Digital Signal Processing for Automotive Systems

Sampling, transforms, filtering, and spectral analysis applied to the ADAS, radar, LiDAR, and sensor signals your programs depend on.

Private cohorts & on-site
Format: 3-day (8:30 a.m.–4:30 p.m.)
Level: Advanced
Location: Scheduled on demand · on-site at your facility or a regional venue
Date(s): Not yet scheduled for open enrollment. Get notified when it is, or book it privately for your team.
Includes: Certificate of Completion · printed slide binder · take-home reference text

Get notified when this course is scheduled

One email when dates are set. Or skip the wait: run it as a private cohort, on-site at your plant.

Talk to us about a private cohort
  • One email, no sequence
  • Never shared
  • Reply within one business day

Faculty

Faculty details for this seminar will be announced with the full schedule.

Fees

Early: $1,895 (payment 4+ weeks ahead)
Standard: $2,095 (check/ACH) · $2,165 (card)

Group discount: $200 off per attendee for 3+ from the same organization.

Also Available

  • Corporate on-site delivery at your facility
  • Private cohort sessions
  • Digital curriculum licensing

Seminar Overview

ADAS, radar, LiDAR, audio, engine control, and every sensor signal in a modern vehicle is processed digitally — and the signal-processing discipline that makes sense of it is rarely taught to mechanical and plastics engineers. Built from MIT OpenCourseWare's signal-processing and electrical-engineering curriculum, this seminar teaches digital signal processing fundamentals: sampling and aliasing, transforms, filtering, and spectral analysis — applied to the automotive signals your ADAS and control work depends on. It closes the gap between the physics you know and the signals your systems process.

Ideal Learner

  • ADAS, perception, and sensor engineers on vehicle programs
  • Electronics and embedded engineers processing sensor data
  • Controls engineers analyzing signals and systems
  • Mechanical engineers moving into signal-heavy subsystems
  • Engineers who must specify or debug DSP pipelines

Learning Objectives

  • Explain sampling, aliasing, and the Nyquist constraint
  • Apply the Fourier, Z, and wavelet transforms to real signals
  • Design and select filters (FIR/IIR) for engineering applications
  • Perform spectral analysis of vibration, noise, and sensor data
  • Specify and debug DSP pipelines in automotive systems

Consulting Sessions

Seminar attendees can sign up for individual consulting sessions with the instructor. Sessions are free for registered attendees, first-come first-served — sign up when registering by calling 248-539-0473 or during the seminar.

Seminar Outline

  • Continuous vs. discrete signals, sampling, aliasing
  • The Nyquist criterion in practice
  • Quantization and its effect on sensor data
  • The DFT/FFT and its meaning
  • Frequency-domain interpretation of signals
  • Windows, leakage, and resolution trade-offs
  • FIR vs. IIR filters and their properties
  • Designing low/high/band-pass filters
  • Filtering vibration, noise, and sensor streams
  • Power spectral density and its estimation
  • Analyzing vibration, sound, and rotating machinery
  • Extracting features for diagnostics and control
  • ADAS sensor pipelines: radar, LiDAR, camera
  • ECU and in-vehicle network signal processing
  • Real-time constraints and implementation
  • From requirement to filter and analysis design
  • Numerical and latency trade-offs
  • Debugging signal-processing artifacts
  • Attendees analyze a real vibration/sensor signal
  • Filter, transform, and extract features
  • Present the signal-processing conclusion

More in Track H — Electrical & Electronic Engineering

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