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Bug fix: GPS failure prediction function
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@n-akram
n-akram committed Oct 30, 2023
1 parent 5dbecea commit fdf8ea2
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149 changes: 104 additions & 45 deletions SafeDrones/core/SafeDrones.py
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Original file line number Diff line number Diff line change
Expand Up @@ -683,69 +683,69 @@ def Chip_MTTF_Model(self,MTTFref=None, Tr=None, Ta = None, u=None,b = None, time
# return P_GPS_Fail.evalf(subs={t: time}), MTTF_GPS.evalf(subs={t: time})


def GPS_Failure_Risk_Calc(self, SatStatus=None, time=None, Lambda = None, MaxSat = 28, MinSat = 7):
# def GPS_Failure_Risk_Calc(self, SatStatus=None, time=None, Lambda = None, MaxSat = 28, MinSat = 7):

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Program Name : Markov-based Drone's Reliability and MTTF Estimator %
# Author : Koorosh Aslansefat %
# Version : 1.0.5 %
# Description : A Markov Process-Based Approach for Reliability %
# Evaluation of the GPS System for Drones %
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# # Program Name : Markov-based Drone's Reliability and MTTF Estimator %
# # Author : Koorosh Aslansefat %
# # Version : 1.0.5 %
# # Description : A Markov Process-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.
# 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.
# Lambda: Failure Rate of the GPS System.

time: Time of the mission
'''
# time: Time of the mission
# '''

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import sympy as sym # Symbolic Calculation
# import numpy as np # linear algebra
# import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
# import sympy as sym # Symbolic Calculation

t = sym.Symbol('t')
L = Lambda
# t = sym.Symbol('t')
# L = Lambda

if SatStatus > MaxSat:
print("The satellite status can not be more than maximum number of satellites. ")
raise ValueError
return None, None
# if SatStatus > MaxSat:
# print("The satellite status can not be more than maximum number of satellites. ")
# raise ValueError
# return None, None

if MinSat < SatStatus <= MaxSat:
P0_GPS = sym.zeros(MaxSat-MinSat+1, 1)
P0_GPS[SatStatus - MinSat] = 1
Sflag = MaxSat - SatStatus
else:
P_Fail = 1
MTTF = 0
return P_Fail, MTTF
# if MinSat < SatStatus <= MaxSat:
# P0_GPS = sym.zeros(MaxSat-MinSat+1, 1)
# P0_GPS[SatStatus - MinSat] = 1
# Sflag = MaxSat - SatStatus
# else:
# P_Fail = 1
# MTTF = 0
# return P_Fail, MTTF

M_GPS_updated = sym.zeros(MaxSat-MinSat+1, MaxSat-MinSat+1)
start_value = -1*MaxSat
# M_GPS_updated = sym.zeros(MaxSat-MinSat+1, MaxSat-MinSat+1)
# start_value = -1*MaxSat

for i in range(MaxSat-MinSat+1):
if i == (MaxSat-MinSat):
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
# for i in range(MaxSat-MinSat+1):
# if i == (MaxSat-MinSat):
# 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 = 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,:])
# MTTF_GPS = sum(tt[Sflag,:])

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 calculate_collision_risk(self, uav_1_trajectory, uav_2_trajectory, danger_threshold=-1, collision_threshold=-1): # self.danger_threshold, self.collision_threshold
# Check that both trajectories have the same length
Expand All @@ -772,6 +772,65 @@ 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):

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# 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 %
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

'''
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
'''

t = sym.Symbol('t')

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 = sym.Matrix(M_GPS_updated)

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

P_GPS_Fail = P_GPS[-1]

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

tt = -1*N_GPS.inv()

MTTF_GPS = sum(tt[Sflag_GPS,:])

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

def Drone_Risk_Calc(self):

import numpy as np
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225 changes: 212 additions & 13 deletions example/SafeDrone-demo-2.ipynb
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