How anamol7khadka/radar works
This MATLAB/Simulink proof of concept simulates a 77 GHz FMCW radar detecting a virtual human and estimating range, angle, and breathing rate. The documented workflow starts with setup, configures radar and target inputs, generates an echo, models the analog front end and ADC, simulates STM32 processing, then extracts detections and displays results. The graph follows README-described behavior; source excerpts were unavailable, so implementation-level call wiring is not asserted.
Main entry points: setup_radar_poc.m Run setup · radar_signal_processing.m Radar processing · generate_fmcw_echo.m FMCW echo · build_simulink_model.m Analog front end
Components 11
Radar setup
- Run setup
setup_radar_poc.m - Radar parameters
radar_parameters.m - Target scene
radar_target_scene.m
Signal chain
- FMCW echo
generate_fmcw_echo.m - Analog front end
build_simulink_model.m - ADC quantizer
adc_quantize.m
Embedded processing
- STM32 FFT
stm32_fixed_point_fft.m - Radar processing
radar_signal_processing.m
Detection and display
- Static plots
plot_instrumentation_results.m - Live display
radar_live_display.m
Other components
- MATLAB user
Connections 16
- MATLAB user → Run setup: runs
- Run setup → Radar parameters: loads settings
- Run setup → Target scene: sets scene
- Run setup → FMCW echo: generates echo
- Run setup → Analog front end: builds model
- Run setup → Radar processing: processes signal
- Radar parameters → FMCW echo: configures
- Target scene → FMCW echo: defines target
- FMCW echo → Analog front end: feeds signal
- Analog front end → ADC quantizer: filters and amplifies
- ADC quantizer → STM32 FFT: provides samples
- STM32 FFT → Radar processing: passes FFT data
- Run setup → Static plots: plots results
- Run setup → Live display: runs display
- Radar processing → Static plots: provides detections
- Radar processing → Live display: provides detections