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).
