^4fGPS/INS Integrated Navigation System Using Multi-Antenna of GPS

摘要

^7fThe INS and GPS integration can improve the accuracy of position and velocity of INS. However, since the weakly observability, especially for ship INS, the azimuth performance can't make much progress. If adding with attitude data additionally, the weakness can be made up. Using Multi-antenna and efficient method, the GPS carrier phase observations can be used to measure the attitude. In this paper, a new extended Kalman Filter algorithm is firstly presented for attitude estimation using GPS differential carrier phase measurements. Then, the integration method for GPS and INS using attitude information is introduced. Based on them, the efficiencies of the new attitude algorithm and the integration method are demonstrated through numerical example which simulate the movement of a ship on the condition of calm sea. Inertial Navigation System (INS) and Global Positioning System (GPS) both have been used fora wide range of navigation functions. They have some strengths and weaknesses inherent in them, respectively. Combination INS and GPS can make up some weaknesses, and improve the accuracy of position and velocity of INS. However, in the alignment of INS or some application such as marine, the attitude accuracy, especially azimuth can't make much progress because of the weakly observability when INS coupled with single GPS. Using the measurements of multi-antenna mounted on vehicle's body, interferometric GPS system can provide orientation information. If couple it and INS, not only the accuracy of position but the attitude can achieve a good perfomance. Therefor, the integrated system of interferometirc GPS with INS has been intensively investigated in recent years. The connected way can be classified two kinds: one is loosely coupled model, another is tightly coupled model. In the former, both GPS and INS output the position, velocity and attitude information, respectively. In the latter, GPS provides not the attitude information directly, but the differential carrier phase measuments. Compared with the latter, the former is more simple and reliable. One of its keys is how to measure attitude effectively using GPS. In this paper, a new extended Kalman Filter algorithm is firstly presented for attitude estimation using GPS.