discussion

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import butter, lfilter



g= np.load("HAE705.npy")
y = g/10
fS = 1e6
t = np.arange(len(y)) / fS


#plt.figure()
#plt.plot(t, y)
#plt.xlabel("temps")
#plt.ylabel("amplitude")
#plt.show()

f0 = 300e3
fc = 200

cos = np.cos(2*np.pi*f0*t)
sin = np.sin(2*np.pi*f0*t)

I = y * cos
Q = y * sin

fc_norm = fc / (fS / 2)
b, a = butter(1, fc_norm, btype='low')

I_filtre = lfilter(b, a, I)
Q_filtre = lfilter(b, a, Q)

phi1= np.arctan2(Q_filtre,I_filtre)
phi2= np.unwrap(phi1)




plt.figure()
plt.plot(t, phi2)
plt.title("phase instentané phi2(t)")
plt.xlabel("temps (s)")
plt.ylabel("phase (rad)")
plt.show()

freq = np.gradient(phi2) / (2 * np.pi) * fS

for _ in range(4):
freq = lfilter(b, a, freq)

plt.figure()
plt.plot(t, freq)
plt.title("freq(t)")
plt.xlabel("temps (s)")
plt.ylabel("frequence (Hz)")
plt.show()

freqences = [...]
plataux = [...]
val_assci = np.round((plataux - offset) / scale)

message = "".join([chr(int(val)) for val in ascii_values])

print("Decoded message:", message)