XM125 mmWave sensor practice
- Download files from Quick start contents at https://github.com/acconeer/acconeer-python-exploration
- Click update.bat
- install CH340 driver at https://www.arduined.eu/ch340-windows-10-driver-download/
- run run_app.bat
- click A121
- click setting and set the baudrate to 115200
- click the connect and click sparseIQ or distance etc... and start measurement!
- Download examples at https://github.com/acconeer/acconeer-python-exploration/tree/master/examples
- run cmd_with_path.bat
- run basic.py and basic_plot.py(serial_port='COMx',override_baudrate=115200)
Server Info:
ServerInfo:
rss_version ............ a121-v1.9.0
sensor_count ........... 1
ticks_per_second ....... 1000
hardware_name .......... xm125
max_baudrate ........... 2000000
sensor_infos:
SensorInfo @ slot 1:
connected .............. True
serial ................. None
Result 1:
Result(data_saturated=False, frame_delayed=False, calibration_needed=False, temperature=0, _frame=array([[( -75, 214), ( -84, 311), ( -94, 335), (-171, 334), (-210, 316),
(-342, 255)],
[( 44, 297), ( -78, 296), (-130, 380), (-146, 294), (-259, 256),
(-308, 267)],
[( -15, 381), ( -46, 359), (-110, 409), (-248, 287), (-257, 277),
(-356, 227)],
[( -14, 322), (-173, 409), ( -95, 293), (-250, 239), (-230, 292),
(-431, 182)]], dtype=[('real', '<i2'), ('imag', '<i2')]), tick=1567, _context=ResultContext(metadata=Metadata(_frame_data_length=24, _sweep_data_length=6, _subsweep_data_offset=array([0]), _subsweep_data_length=array([6]), _calibration_temperature=2, _tick_period=0, _base_step_length_m=0.00250227400101721, _max_sweep_rate=8902.890625, _high_speed_mode=True), ticks_per_second=1000))
Result 2:
Result(data_saturated=False, frame_delayed=False, calibration_needed=False, temperature=1, _frame=array([[( -64, 323), (-138, 312), ( -42, 315), (-188, 223), (-230, 294),
(-308, 225)],
[( 41, 311), ( -42, 291), (-102, 324), (-213, 253), (-264, 292),
(-314, 235)],
[( -31, 283), (-128, 340), ( -94, 389), (-235, 357), (-175, 289),
(-340, 193)],
[( -85, 328), ( -76, 292), ( -82, 252), (-246, 231), (-329, 246),
(-391, 228)]], dtype=[('real', '<i2'), ('imag', '<i2')]), tick=1586, _context=ResultContext(metadata=Metadata(_frame_data_length=24, _sweep_data_length=6, _subsweep_data_offset=array([0]), _subsweep_data_length=array([6]), _calibration_temperature=2, _tick_period=0, _base_step_length_m=0.00250227400101721, _max_sweep_rate=8902.890625, _high_speed_mode=True), ticks_per_second=1000))
Result 3:
slow version(with many subsweeps): sparse_iq_copy.py
fast version(only one sweep): faster_range_doppler.py
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installation: https://youtu.be/b6R--BpjOM4
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run basic.py and basic_plot.py to get graph from raw data: https://youtu.be/ERDY-VRpA3k
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run basic_plot.py to get 3d graph from raw data: https://youtu.be/0qt5du7j4OU
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get range-doppler heatmap using sparse_iq_copy.py https://youtu.be/xbgBpl3dfMc
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distance measurement using examples/algo/a121/distance/processor.py https://youtu.be/vF7i7laj-D8
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speed measurement using examples/algo/a121/speed/processor.py https://youtu.be/zhe-X66ccDs