Collaborative positioning.png

COLLABORATIVE POSITIONING FOR IOT IN SMART CITIES

January 5 - June 13, 2026

Due to the forecasting 5G connectivity, all the road agents are expected to connect together. One potential is to making use of the sensors' measurement from the connected road agents to collaboratively positioning. We IPNL aim to develop a collaborative positioning platform and algorithm to integrate the information. We expect the collaborative positioning will play an important role in the futuristic IoT applications. 

Researchers:

Mr Guohao ZHANG (PhD Student)

Mr Yang SONG (MSc Student)

JOURNAL PUBLICATIONS

Guohao Zhang, Weisong Wen, Li-Ta Hsu

GPS Solutions, 2019, 23(3): 83.

Guohao Zhang, Li-Ta Hsu

Journal of Intelligent & Robotic Systems, 2019, 94(1): 219-235.

Download Slide

Guohao Zhang, Bing Xu, Hoi-Fung Ng, Li-Ta Hsu

Remote Sensing, 2021 (Submitted).

Short Brief: The proposed simulator employs a ray-tracing technique searching for all possible interferences in the urban area. Then, it categorizes them into direct, reflected, diffracted, and multipath signals to simulate the pseudorange, C/N0, and Doppler shift measurements correspondingly. The performance of the proposed simulator is validated through real experimental comparisons with different scenarios based on commercial-grade receivers.

Examples of simulation data (in RINEX format)

COOPERATIVE VISUAL INS WITH MULTIPLE VEHICLES IN WHAMPOA, HONG KONG