Udemy - DoA Estimation for Automotive FMCW Radar

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Udemy - DoA Estimation for Automotive FMCW Radar (Size: 544.8 MB)
  2 - Phased Arrays and Direction of Arrival
  3 - DoA Estimation Methods
  4 - Validation with AWR2243
  10. DoA Estimation with Real Measurements.mp4 65.5 MB
  5 - Additional Resources
  11. Bonus Lecture.mp4 9.2 MB
  9. Measurement Setup, Scenarios, and Signal Processing.mp4 108.8 MB
  4. Spatial FFT.mp4 37.7 MB
  5. Bartlett Beamforming.mp4 40.1 MB
  6. Capon MVDR.mp4 63.7 MB
  7. MUSIC.mp4 51.6 MB
  8. ESPRIT.mp4 53.5 MB
  3. Phased Arrays and DoA Fundamentals.mp4 35.8 MB
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  awr2243_de_interleaving.py 10.5 KB
  awr2243_detection_profile.py 13.9 KB
  awr2243_doa_estimation.py 48.3 KB
  awr2243_rd_fft.py 14.9 KB
  awr2243_reading_adc.py 5.1 KB
  awr2243_virtual_channels.py 24 KB
  configuration.py 4 KB
  detect
  __init__.py 102.4 B
  __pycache__
  __init__.cpython-313.pyc 307.2 B
  ca_cfar.cpython-313.pyc 2.4 KB
  ca_cfar.py 1.9 KB
  doa
  __init__.py 512 B
  __pycache__
  __init__.cpython-313.pyc 614.4 B
  axis.cpython-313.pyc 1.3 KB
  axis.py 819.2 B
  beamformer.cpython-313.pyc 17.2 KB
  beamformer.py 15.4 KB
  doppler
  __init__.py 102.4 B
  __pycache__
  __init__.cpython-313.pyc 204.8 B
  doppler_fft.cpython-313.pyc 2.4 KB
  doppler_fft.py 1.8 KB
  io
  __init__.py 102.4 B
  __pycache__
  __init__.cpython-313.pyc 307.2 B
  range
  __init__.py 307.2 B
  __pycache__
  __init__.cpython-313.pyc 409.6 B
  axis.cpython-313.pyc 716.8 B
  axis.py 1.1 KB
  dataset
  awr2243_calibration.npz 4.6 KB
  broadside_0p0m.bin 8 MB
  broadside_3p0m.bin 8 MB
  explore
  __pycache__
  __init__.cpython-313.pyc 102.4 B
  doa_bartlett.cpython-313.pyc 14.8 KB
  doa_capon.cpython-313.pyc 14.6 KB
  doa_esprit.cpython-313.pyc 19.2 KB
  doa_fft.cpython-313.pyc 11.2 KB
  doa_music.cpython-313.pyc 16.2 KB
  live_covariance.cpython-313.pyc 7.5 KB
  off_boresight_0p0m.bin 8 MB
  off_boresight_3p0m.bin 8 MB
  fft.cpython-313.pyc 2.3 KB
  fft.py 3.3 KB
  scale.cpython-313.pyc 2.2 KB
  scale.py 1.2 KB
  window.cpython-313.pyc 1.4 KB
  window.py 819.2 B
  read_adc.cpython-313.pyc 2.9 KB
  read_adc.py 5.3 KB
  fft_angle.cpython-313.pyc 3.3 KB
  fft_angle.py 2.3 KB
  localmax.cpython-313.pyc 1.9 KB
  localmax.py 1.4 KB
  doa_bartlett.py 11.3 KB
  doa_capon.py 10.7 KB
  doa_esprit.py 15.5 KB
  doa_fft.py 9.8 KB
  doa_music.py 12.3 KB
  requirements.txt 0 B
  scripts
  __pycache__
  __init__.cpython-313.pyc 102.4 B
  awr2243_calibration.cpython-313.pyc 35 KB
  awr2243_cfar_detection.cpython-313.pyc 14.1 KB
  awr2243_de_interleaving.cpython-313.pyc 11.4 KB
  awr2243_detection_profile.cpython-313.pyc 13.8 KB
  awr2243_doa_estimation.cpython-313.pyc 44.2 KB
  awr2243_doa_spectrum.cpython-313.pyc 39.5 KB
  awr2243_estimation_validation.cpython-313.pyc 26.9 KB
  awr2243_rd_fft.cpython-313.pyc 15.3 KB
  awr2243_reading_adc.cpython-313.pyc 6 KB
  awr2243_unitary_validation.cpython-313.pyc 20.6 KB
  awr2243_virtual_channels.cpython-313.pyc 24 KB
  ~Get Your Files Here !
  1 - Introduction
  1. Introduction.mp4 32.5 MB
  2. Prerequisites and Course Setup.mp4 13.8 MB
  awr2243_doa_estimation
  README.md 819.2 B
  awr2243
  __pycache__
  __init__.cpython-313.pyc 102.4 B
  aoa
  __pycache__
  __init__.cpython-313.pyc 512 B
  axis.cpython-313.pyc 1.3 KB
  beamformer.cpython-313.pyc 12.9 KB
  cartesian.cpython-313.pyc 819.2 B
  fft_angle.cpython-313.pyc 2.1 KB
  configuration.cpython-313.pyc 4.1 KB
  ▲ 90 total files

Description


DoA Estimation for Automotive FMCW Radar
https://WebToolTip.com
Published 8/2026

Created by Aleksei Rostov

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Level: Intermediate | Genre: eLearning | Language: English | Duration: 11 Lectures ( 57m ) | Size: 531 MB
Learn Spatial FFT, Bartlett, Capon/MVDR, MUSIC and ESPRIT with simulations and real AWR2243 radar measurements
What you'll learn

⚡ Understand how phased antenna arrays and spatial phase differences enable direction-of-arrival estimation.

⚡ Implement and compare Spatial FFT, Bartlett, Capon/MVDR, MUSIC, and ESPRIT DoA estimation methods.

⚡ Evaluate angular resolution, estimation accuracy, and limitations of conventional and super-resolution DoA methods.

⚡ Process real FMCW radar measurements from a TDM MIMO virtual antenna array for direction-of-arrival estimation.

⚡ Validate DoA algorithms using real AWR2243 measurements with single-target and two-target radar scenarios.
Requirements

❗ Basic understanding of digital signal processing and complex-valued signals.

❗ Basic knowledge of Python and NumPy is recommended.

❗ Basic familiarity with FMCW radar is helpful but not required.

❗ No radar hardware is required; measurement data and processing scripts are provided.

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