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changed GPS function to k-out-of-n algorithm
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@n-akram
n-akram committed Nov 8, 2023
1 parent b59ea6e commit 9a5a9f6
Showing 1 changed file with 85 additions and 38 deletions.
123 changes: 85 additions & 38 deletions SafeDrones/core/SafeDrones.py
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Original file line number Diff line number Diff line change
Expand Up @@ -772,66 +772,113 @@ def calculate_collision_risk(self, uav_1_trajectory, uav_2_trajectory, danger_th

return danger_zone_risk, collision_zone_risk


def GPS_Failure_Risk_Calc(self, SatStatus=None, time=None, Lambda = None, MaxSat = 29, MinSat = 17):
def GPS_Failure_Risk_Calc(self, SatStatus=None, time=None, Lambda=None, MaxSat=29, MinSat=17):

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Program Name : Markov-based Drone's Reliability and MTTF Estimator %
# Authors : Koorosh Aslansefat and Mohammed Naveed Akram %
# Version : 1.0.6 %
# Description : A Markov Process-Based Approach for Reliability %
# Program Name : k-out-of-n based Reliability and MTTF Estimator %
# Authors : Koorosh Aslansefat, Mohammed Naveed Akram, Martin Walker %
# Version : 1.0.7 %
# Description : A k-out-of-n-Based Approach for Reliability %
# Evaluation of the GPS System for Drones %
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

'''
SatStatus: is an integer between 0 and MaxSat. 0 means no satellite is available and 14 means fully satellite coverage.
Lambda: Failure Rate of the GPS System.
time: Time of the mission
SatStatus: is an integer between 0 and MaxSat.
Lambda: Failure Rate of a single GPS satellite/connection.
time: Time of the mission.
'''

t = sym.Symbol('t')

import math

if Lambda == None:
Lambda = self.GPS_Lambda
L = Lambda

if SatStatus is None:
SatStatus = self.SatStatus
p0_fail = 1 - math.exp(-Lambda * time) # Probability of failure for one satellite connection
numSats = SatStatus - MinSat + 1 # Number of satellites until system failure
if numSats <= 0:
return 1, 0 # System failure: insufficient satellites
k = MinSat
n = SatStatus

# Calculate overall probability of failure
p0_success = 1 - p0_fail
if k < 0 or k > n: # Parameter error
return 1, 0

if MinSat < SatStatus <= MaxSat:
P0_GPS = sym.zeros(MaxSat-MinSat+2, 1) # +2 to account for the additional row
P0_GPS[MaxSat - SatStatus] = 1
Sflag_GPS = (MaxSat-MinSat) - (MaxSat - SatStatus)
else:
P_Fail = 1
MTTF = 0
return P_Fail, MTTF
p_success = 0
for i in range(k, n+1): # n is inclusive
fac = math.factorial(n) / (math.factorial(i) * math.factorial(n - i))
p_success += fac * (p0_success ** i) * (p0_fail ** (n-i))
p_fail = 1 - p_success

# Calculate MTTF
mttf = 0
for i in range(MinSat, SatStatus+1):
mttf += 1/i
mttf *= 1/Lambda

# Return
return p_fail, mttf

# def GPS_Failure_Risk_Calc(self, SatStatus=None, time=None, Lambda = None, MaxSat = 29, MinSat = 17):

# #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# # Program Name : Markov-based Drone's Reliability and MTTF Estimator %
# # Authors : Koorosh Aslansefat and Mohammed Naveed Akram %
# # Version : 1.0.6 %
# # Description : A Markov Process-Based Approach for Reliability %
# # Evaluation of the GPS System for Drones %
# #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

M_GPS_updated = sym.zeros(MaxSat-MinSat+2, MaxSat-MinSat+2) # +2 to account for the additional row and column
start_value = -1*MaxSat
# '''
# SatStatus: is an integer between 0 and MaxSat. 0 means no satellite is available and 14 means fully satellite coverage.
# Lambda: Failure Rate of the GPS System.
# time: Time of the mission
# '''

for i in range(MaxSat-MinSat+2): # +2 to loop through the additional row
if i == MaxSat-MinSat+1: # +1 to account for the additional row
M_GPS_updated[i, i] = (start_value + i) * L
else:
M_GPS_updated[i, i] = (start_value + i) * L
M_GPS_updated[i+1, i] = -(start_value + i) * L
# t = sym.Symbol('t')

# if Lambda == None:
# Lambda = self.GPS_Lambda
# L = Lambda

# if SatStatus is None:
# SatStatus = self.SatStatus

# if MinSat < SatStatus <= MaxSat:
# P0_GPS = sym.zeros(MaxSat-MinSat+2, 1) # +2 to account for the additional row
# P0_GPS[MaxSat - SatStatus] = 1
# Sflag_GPS = (MaxSat-MinSat) - (MaxSat - SatStatus)
# else:
# P_Fail = 1
# MTTF = 0
# return P_Fail, MTTF

# M_GPS_updated = sym.zeros(MaxSat-MinSat+2, MaxSat-MinSat+2) # +2 to account for the additional row and column
# start_value = -1*MaxSat

# for i in range(MaxSat-MinSat+2): # +2 to loop through the additional row
# if i == MaxSat-MinSat+1: # +1 to account for the additional row
# M_GPS_updated[i, i] = (start_value + i) * L
# else:
# M_GPS_updated[i, i] = (start_value + i) * L
# M_GPS_updated[i+1, i] = -(start_value + i) * L

M_GPS_updated[-1,-1] = 0
# M_GPS_updated[-1,-1] = 0

M_GPS = sym.Matrix(M_GPS_updated)
# M_GPS = sym.Matrix(M_GPS_updated)

P_GPS = sym.exp(M_GPS*t)*P0_GPS
# P_GPS = sym.exp(M_GPS*t)*P0_GPS

P_GPS_Fail = P_GPS[-1]
# P_GPS_Fail = P_GPS[-1]

N_GPS = M_GPS[:-1, :-1]
# N_GPS = M_GPS[:-1, :-1]

tt = -1*N_GPS.inv()
# tt = -1*N_GPS.inv()

MTTF_GPS = sum(tt[Sflag_GPS,:])
# MTTF_GPS = sum(tt[Sflag_GPS,:])

return P_GPS_Fail.evalf(subs={t: time}), MTTF_GPS.evalf(subs={t: time})
# return P_GPS_Fail.evalf(subs={t: time}), MTTF_GPS.evalf(subs={t: time})

def Drone_Risk_Calc(self):

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