Inertial deeply aided GNSS positioning for spinning platform

Abstract

GNSS positioning in high dynamic circumstances is an extremely challenging technology due to inevitably severe Doppler frequency shift. Especially for spinning platform, the conventional GNSS receiver cannot work reliably without the exact estimation on motion state of the maneuvering spinning platform. In this paper, the inertial aided GNSS ultra-tightly coupled integrated navigation algorithm is proposed to solve the issues in navigation and positioning in high dynamic circumstances. In the proposed integrated navigation solution, the inertial navigation system is utilized to aid the satellite navigation system to deal with tracking loop errors of the GNSS signal by estimating Doppler frequency shift with IMU, which provides the attitude transformation matrix and the velocity of the platform. Moreover, the noise bandwidth of carrier loop and the correlator spacing are reduced. As a result, the accuracies of the carrier and code tracking loops are improved significantly. In order to implement the closed-loop modification, an Unscented Kalman Filter is designed to estimate the errors of state parameters in the navigation system. Meanwhile, the accumulated error of inertial navigation system could be promptly removed in every fifty milliseconds by exploiting feedback adjustment. To verify the correctness and validity of the proposed algorithm, an ultra-tight integrated navigation simulated system is also designed. The simulation results show that the ultra-tightly coupled integrated navigation algorithm is capable to improve the stability and accuracy of integrated navigation system, which could be applied in various high dynamic circumstances.