Globalstar

Yu Zhang, H. Qin, Guangting Shi

As one of the early low Earth orbit (LEO) communication satellite constellations, Globalstar provides voice communication, Internet of Things (IoT), and cooperative positioning services. In this paper, considering the unknown signal specifications of Globalstar signals, we first examine the common characteristics of LEO constellation signals affected by high-speed motion. We then analyze the complicated modulation scheme of Globalstar pilot signals. By adequately processing the sampled signals of opportunity from Globalstar, we successfully extract the Doppler frequency. Finally, we perform Doppler positioning, achieving a non-cooperative horizontal positioning capability for Globalstar with an accuracy superior to 300 meters.

Ahmad Esmaeilkhah, Rene Jr Landry

Xing Liu, J. López-Salcedo, Gonzalo Seco-Granados, Tareq Y. Al-Naffouri

Opportunistic navigation using low Earth orbit (LEO) satellites has emerged as a promising alternative and complement to global navigation satellite systems (GNSS). Globalstar is a noteworthy LEO constellation for this application, as it employs a spread-spectrum modulation principle similar to that used in most GNSS systems. A significant challenge in processing Globalstar signals lies in the absence of documented specifications on the spreading code sequences. This paper explores an approach to deriving these codes using the limited available information. It then examines the acquisition and tracking of Globalstar satellite signals for opportunistic navigation. The experimental results validate the successful generation of the pseudorandom codes and the reliability of the signal acquisition and tracking process, highlighting the potential of Globalstar satellites for navigation applications.

O. Peña, Gonzalo Seco-Granados, J. López-Salcedo

It is nowadays widely accepted that the future of satellite-based positioning will comprise the combination of conventional Global Navigation Satellite Systems (GNSS) with new Low-Earth Orbit (LEO) satellites specifically designed for positioning, navigation and timing (PNT). In the meantime, opportunistic positioning using existing LEO constellations has become a practical way to showcase the benefits of incorporating LEO satellites in the PNT domain. Among these constellations, Globalstar is particularly interesting because it shares the same spread-spectrum modulation principle as most GNSS. Therefore, Globalstar signals could easily be processed by GNSS receivers with some minor modifications. Unfortunately, the spreading codes for Globalstar are not publicly available, thus preventing the optimal receiver implementation. While some attempts have been done to estimate such codes, or to get rid of them, the present paper shows that tracking of Globalstar signals is possible using a set of, presumably, very similar spreading code sequences to the ones actually used by Globalstar satellites. Experimental results with live recorded signals are provided to confirm this statement.

Yu Zhang, Honglei Qin, Guangting Shi, Mingyuan Yang, Yanxu Chen

Low Earth orbit (LEO) communication constellations, as signal sources of opportunity, can be utilized to provide positioning, navigation, and timing (PNT) services, serving as an important backup to the global navigation satellite systems (GNSSs). Moreover, location information is a critical component in many Internet of Things (IoT) applications. The Globalstar constellation, which has launched bidirectional IoT modules, has recently broadcast a new downlink periodic burst signal composed of chirp signals and quadrature phase shift keying (QPSK)-modulated direct-sequence spread spectrum (DSSS) signals. To address the challenge of unknown signal parameters, this article first establishes a blind parameter estimation framework to enable noncooperative recovery of the complete signal structure, including frame structure, modulation parameters, and spreading-code sequences. Considering the weak signal strength and burst-type transmission characteristics, an iterative cascaded parallel search (ICPS) method is further proposed. ICPS consists of two stages: the iterative equivalent matching filtering (IEMF) method for coarse synchronization, and the cascaded parallel search (CPS) method for precise synchronization. This framework enables fast and accurate signal detection and time-frequency synchronization, thereby facilitating Doppler extraction. Based on real-world measurement data, the proposed framework successfully extracts signal parameters and validates the effectiveness of the ICPS algorithm. Subsequently, Doppler-based positioning equations are constructed, and Doppler positioning is performed.