def build_measurements(param):
output = []
inputs = read_param(param)
for inp in inputs:
obj = messages_pb2.Measurement()
output.append(obj)
for dest, src in _measurement_fields.items():
fld = inp.get(src)
if (fld):
if (isinstance(fld, list)):
getattr(obj, dest).extend(fld)
else:
setattr(obj, dest, fld)
return (output)
def plot(config,
measurements,
orbit_fit,
interactive=False,
output_file_path=None):
cfg = read_param(config)
inp = [
x for x in read_param(measurements)
if ("Station" in x or "Position" in x or "PositionVelocity" in x)
]
out = [
x for x in read_param(orbit_fit) if ("PreFit" in x and "PostFit" in x)
]
key = list(cfg["Measurements"].keys())
dmcrun = (cfg["Estimation"].get("DMCCorrTime", 0.0) > 0.0
and cfg["Estimation"].get("DMCSigmaPert", 0.0) > 0.0)
dmcidx = 6
cd = cfg.get("Drag", {}).get("Coefficient", {}).get("Estimation", "")
cr = cfg.get("RadiationPressure", {}).get("Creflection",
{}).get("Estimation", "")
if (cd == "Estimate"):
dmcidx += 1
if (cr == "Estimate"):
dmcidx += 1
parnames = []
if (cd == "Estimate" or (cd == "Consider" and cr == "Consider")):
parnames.extend([r"$C_D$", r"$C_R$"])
else:
parnames.extend([r"$C_R$", r"$C_D$"])
for sk, sv in cfg.get("Stations", {}).items():
if (sv.get("BiasEstimation", "") in ["Estimate", "Consider"]):
for m in cfg.get("Measurements", {}).keys():
parnames.append(sk + m)
tstamp,prefit,posfit,inocov,params,estmacc,estmcov = [],[],[],[],[],[],[]
for i, o in zip(inp, out):
tstamp.append(dateutil.parser.isoparse(i["Time"]))
if (key[0] == "Position" or key[0] == "PositionVelocity"):
prefit.append(
[ix - ox for ix, ox in zip(i[key[0]], o["PreFit"][key[0]])])
posfit.append(
[ix - ox for ix, ox in zip(i[key[0]], o["PostFit"][key[0]])])
else:
if (len(key) == 2):
prefit.append([
i[key[0]] - o["PreFit"][key[0]][-1],
i[key[1]] - o["PreFit"][key[1]][-1]
])
posfit.append([
i[key[0]] - o["PostFit"][key[0]][-1],
i[key[1]] - o["PostFit"][key[1]][-1]
])
else:
prefit.append([i[key[0]] - o["PreFit"][key[0]][-1]])
posfit.append([i[key[0]] - o["PostFit"][key[0]][-1]])
p = []
for m in range(len(o["InnovationCovariance"])):
p.append(3.0 * numpy.sqrt(o["InnovationCovariance"][m][m]))
inocov.append(p)
if (len(o["EstimatedState"]) > 6):
if (dmcrun):
params.append(o["EstimatedState"][6:dmcidx] +
o["EstimatedState"][dmcidx + 3:])
else:
params.append(o["EstimatedState"][6:])
if (dmcrun):
r = numpy.array(o["EstimatedState"][:3])
r /= norm(r)
v = numpy.array(o["EstimatedState"][3:6])
v /= norm(v)
h = numpy.cross(r, v)
rot = numpy.vstack((r, numpy.cross(h, r), h))
estmacc.append(rot.dot(o["EstimatedState"][dmcidx:dmcidx + 3]))
pre = numpy.array(prefit)
pos = numpy.array(posfit)
cov = numpy.array(inocov)
par = numpy.array(params)
estmacc = numpy.array(estmacc)
start = tstamp[0] if (tstamp[0] < tstamp[-1]) else tstamp[-1]
tim = [(t - start).total_seconds() / 3600 for t in tstamp]
angles = ["Azimuth", "Elevation", "RightAscension", "Declination"]
if (key[0] in angles and key[1] in angles):
pre *= 648000.0 / math.pi
pos *= 648000.0 / math.pi
cov *= 648000.0 / math.pi
units = ["arcsec", "arcsec"]
else:
if ("Position" in key):
units = ["m", "m", "m"]
elif ("PositionVelocity" in key):
units = ["m", "m", "m", "m/s", "m/s", "m/s"]
else:
units = ["m", "m/s"]
if ("Position" in key):
ylabs = [r"$\Delta x$", r"$\Delta y$", r"$\Delta z$"]
order = [1, 2, 3]
elif ("PositionVelocity" in key):
ylabs = [
r"$\Delta x$", r"$\Delta y$", r"$\Delta z$", r"$\Delta v_x$",
r"$\Delta v_y$", r"$\Delta v_z$"
]
order = [1, 3, 5, 2, 4, 6]
else:
ylabs = key
outfiles = []
plt.figure(0)
plt.suptitle("Pre-fit residuals")
for i in range(pre.shape[-1]):
if ("Position" in key):
plt.subplot(3, 1, order[i])
elif ("PositionVelocity" in key):
plt.subplot(3, 2, order[i])
else:
plt.subplot(pre.shape[-1], 1, i + 1)
plt.semilogx(tim, pre[:, i], "ob")
plt.xlabel("Time [hr]")
plt.ylabel("%s [%s]" % (ylabs[i], units[i]))
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
if (output_file_path is not None):
outfiles.append(output_file_path + "_prefit.png")
plt.savefig(outfiles[-1], format="png")
plt.figure(1)
plt.suptitle("Post-fit residuals")
for i in range(pre.shape[-1]):
if ("Position" in key):
plt.subplot(3, 1, order[i])
elif ("PositionVelocity" in key):
plt.subplot(3, 2, order[i])
else:
plt.subplot(pre.shape[-1], 1, i + 1)
plt.semilogx(tim, pos[:, i], "ob")
plt.semilogx(tim, -cov[:, i], "-r")
plt.semilogx(tim, cov[:, i], "-r", label=r"Innov. 3$\sigma$")
plt.xlabel("Time [hr]")
plt.ylabel("%s [%s]" % (ylabs[i], units[i]))
if ("Position" not in key and "PositionVelocity" not in key):
plt.ylim(-cov[i, 0], cov[i, 0])
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
if (output_file_path is not None):
outfiles.append(output_file_path + "_postfit.png")
plt.savefig(outfiles[-1], format="png")
for i in range(par.shape[-1]):
if (i == 0):
plt.figure(2)
plt.suptitle("Estimated parameters")
plt.subplot(par.shape[1], 1, i + 1)
plt.semilogx(tim, par[:, i], "ob")
plt.xlabel("Time [hr]")
plt.ylabel(parnames[i])
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
if (output_file_path is not None):
outfiles.append(output_file_path + "_estpar.png")
plt.savefig(outfiles[-1], format="png")
if (dmcrun):
lab = [
r"Radial [$\frac{m}{s^2}$]", r"In track [$\frac{m}{s^2}$]",
r"Cross track [$\frac{m}{s^2}$]"
]
plt.figure(3)
plt.suptitle("DMC estimated accelerations")
for i in range(3):
plt.subplot(3, 1, i + 1)
plt.semilogx(tim, estmacc[:, i], "-b")
plt.xlabel("Time [hr]")
plt.ylabel(lab[i])
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
if (output_file_path is not None):
outfiles.append(output_file_path + "_estacc.png")
plt.savefig(outfiles[-1], format="png")
if (interactive):
plt.show()
plt.close("all")
return (outfiles)
def build_settings(param):
inp = read_param(param)
cfg = messages_pb2.Settings()
for dest, src in _settings_fields.items():
fld = inp
for s in src[0]:
fld = fld.get(s, src[1]) if s == src[0][-1] else fld.get(s)
if (fld is None):
fld = src[1]
break
if (fld is None):
continue
if (isinstance(fld, list)):
getattr(cfg, dest).extend(fld)
else:
setattr(cfg, dest, fld)
for f in inp.get("SpaceObject", {}).get("Facets", []):
fac = messages_pb2.Facet(area=f["Area"])
fac.normal.extend(f["Normal"])
cfg.rso_facets.append(fac)
coef = inp.get("Drag", {}).get("Coefficient", {})
cfg.drag_coefficient.CopyFrom(
messages_pb2.Parameter(name="Cd",
value=coef.get("Value", 2.0),
min=coef.get("Min", 1.0),
max=coef.get("Max", 3.0),
estimation=coef.get("Estimation", "Estimate")))
for f in inp.get("Drag", {}).get("MSISEFlags", []):
obj = messages_pb2.IntegerArray()
obj.array.extend(f)
cfg.drag_MSISE_flags.append(obj)
coef = inp.get("RadiationPressure", {}).get("Creflection", {})
cfg.rp_coeff_reflection.CopyFrom(
messages_pb2.Parameter(name="Cr",
value=coef.get("Value", 1.5),
min=coef.get("Min", 1.0),
max=coef.get("Max", 2.0),
estimation=coef.get("Estimation", "Estimate")))
for m in inp.get("Maneuvers", []):
man = messages_pb2.Maneuver(time=m["Time"],
trigger_event=m["TriggerEvent"],
maneuver_type=m["ManeuverType"])
if ("TriggerParams" in m):
man.trigger_params.extend(m["TriggerParams"])
if ("ManeuverParams" in m):
man.maneuver_params.extend(m["ManeuverParams"])
cfg.maneuvers.append(man)
for k, v in inp.get("Stations", {}).items():
sta = messages_pb2.Station(
latitude=v["Latitude"],
longitude=v["Longitude"],
altitude=v["Altitude"],
azimuth_bias=v.get("AzimuthBias", 0.0),
elevation_bias=v.get("ElevationBias", 0.0),
range_bias=v.get("RangeBias", 0.0),
range_rate_bias=v.get("RangeRateBias", 0.0),
right_ascension_bias=v.get("RightAscensionBias", 0.0),
declination_bias=v.get("DeclinationBias", 0.0))
sta.position_bias.extend(v.get("PositionBias", [0.0] * 3))
sta.position_velocity_bias.extend(
v.get("PositionVelocityBias", [0.0] * 6))
cfg.stations[k].CopyFrom(sta)
for k, v in inp.get("Measurements", {}).items():
mea = messages_pb2.MeasurementSetting(two_way=v.get("TwoWay", True))
mea.error.extend(v["Error"])
cfg.measurements[k].CopyFrom(mea)
coef = inp.get("Estimation", {}).get("DMCAcceleration", {})
cfg.estm_DMC_acceleration.CopyFrom(
messages_pb2.Parameter(name="",
value=coef.get("Value", 0.0),
min=coef.get("Min", -1.0E-3),
max=coef.get("Max", 1.0E-3),
estimation=coef.get("Estimation", "Estimate")))
return (cfg)
def plot(config, sim_data, interactive=False, output_file_path=None):
mu = 398600.4418
cfg = read_param(config)
out = read_param(sim_data)
tstamp,hvec,hmag,ener,sma,ecc,inc,raan,argp,tran = [],[],[],[],[],[],[],[],[],[]
for o in out:
rv = [x / 1000.0 for x in o["TrueStateCartesian"][:6]]
rn = norm(rv[:3])
vn = norm(rv[3:])
h = cross(rv[:3], rv[3:])
hn = norm(h)
a = 1.0 / (2.0 / rn - vn**2 / mu)
e = cross(rv[3:], h) / mu - rv[:3] / rn
en = norm(e)
i = acos(h[2] / hn) * 180.0 / pi
n = cross([0, 0, 1], h)
nn = norm(n)
O = acos(dot(n, [1, 0, 0]) / nn) * 180.0 / pi
if (n[1] < 0.0):
O = 360.0 - O
w = acos(dot(n, e) / (nn * en)) * 180.0 / pi
if (e[2] < 0.0):
w = 360.0 - w
theta = acos(dot(rv[:3], e) / (rn * en)) * 180.0 / pi
if (dot(rv[:3], rv[3:]) < 0):
theta = 360.0 - theta
tstamp.append(dateutil.parser.isoparse(o["Time"]))
hvec.append(h)
hmag.append(hn)
ener.append(0.5 * vn**2 - mu / rn)
sma.append(a)
ecc.append(en)
inc.append(i)
raan.append(O)
argp.append(w)
tran.append(theta)
hvec = array(hvec)
tim = [(t - tstamp[0]).total_seconds() / 3600 for t in tstamp]
outfiles = []
plt.figure(0)
plt.subplot(611)
plt.plot(tim, sma, "ob")
plt.xlabel("Time [hr]")
plt.ylabel("SMA [km]")
plt.subplot(612)
plt.plot(tim, ecc, "ob")
plt.xlabel("Time [hr]")
plt.ylabel("Eccentricity")
plt.subplot(613)
plt.plot(tim, inc, "ob")
plt.xlabel("Time [hr]")
plt.ylabel("Inclination [deg]")
plt.subplot(614)
plt.plot(tim, raan, "ob")
plt.xlabel("Time [hr]")
plt.ylabel("RAAN [deg]")
plt.subplot(615)
plt.plot(tim, argp, "ob")
plt.xlabel("Time [hr]")
plt.ylabel("Perigee arg. [deg]")
plt.subplot(616)
plt.plot(tim, tran, "ob")
plt.xlabel("Time [hr]")
plt.ylabel("True anom. [deg]")
if (output_file_path is not None):
outfiles.append(output_file_path + "_elements.png")
plt.savefig(outfiles[-1], format="png")
plt.figure(1)
plt.subplot(211)
plt.plot(tim, hmag, "ob")
plt.xlabel("Time [hr]")
plt.ylabel("Angular momentum")
plt.subplot(212)
plt.plot(tim, ener, "ob")
plt.xlabel("Time [hr]")
plt.ylabel("Specific energy")
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
if (output_file_path is not None):
outfiles.append(output_file_path + "_momentum_energy.png")
plt.savefig(outfiles[-1], format="png")
plt.figure(2)
plt.subplot(311)
plt.plot(tim, hvec[:, 0], "ob")
plt.xlabel("Time [hr]")
plt.ylabel("h(x)")
plt.subplot(312)
plt.plot(tim, hvec[:, 1], "ob")
plt.xlabel("Time [hr]")
plt.ylabel("h(y)")
plt.subplot(313)
plt.plot(tim, hvec[:, 2], "ob")
plt.xlabel("Time [hr]")
plt.ylabel("h(z)")
plt.suptitle("Components of angular momentum")
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
if (output_file_path is not None):
outfiles.append(output_file_path + "_momentum_components.png")
plt.savefig(outfiles[-1], format="png")
if (interactive):
plt.show()
plt.close("all")
return (outfiles)