Design and implement signal processing and sensor fusion algorithms for ultrasonic-based parking assist systems. Collaborate with hardware, software, and systems teams to ensure accurate and reliable distance detection and object recognition in automotive environments.
Key Responsibilities :
- Develop signal processing algorithms for ultrasonic sensors to detect distances and identify obstacles.
- Filter and interpret raw sensor data using methods like Kalman filtering, FFT, envelope detection, and matched filtering.
- Implement sensor fusion algorithms combining ultrasonic data with other sources (e.g., camera, radar).
- Optimize algorithms for real-time embedded implementation.
- Validate algorithm performance using real-world and simulated datasets.
- Contribute to the integration of ultrasonic sensor models in system-level simulations (e.g., with MATLAB / Simulink).
- Support calibration and tuning processes for sensor deployment in vehicles.
- Collaborate with cross-functional teams to ensure compliance with automotive standards (e.g., ISO 26262, AUTOSAR).
Required Skills and Qualifications :
Strong knowledge of digital signal processing (DSP), especially for ultrasonic applications.Proficient in MATLAB / Simulink and / or Python for algorithm development and data analysis.Experience with C / C++ for embedded systems implementation.Understanding of sensor fusion techniques and Kalman filters.Familiarity with automotive communication protocols (e.g., CAN, LIN).Experience with real-time operating systems (RTOS) or embedded Linux is a plus.Knowledge of machine learning methods is a bonus (for obstacle classification or environmental context understanding).Skills Required
Embedded Design, C