From 465ea04df282db1dff8210f95fb5b52241dfc85c Mon Sep 17 00:00:00 2001
From: Alan Johnston <alan.b.johnston@gmail.com>
Date: Mon, 27 Oct 2025 13:45:10 -0400
Subject: [PATCH] Create auto-tune.py

---
 groundstation/auto-tune.py | 81 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 81 insertions(+)
 create mode 100644 groundstation/auto-tune.py

diff --git a/groundstation/auto-tune.py b/groundstation/auto-tune.py
new file mode 100644
index 00000000..435d6523
--- /dev/null
+++ b/groundstation/auto-tune.py
@@ -0,0 +1,81 @@
+from rtlsdr import RtlSdr
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Create a sample signal (sum of two sine waves)
+sampling_rate = 1024e3 # 250e3 # Hz
+duration = 65536/sampling_rate # 1          # seconds
+# t = np.linspace(0, duration, int(sampling_rate * duration), endpoint=False)
+t = np.linspace(0, duration, int(sampling_rate * duration), endpoint=False)
+# frequency1 = 50       # Hz
+# frequency2 = 120      # Hz
+# signal = 0.7 * np.sin(2 * np.pi * frequency1 * t) + np.sin(2 * np.pi * frequency2 * t)
+
+sdr = RtlSdr()
+
+# configure device
+sdr.sample_rate = sampling_rate # 250e3 # 2.4e6
+center_frequency = 434.8e6
+sdr.center_freq = center_frequency
+sdr.gain = 4
+sdr.direct_sampling = False
+
+# signal = sdr.read_samples(64*1024) #256
+signal = sdr.read_samples(duration*sampling_rate) #256
+
+print(f"Center frequency is {center_frequency}")
+
+sdr.close()
+
+# Compute the FFT
+fft_result = np.fft.fft(signal)
+
+# Calculate the frequencies corresponding to the FFT output
+n = len(signal)
+frequencies = np.fft.fftfreq(n, d=1/sampling_rate)
+
+# Take the absolute value for amplitude spectrum and consider only the positive frequencies
+positive_frequencies_indices = np.where(frequencies >= 0)
+positive_frequencies = frequencies[positive_frequencies_indices]
+amplitude_spectrum = 2/n * np.abs(fft_result[positive_frequencies_indices]) # Normalize for amplitude
+
+# Plotting the results
+plt.figure(figsize=(12, 6))
+
+plt.subplot(1, 2, 1)
+plt.plot(t, signal)
+plt.title('Time Domain Signal')
+plt.xlabel('Time (s)')
+plt.ylabel('Amplitude')
+
+plt.subplot(1, 2, 2)
+plt.stem(positive_frequencies, amplitude_spectrum, markerfmt=" ", basefmt="-b")
+plt.title('Frequency Domain (FFT)')
+plt.xlabel('Frequency (Hz)')
+plt.ylabel('Amplitude')
+plt.grid(True)
+
+plt.tight_layout()
+plt.show()
+
+print(amplitude_spectrum)
+x = amplitude_spectrum 
+print(x)
+min_value = min(x)
+max_value = max(x)
+
+#freq_min = np.argmax(min_value)
+print(np.argmax(x))
+print(np.argmax(x)*(150e3 - 10e3)/(9770 - 709))
+print(sampling_rate)
+print(center_frequency)
+
+offset = (np.argmax(x)*(150e3 - 10e3)/(9770 - 709))
+freq_max = center_frequency + offset 
+
+print(f"The maximum signal is {max_value} at frequency {freq_max}")
+#print(f"The minimum signal is {min_value} at frequency {freq_min}")
+
+print(min_value)
+print(max_value)
+