Very Precise Point Positioing by Using Multiple Antennas and Applications

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K06609
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Aerospace engineering
• Research Institution: Ritsumeikan University
• Principal Investigator: Sugimoto Sueo 立命館大学, 理工学部, 授業担当講師 (70093424)
• Co-Investigator(Kenkyū-buntansha): 久保 幸弘 立命館大学, 理工学部, 教授 (00388125)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: 超精密測位(VPPP) / 精密測位(PPP) / カルマンフィルタ / GNSSジャイロ / 複数のGNSS受信機 / 受信機間距離拘束 / GNSS回帰モデル / オイラー角

Outline of Final Research Achievements

We have developed new VPPP algorithms and attitude estimation algorithms (so-called; GNSS GYRO) using multiple low cost single frequency antennas based on GNSS Regression measurement models (GR models). By using the double differences for GNSS observables by multiple antennas with constraints of solid geometrical distances among antennas, we developed new Kalman filtering algorithms of all antennas' positions as well as the baseline vectors among antennas. Then using the geometric constraints for all antennas' positions, the updated algorithms of estimated antennas' positions and integer ambiguities by developing new Kalman filter based on the ambiguity resolution methods are derived. Experimental results by using real GNSS data for only ten seconds (10 epochs) from low-cost L1 receivers without using any external transmitted information show that less than 50cm RMS positioning errors and less than 0.2 degree errors of Euler's angles for the attitude estimation are acheived.

Free Research Field

確率システム制御、信号画像処理