An Emergency Positioning System Fusing GEO Satellite Doppler Observation and INS for SOTM

This article presents a newly invented emergency positioning system deployed on a satellite communication on-the-move (SOTM) platform, which can extend the SOTM communication function to the positioning function. Inherent to the SOTM system's high reliability, this emergency positioning system can effectively estimate the vehicle's position by fusing a geosynchronous orbit (GEO) satellite Doppler frequency observation and inertial navigation system (INS) of a SOTM-mounted moving vehicle when the global navigation satellite system (GNSS) is unavailable. It is a great challenge to use GEO Doppler frequency measurement with weak observability to correct the INS's cumulative error to estimate the position of the vehicle. In this article, the traditional inertial measurement unit (IMU) pre-integration model is improved to meet the needs of large-scale and high-precision navigation. In addition, we use graph optimization (GO) to estimate all states in the trajectory, which can effectively improve the observability of the error and reduce the nonlinear influence. We evaluated the system on a Ku-band SOTM platform, and the experimental results indicate that the system can achieve a convergent positioning accuracy of tens of meters. This method can provide emergency positioning in the case of GNSS interference.

I. Introduction

The satellite communication on-the-move (SOTM) system, which can establish a reliable communication link with communication satellites while in motion, is widely used in military and civilian applications. Its essence is an inertial stabilized directional antenna pointing to a geosynchronous orbit (GEO) communication satellite, which can effectively isolate the pointing deviation caused by the vehicle’s dynamics. Meanwhile, the positioning of the vehicle is essential information, especially in military and rescue applications. However, the low-cost global navigation satellite system (GNSS) receiver is susceptible to jamming. There has been significant work conducted on anti-jamming GNSS positioning, such as ultra-tight integration with inertial navigation [1], phased array multi-beam directional antenna [2], and combination of machine vision [3] and LIDAR [4]. Nonetheless, the integration of machine vision and LIDAR may lead to accumulated errors; the ultra-tight integration is difficult to locate under substantial interference, and the phased array antenna is too costly. Real-time positioning under GNSS interference is still an open problem.