CSL student receives best presentation award for GPS research at GNSS conference

GPS signals are effective for location tracking in open sky environments, but in dense urban environments, they can be less reliable.

Ashwin Kanhere was awarded “Best Presentation of the Session” for his paper, “Integrity for GPS/LiDAR Fusion Utilizing a RAIM Framework,” which demonstrates that laser measurements can help compensate for GPS loss in noisy environments. Kanhere, a graduate student in aerospace engineering, received the award last month at the Institute of Navigation (ION) Global Navigation Satellite Systems (GNSS) conference in Florida, along with his advisor and co-author, CSL’s Grace X. Gao.

Kanhere presented research that focused on the integrity of a GPS-LiDAR sensor fusion navigation solution. With developments in autonomous cars and drones, there is a growing need for improved location tracking and methods to detect and isolate faulty measurements. That is where laser measurements can be useful.

While obstructions, such as tall buildings on both sides of a street, can degrade the quality of a GPS signal, the same features can actually provide improved localization performance for laser scans.

“When you combine lasers and GPS, not only do you get better position estimates, but you have more measurements overall to perform fault detection,” Kanhere said.

Kanhere said the research up to this point was a proof of concept for the fault detection and isolation algorithm. Now that they know it’s possible, the group hopes to extend the research to finding measurement faults inside individual laser point clouds.

“For safety-critical applications, such as autonomous driving, it is important to navigate not only accurately, but with high integrity and confidence. We are excited to work in this domain,” said Gao, assistant professor of electrical and computer engineering.

Gao had three other students also present at the conference, Tara Mina, “Multi-Receiver GPS Signal Authentication against Spoofing for Power Systems”; Siddharth Tanwar “Decentralized Collaborative Localization in Urban Environments using 3D-mapping-aided GNSS and Inter-Agent Ranging”; and Sriramya Bhamidipati “SLAM-based RAIM for Multiple Fault Detection and Isolation.”