feat: osnovna arduino skica + display skripta za prvih 100 vzorcev

2026-01-24 20:14:25 +01:00
parent 1117213f82
commit 97728bd829
2 changed files with 291 additions and 0 deletions
@@ -0,0 +1,92 @@
+import serial
+import struct
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.animation import FuncAnimation
+import sys
+
+# --- KONFIGURACIJA---
+SERIAL_PORT = '/dev/ttyACM0'   # Preveri svoj port
+BAUD_RATE = 115200     
+FFT_SIZE = 1024
+BIN_COUNT = FFT_SIZE // 2  # 512 Bins
+DISPLAY_BINS = 100  # Only display first 100 bins
+SWEEP_SIZE = 2
+BYTES_PER_FRAME = BIN_COUNT * 4 + SWEEP_SIZE
+WATERFALL_HISTORY = 100  # Number of frames to display in waterfall
+
+try:
+    ser = serial.Serial(SERIAL_PORT, BAUD_RATE, timeout=2)
+    ser.reset_input_buffer()
+    print("Povezava z Arduino Due vzpostavljena")
+except Exception as e:
+    print(f"Error: {e}")
+    sys.exit()
+
+# Setup Plot with two subplots
+fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 10))
+
+x_freq = np.zeros(DISPLAY_BINS)
+y_data = np.zeros(DISPLAY_BINS)
+
+# FFT plot (top)
+bar_plot, = ax1.plot(x_freq, y_data, color="#ff0000", lw=1)
+ax1.set_xlabel('Razdalja [m]')
+ax1.set_ylabel('Amplituda')
+
+# Waterfall plot (bottom)
+waterfall_data = np.zeros((WATERFALL_HISTORY, DISPLAY_BINS))
+waterfall_img = ax2.imshow(waterfall_data, aspect='auto', cmap='viridis', 
+                           interpolation='nearest', origin='upper')
+ax2.set_xlabel('Razdalja [m]')
+ax2.set_ylabel('Čas (frame)')
+ax2.set_title('Waterfall prikaz')
+cbar = plt.colorbar(waterfall_img, ax=ax2, label='Amplituda')
+
+def update(frame):
+    global waterfall_data
+    
+    if ser.in_waiting >= BYTES_PER_FRAME:
+        raw_data = ser.read(BYTES_PER_FRAME)
+        
+        try:
+            fm_sweep = struct.unpack(f'H', raw_data[:2])
+
+            x_dist = np.linspace(0, 1024*3e8/100e6/fm_sweep[0], BIN_COUNT)
+            x_dist_display = x_dist[:DISPLAY_BINS]  # Only first 100 bins
+            ax1.set_title(f'FFT prikaz radarskega signala FM={fm_sweep[0]}')
+            bar_plot.set_xdata(x_dist_display)
+            ax1.set_xlim(x_dist_display[2], x_dist_display[-1]) # Skip DC
+
+            fft_data = struct.unpack(f'{BIN_COUNT}f', raw_data[2:])
+            fft_data_display = fft_data[:DISPLAY_BINS]  # Only use first 100 bins
+
+            # Update FFT plot
+            bar_plot.set_ydata(fft_data_display)
+
+            # Auto-scale FFT plot
+            peak = np.max(fft_data_display[2:]) 
+            if peak > ax1.get_ylim()[1]:
+                ax1.set_ylim(0, peak * 1.2)
+            elif peak < ax1.get_ylim()[1] * 0.5 and peak > 10:
+                ax1.set_ylim(0, peak * 1.5)
+            
+            # Update waterfall (scroll up and add new data at bottom)
+            waterfall_data = np.roll(waterfall_data, -1, axis=0)
+            waterfall_data[-1, :] = fft_data[:DISPLAY_BINS]
+            
+            waterfall_img.set_data(waterfall_data)
+            waterfall_img.set_clim(vmin=np.min(waterfall_data), vmax=np.max(waterfall_data))
+            
+            # Update waterfall x-axis to match distance
+            waterfall_img.set_extent([x_dist_display[0], x_dist_display[-1], WATERFALL_HISTORY, 0])
+                
+        except Exception as e:
+            print(f"Frame Error: {e}")
+            ser.reset_input_buffer()
+
+    return bar_plot, waterfall_img
+
+ani = FuncAnimation(fig, update, interval=0, blit=True)
+plt.tight_layout()
+plt.show()