Application of Helmert Variance Component Based Adaptive Kalman Filter in Multi-GNSS PPP/INS Tightly Coupled Integration

Zhouzheng Gao,Maorong Ge,Wenbin Shen,Xiaoji Niu,Hongping Zhang

doi:10.3390/rs8070553

Abstract

The integration of the Global Positioning System (GPS) and the Inertial Navigation System (INS) based on Real-time Kinematic (RTK) and Single Point Positioning (SPP) technology have been applied as a powerful approach in kinematic positioning and attitude determination. However, the accuracy of RTK and SPP based GPS/INS integration mode will degrade visibly along with the increasing user-base distance and the quality of pseudo-range. In order to overcome such weaknesses, the tightly coupled integration between GPS Precise Point Positioning (PPP) and INS was proposed recently. Because of the rapid development of the multi-constellation Global Navigation Satellite System (multi-GNSS), we introduce the multi-GNSS into the tightly coupled integration of PPP and INS in this paper. Meanwhile, in order to weaken the impacts of the GNSS observations with low quality and the inaccurate state model on the performance of the multi-GNSS PPP/INS tightly coupled integration, the Helmert variance component estimation based adaptive Kalman filter is employed in the algorithm implementation. Finally, a set of vehicle-borne GPS + BeiDou + GLONASS and Micro-Electro-Mechanical-Systems (MEMS) INS data is analyzed to evaluate the performance of such algorithm. The statistics indicate that the performance of the multi-GNSS PPP/INS tightly coupled integration can be enhanced significantly in terms of both position accuracy and convergence time.

Highlights

Since the integration of the Global Positioning System (GPS) and the Inertial Navigation System (INS) was proposed by Cox in 1978 [1], it has been used widely as an effective and precise tool to obtain precise position, velocity, and attitude in many dynamic domains [2,3,4]
Global Navigation Satellite System (GNSS) observations with low quality and the inaccurate state model on the performance of the multi-GNSS Precise Point Positioning (PPP)/INS tightly coupled integration, the Helmert variance component estimation based adaptive Kalman filter is employed in the algorithm implementation
GPS + BeiDou + GLONASS and Micro-Electro-Mechanical-Systems (MEMS) INS data is analyzed to evaluate the performance of such algorithm

Summary

Introduction

Since the integration of the Global Positioning System (GPS) and the Inertial Navigation System (INS) was proposed by Cox in 1978 [1], it has been used widely as an effective and precise tool to obtain precise position, velocity, and attitude in many dynamic domains [2,3,4]. The SPP based integration system can only provide meter level position accuracy [10,11], which can only be used in the regions without high accuracy requirement. Centimeter level position accuracy can be obtained by using RTK based integration, its performance is highly influenced by the distance between users and base station owing to the decreasing relationship of GPS observations for the station-pair [5]. 2016, 8, 553 a system that can provide high accuracy location information, and overcome the disadvantages in RTK- and SPP- based integration system is urgently required, such as in mobile mapping system and unmanned control system. Remote Sens. 2016, 8, 553 a system that can provide high accuracy location information, and overcome the disadvantages in RTK- and SPP- based integration system is urgently required, such as in mobile mapping system and unmanned control system.

Methods

Findings

Discussion

Conclusion