Probabilistic method for BDS detection

Including probabilistic method to determine BDS 5,0 and BDS 6,0 (by using a multivariate normal distribution with reference data)
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Huy Vû 2018-03-13 11:31:34 +01:00 committed by GitHub
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@ -19,6 +19,7 @@ A python package for decoding ModeS (DF20, DF21) messages.
from __future__ import absolute_import, print_function, division
from . import util, modes_common
from scipy.stats import multivariate_normal
def icao(msg):
return modes_common.icao(msg)
@ -1001,5 +1002,70 @@ def BDS(msg):
elif sum(isBDS) == 1:
return BDS[isBDS.index(True)]
else:
bds_ = [bds for (bds, i) in zip(BDS, isBDS) if i]
return ','.join(bds_)
return = [bds for (bds, i) in zip(BDS, isBDS) if i]
def Vxy(V, angle):
Vx = V*np.sin(np.deg2rad(angle))
Vy = V*np.cos(np.deg2rad(angle))
return Vx, Vy
def BDSv2(msg, SPDref=np.nan, TRKref=np.nan, ALTref=np.nan):
"""Use probabilistic method to determine the most likely BDS code of an message
Args:
msg (String): 28 bytes hexadecimal message string
SPDref (float): reference speed (for example ADS-B GS)
TRKref (float): reference track (for example ADS-B TRK)
ALTref (float): reference altitude (for example ADS-B altitude)
Returns:
String or None: BDS version, or possible versions, or None if nothing matches.
"""
BDS = pms.ehs.BDS(msg)
if type(BDS) != list:
return BDS
else:
if 'BDS53' in BDS:
BDS.remove('BDS53')
if 'BDS40' in BDS:
fms = pms.ehs.alt40fms(msg)
mcp = pms.ehs.alt40mcp(msg)
baro = pms.ehs.p40baro(msg)
if fms != None:
if (((fms % 100) <= 8) or ((fms % 100) >= 92)) and fms < 50500:
return 'BDS40'
if mcp != None:
if (((mcp % 100) <= 8) or ((mcp % 100) >= 92)) and mcp < 50500:
return 'BDS40'
if baro != None:
if (983 <= baro <= 1043): #1013 -+ 30
return 'BDS40'
if set(BDS).issubset(['BDS50', 'BDS60']):
if ~(np.isnan(SPDref) or np.isnan(TRKref) or np.isnan(ALTref)):
meanV = Vxy(SPDref, TRKref)
sigmaV = 20
covV = [[sigmaV**2, 0], [0, sigmaV**2]]
try: # Because register field is not available.
pBDS50 = multivariate_normal(meanV, covV).pdf(Vxy(pms.ehs.gs50(msg), pms.ehs.trk50(msg)))
pBDS60_1 = multivariate_normal(meanV, covV).pdf(Vxy(aero.mach2tas(pms.ehs.mach60(msg), ALTref*aero.ft)/aero.kts, pms.ehs.hdg60(msg)))
pBDS60_2 = multivariate_normal(meanV, covV).pdf(Vxy(aero.cas2tas(pms.ehs.ias60(msg)*aero.kts, ALTref*aero.ft)/aero.kts, pms.ehs.hdg60(msg)))
pBDS60 = max(pBDS60_1, pBDS60_2)
except:
return BDS
if pBDS50 + pBDS60 > 0: #Avoid None values
if pBDS50 > pBDS60:
return 'BDS50'
elif pBDS50 < pBDS60:
return 'BDS60'
return BDS