians=False,
)
return off_axis_ang
### SETTINGS END ###
for ind in tqdm(range(rotation_offset_num)):
epoch = epoch0 + rotation_offset[ind]
off_axis_ang = get_offaxis(epoch)
best_ind[ind] = np.argmin(off_axis_ang)
best_ang[ind] = off_axis_ang[best_ind[ind]]
best_t[ind] = t_samp[best_ind[ind]]
fig, ax = plt.subplots()
ax.plot(rotation_offset.sec/3600.0, best_ang, '-b')
ax.set_xlabel('Rotation offset [h]')
ax.set_ylabel('Best off-axis angle [deg]')
fig.savefig(output_folder / 'rotation_offset.png')
best_offset = np.argmin(best_ang)
offset = rotation_offset.sec[best_offset]
minima_ind, = scisig.argrelextrema(best_ang, np.less)
for mind in range(len(minima_ind)):
t_pass = t_samp[best_ind[minima_ind[mind]]]
t_offset = rotation_offset.sec[minima_ind[mind]]
ep_off = TimeDelta(t_pass + t_offset, format='sec')
print(f'\n\
ind={best_ind[minima_ind[mind]]}, \n\
t pass = {best_t[minima_ind[mind]]}, \n\
offset = {rotation_offset.sec[minima_ind[mind]]} s, \n\
off axis angle = {best_ang[minima_ind[mind]]} deg')
epoch = epoch0 + rotation_offset[minima_ind[mind]]
off_axis_ang = get_offaxis(epoch)
fig, ax = plt.subplots()
ax.plot(t_samp/3600.0, off_axis_ang, '-b')
ax.plot(t_samp[best_ind[minima_ind[mind]]]/3600.0, off_axis_ang[best_ind[minima_ind[mind]]], 'or')
fig.savefig(output_folder / f'minima{mind}_off_axis_ang.png')
ECEF_state = tle_obj.get_state(t_pass)
tle_obj.out_frame = 'TEME'
TEME_state = tle_obj.get_state(t_pass)
print('ECEF: ', ECEF_state)
print('TEME: ', TEME_state)
orb = pyorb.Orbit(
M0=pyorb.M_earth, m=0,
num=1,
degrees=True,
type='mean',
)
orb.cartesian = TEME_state
obj = sorts.SpaceObject(
propagator = sorts.propagator.Kepler,
propagator_options = {
'settings': {
'in_frame': 'TEME',
'out_frame': 'ITRS',
}
},
state = orb,
epoch = epoch0 + ep_off,
parameters={
'd': 1,
'm': 0,
}
)
print(obj)
print(f'in_frame ={obj.in_frame}')
print(f'out_frame={obj.out_frame}')
print(f'Orbital period {period/3600.0} h')
t_search = np.arange(-period*1.5, period*1.5, dt, dtype=np.float64)
t_search_h = t_search/3600.0
ecef_states = obj.get_state(t_search)
data = {
'az': [None]*total_systems,
'el': [None]*total_systems,
'el_maxima': [None]*total_systems,
}
for ri, radar in enumerate(radars):
txi = station_inds[ri][0]
rxi = station_inds[ri][1]
enu = radar.tx[txi].enu(ecef_states)
azel = pyant.coordinates.cart_to_sph(enu, radians=False)
data['az'][ri] = np.mod(azel[0, :] + 360.0, 360)
data['el'][ri] = azel[1, :]
data['el_maxima'][ri], = scisig.argrelextrema(azel[1, :], np.greater)
print(f'Radar {ri}')
print('Elevation maxima:')
print(f'Az = {data["az"][ri][data["el_maxima"][ri]]} deg')
print(f'El = {data["el"][ri][data["el_maxima"][ri]]} deg')
print(f't = {t_search_h[data["el_maxima"][ri]]*60} min')
fig = plt.figure(figsize=(15,15))
ax = fig.add_subplot(111, projection='3d')
sorts.plotting.grid_earth(ax)
for ri, radar in enumerate(radars):
txi = station_inds[ri][0]
rxi = station_inds[ri][1]
ax.plot(radar.tx[txi].ecef[0], radar.tx[txi].ecef[1], radar.tx[txi].ecef[2], 'or')
if ri != fixed_pointing:
for elmi in range(len(data["el_maxima"][ri])):
rsph = np.array([
data["az"][ri][data["el_maxima"][ri][elmi]],
data["el"][ri][data["el_maxima"][ri][elmi]],
1,
])
rp = pyant.coordinates.sph_to_cart(rsph, radians=False)
rp = sorts.frames.ecef_to_enu(
radar.tx[txi].lat,
radar.tx[txi].lon,
radar.tx[txi].alt,
rp,
radians=False,
)
ax.plot(
[radar.tx[txi].ecef[0], radar.tx[txi].ecef[0] + rp[0]*5000e3],
[radar.tx[txi].ecef[1], radar.tx[txi].ecef[1] + rp[1]*5000e3],
[radar.tx[txi].ecef[2], radar.tx[txi].ecef[2] + rp[2]*5000e3],
'--g',
)
ax.plot(
[ecef_st[0], ecef_st[0] + ecef_point[0]*3000e3],
[ecef_st[1], ecef_st[1] + ecef_point[1]*3000e3],
[ecef_st[2], ecef_st[2] + ecef_point[2]*3000e3],
'-g',
)
ax.plot(ecef_states[0,:], ecef_states[1,:], ecef_states[2,:], '-b')
ax.plot(ecef_states[0,-1], ecef_states[1,-1], ecef_states[2,-1], 'xb')
ax.set_title('Orbit')
fig.savefig(output_folder / f'minima{mind}_orbit.png')
fig = plt.figure(constrained_layout=True)
fig.suptitle('Multi-beampark passes')
subfigs = fig.subfigures(nrows=total_systems, ncols=1)
for row, subfig in enumerate(subfigs):
addon = ' [FIXED]' if row == fixed_pointing else ''
subfig.suptitle(f'{names[row]}{addon}')
axes = subfig.subplots(nrows=1, ncols=2)
axes[0].plot(t_search_h, data['az'][row])
axes[0].set_xlabel('Detection epoch + time [h]')
axes[0].set_ylabel('Azimuth [deg]')
axes[1].plot(t_search_h, data['el'][row])
axes[1].set_xlabel('Detection epoch + time [h]')
axes[1].set_ylabel('Elevation [deg]')
if row == 0:
axes[0].axhline(azimuth, color='r')
axes[1].axhline(elevation, color='r')
else:
axes[1].axhline(elevation_limits[row - 1], color='g')
fig.savefig(output_folder / f'minima{mind}_results.png')
plt.show()