Radar Localization and Integration for Future Autonomous Car Navigation

The purpose of this project is to offer low-cost navigation solutions for autonomous vehicles based on automotive radars that can work efficiently in all weather conditions and degraded vision environments. Radar will be utilized to estimate the vehicle’s relative position. The radar solution will be integrated with the inertial navigation system (INS) solution to limit inertial sensors’ drifts, enhance navigation accuracy, and compensate for GNSS signal outages. Different algorithms will be applied in that project to fulfill the required goal. The expected benefits to Profound Positioning Inc. (PPI) through my internship can be substantial and multifaceted, primarily driven by my extensive expertise in navigation systems, sensor fusion, and autonomous technologies. My strong academic background and research experience in Geomatics Engineering, particularly in inertial sensor navigation, radar applications, and sensor fusion, will give the company significant technical knowledge and a unique perspective in developing advanced navigation solutions. The research will provide Profound Positioning Inc. with the expertise to design a low-cost dead-reckoning navigation system that promises high performance, integrating quite well with its products. Moreover, the proposed research could further strengthen Profound Positioning Inc. substantially, performing products designed to perform navigation in harsh environments and degraded or denied GNSS environments.

Faculty Supervisor:

Hongzhou Yang

Student:

Partner:

Profound Positioning Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Calgary

Program: