Abstract

The key objective of this research is to develop a new method for GNSS ambiguity resolution based on mixed integer non-linear programming (MINLP). Instead of separating the ambiguity resolution process individually from GNSS positioning through LAMBDA method. This research tries to integrate the ambiguity resolution process with the position estimation process together. In this integrated method, the GNSS observation and other estimated parameter information can help optimize the integer ambiguity estimation. This research will realize this algorithm first and verify the validity of this algorithm based on simulation data. A comparison of this novel algorithm and conventional GNSS ambiguity fixed with LAMBDA method will be conducted. Based on aforementioned work, this algorithm will be tested with real observations then. The final goal is to apply this novel algorithm in GNSS positioning in highly urban environment, like in Hong Kong. This research aims to improve the integer ambiguity resolution performance in complicated environment which brings great challenge to precise positioning due to the contamination of non-line-of-sight signals and multipath.

Dr. Wen, W. and Penggao Yan.

Scholarship Plan

• (1st year) 09/2022-08/2023: PPPFS
• (2nd year) 09/2023-08/2024: PPPFS
• (3rd year) 09/2024-08/2025: PPPFS

Recent Research Plan: Zhang Honming

Student Supervision

• Supervise Edward? (undergraduate student)

News

• 3 papers by year 2023

• [01/02/2022]

  • work on the paper for the IEEE PLANS 2023
  • work on the Kalman filtering based LiDAR/inertial integration with 2D LiDAR. The noise of the LiDAR measurement is modelled with the GMM.