def setUp(self):
# Radar & States generation
self.setUp_radar_states()
# Filter definition
## Classical models
self.radar_filter_ca = MultiplePeriodRadarsFilterCA(dim_x=9,
dim_z=3,
q=100.,
radars=self.radars)
self.radar_filter_cv = MultiplePeriodRadarsFilterCV(dim_x=9,
dim_z=3,
q=100.,
radars=self.radars)
self.radar_filter_ct = MultiplePeriodRadarsFilterCT(dim_x=9,
dim_z=3,
q=100.,
radars=self.radars)
## IMM with ca, cv and ct models
filters = [
self.radar_filter_cv, self.radar_filter_ca, self.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]])
self.radar_filter = RadarIMM(filters=filters, mu=mu, M=trans)
# Benchmark definition
self.benchmark = Benchmark(radars=self.radars,
radar_filter=self.radar_filter,
states=self.states)
def generate_filters(radar_type):
global ca_dict, cv_dict, ct_dict, ta_dict, filter, filters, radars, x0, y0, z0
filter_dicts = [cv_dict, ca_dict, ct_dict, ta_dict]
current_filters = []
for filter_dict in filter_dicts:
if filter_dict["is_chosen"]:
current_filters.append(filter_dict)
# Filter instanciation
for filter_dict in current_filters:
detector = None
if not (filter_dict["detector"] == "None"):
detector_type = globals()[filter_dict["detector"] + "Detector"]
detector = detector_type()
q = float(filter_dict["q"])
if radar_type == "Radar" and len(radars) == 1:
filter_class = filter_dict["name"]
elif radar_type == "Radar" and len(radars) == 2:
filter_class = filter_dict["mname"]
elif radar_type == "PeriodRadar" and len(radars) == 2:
filter_class = filter_dict["mpname"]
current_filter = filter_class(radars=radars,
q=q,
detector=detector,
x0=x0,
y0=y0,
z0=z0)
filters.append(current_filter)
# IMM Generation
if len(filters) == 1:
filter = filters[0]
if len(filters) == 2:
mu = [0.5, 0.5]
trans = np.array([[0.998, 0.02], [0.100, 0.900]])
filter = RadarIMM(filters, mu, trans)
if len(filters) == 3:
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]])
filter = RadarIMM(filters, mu, trans)
if len(filters) == 4:
mu = [0.25, 0.25, 0.25, 0.25]
trans = np.array([[0.997, 0.001, 0.001, 0.001],
[0.050, 0.850, 0.050, 0.050],
[0.001, 0.001, 0.997, 0.001],
[0.001, 0.001, 0.001, 0.997]])
filter = RadarIMM(filters, mu, trans)
def setUp(self):
# Radar & States generation
self.setUp_radar_states()
# Filter definition
## Classical models
self.radar_filter_ca = RadarFilterCA(dim_x = 9, dim_z = 3, q = 100., radar = self.radar)
self.radar_filter_cv = RadarFilterCV(dim_x = 9, dim_z = 3, q = 100., radar = self.radar)
## IMM with ca, cv and ct models
filters = [self.radar_filter_cv, self.radar_filter_ca]
mu = [0.5, 0.5]
trans = np.array([[0.999, 0.001],
[0.001, 0.999]])
self.radar_filter = RadarIMM(filters = filters, mu = mu, M = trans)
# Benchmark definition
self.benchmark = Benchmark(radars = self.radar, radar_filter = self.radar_filter, states = self.states)
detector=detector,
radars=pradars,
x0=x0,
y0=y0,
z0=z0)
radar_filter_ct = MultiplePeriodRadarsFilterCT(q=350.,
detector=detector,
radars=pradars,
x0=x0,
y0=y0,
z0=z0)
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 = RadarIMM(filters, mu, trans)
# =============================== Attackers ================================
## No attacker
# attacker = None
## Attackers for 2 Period Radars
# attacker = DriftPeriodAttacker(filter = imm, t0 = 500, time = 300,
# attack_drift = np.array([[100,100,100]]).T,
# radar = pradar2, radar_pos = 1)
attacker = CumulativeDriftPeriodAttacker(filter=imm,
t0=300,
time=2000,
delta_drift=np.array([[0, 0,
1]]).T,