def generate_states(traj_name):
global states, x0, y0, z0
trajectory = Track()
method_name = getattr(trajectory,
"gen_" + traj_name.replace(" ", "").lower())
states = method_name()
x0, y0, z0 = trajectory.initial_position(states)
def gen_env():
trajectory = Track()
states = trajectory.gen_landing()
x0 = states[0, 0]
y0 = states[0, 3]
z0 = states[0, 6]
radar = Radar(x=0, y=2000)
radar_filter_cv = RadarFilterCV(dim_x=9,
dim_z=3,
q=1.,
x0=x0,
y0=y0,
z0=z0,
radar=radar)
radar_filter_ca = RadarFilterCA(dim_x=9,
dim_z=3,
q=400.,
x0=x0,
y0=y0,
z0=z0,
radar=radar)
radar_filter_ct = RadarFilterCT(dim_x=9,
dim_z=3,
q=350.,
x0=x0,
y0=y0,
z0=z0,
radar=radar)
filters = [radar_filter_cv, radar_filter_ca, radar_filter_ct]
mu = [0.33, 0.33, 0.33]
trans = np.array([[0.998, 0.001, 0.001], [0.050, 0.900, 0.050],
[0.001, 0.001, 0.998]])
imm = IMMEstimator(filters, mu, trans)
benchmark_imm3 = Benchmark(radars=radar, radar_filter=imm, states=states)
benchmark_imm3.launch_benchmark(with_nees=True)
from fdia_simulation.models import Radar, PeriodRadar, Track
from fdia_simulation.filters import (RadarFilterCA, MultipleRadarsFilterCA, MultiplePeriodRadarsFilterCA,
RadarFilterCV, MultipleRadarsFilterCV, MultiplePeriodRadarsFilterCV,
RadarFilterCT, MultipleRadarsFilterCT, MultiplePeriodRadarsFilterCT,
RadarFilterTA, MultipleRadarsFilterTA, MultiplePeriodRadarsFilterTA)
from fdia_simulation.attackers import (Attacker,DOSAttacker,DriftAttacker,
PeriodAttacker,DOSPeriodAttacker,DriftPeriodAttacker)
from fdia_simulation.benchmarks import Benchmark
from fdia_simulation.anomaly_detectors import MahalanobisDetector, EuclidianDetector
if __name__ == "__main__":
# ==========================================================================
# ================== Position generation for the aircraft ==================
# ==========================================================================
trajectory = Track()
states = trajectory.gen_landing()
x0,y0,z0 = trajectory.initial_position(states)
# ==========================================================================
# ========================= Radar(s) Generation ============================
# ==========================================================================
## =================== Standard Radars (same data rates)
## Specify your own radar positions and beliefs over measurements!
# Radar 1: Precision radar
radar1 = Radar(x = -6000, y = 10000)
# Radar 2: Standard radar
radar2 = Radar(x = 1000, y = 8000,
r_std = 5., theta_std = 0.005, phi_std = 0.005)
radar2 = Radar(x=1000, y=8000)
radars = [radar1, radar2]
## Different data rates radars
dt1 = 0.1
dt2 = 0.4
fradar1 = PeriodRadar(x=-6000, y=10000, dt=dt1)
fradar2 = PeriodRadar(x=1000,
y=8000,
dt=dt2,
r_std=5.,
theta_std=0.005,
phi_std=0.005)
fradars = [fradar1, fradar2]
##States
trajectory = Track()
states = trajectory.gen_landing()
x0 = states[0, 0]
y0 = states[0, 3]
z0 = states[0, 6]
# Loop over every list and output + write results
for filter in FILTERS_1_RADAR:
name = filter.__name__[-2:]
print('=================================================================')
print('=========================== ' + name +
'-1 Radar ==========================')
noise_finder = NoiseFinder1Radar(radar1, states, filter, nb_iterations=3)
noise_finder.launch_benchmark()
best_value = noise_finder.best_value()
print(('Best value for ' + name + '-1Radar:{0}').format(best_value))
Created on Thu Jul 04 11:47:28 2019
@author: qde
"""
import numpy as np
import matplotlib.pyplot as plt
from filterpy.kalman import IMMEstimator
from fdia_simulation.models import Radar, Track
from fdia_simulation.filters import MultipleRadarsFilterCV, MultipleRadarsFilterCA, MultipleRadarsFilterCT
from fdia_simulation.attackers import MoAttacker
from fdia_simulation.benchmarks import Benchmark
if __name__ == "__main__":
#================== Position generation for the aircraft =====================
trajectory = Track()
states = trajectory.gen_takeoff()
x0 = states[0, 0]
y0 = states[0, 3]
z0 = states[0, 6]
# ==========================================================================
# ======================== Radars data generation ===========================
# Radar 1: Precision radar
radar1 = Radar(x=800, y=200)
# Radar 2: Standard radar
radar2 = Radar(x=0, y=1000, r_std=5., theta_std=0.005, phi_std=0.005)
# ==========================================================================
# ========================= IMM generation =================================