diff --git a/groundstation/auto-tune.py b/groundstation/auto-tune.py
index d49ab3f6..b7808902 100644
--- a/groundstation/auto-tune.py
+++ b/groundstation/auto-tune.py
@@ -18,74 +18,76 @@ if __name__ == "__main__":
         
 	sampling_rate = 1024e3 # 250e3 # Hz
 	duration = 65536/sampling_rate # 1          # seconds
-	t = np.linspace(0, duration, int(sampling_rate * duration), endpoint=False)
-	
-	sdr = RtlSdr()
-	
-	# configure device
-	sdr.sample_rate = sampling_rate # 250e3 # 2.4e6
-	#center_frequency = 434.8e6
-	sdr.center_freq = center_frequency
-	sdr.gain = 47
-	sdr.direct_sampling = False
-	
-	# signal = sdr.read_samples(64*1024) #256
-	signal = sdr.read_samples(duration*sampling_rate).real #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
-	
-	if (graph == 'y'):
-	  # 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) * 100
-	
-	#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 + 2000
 	
+	try:	
+		sdr = RtlSdr()
+		
+		# configure device
+		sdr.sample_rate = sampling_rate # 250e3 # 2.4e6
+		#center_frequency = 434.8e6
+		sdr.center_freq = center_frequency
+		sdr.gain = 47
+		sdr.direct_sampling = False
+		
+		# signal = sdr.read_samples(64*1024) #256
+		signal = sdr.read_samples(duration*sampling_rate).real #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
+		
+		if (graph == 'y'):
+		  # Plotting the results
+		  t = np.linspace(0, duration, int(sampling_rate * duration), endpoint=False)
+			
+		  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) * 100
+		
+		#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 + 2000
+	except: # if no RTL-SDR or in use, stop scanning with high max value and center frequency
+		max_value = 100
+		freq_max = center_frequency + 200e3 # should be 434900000
+		
 	print(f" {freq_max:.0f} {max_value:.0f}")
-	#print(f"The minimum signal is {min_value} at frequency {freq_min}")
-	
-	#print(min_value)
-	#print(max_value)
+