Exploring LEO-Aided GPS Direct Position Estimation in Degraded Signal Environments

Abstract

Due to their low received signal power, Global Navigation Satellite Systems (GNSS) are easily subject to radio frequency interference (RFI). Subsequently, extensive research regarding advanced receiver designs that mitigate RFI is ubiquitous. Among these designs is the Direct Position Estimation (DPE) architecture, which addresses the shortcomings of conventional receivers by jointly processing all channels and estimating the receiver state in a single step. Combining each channel’s received power, this single-step methodology proves more robust than receivers that fuse measurements from independently processed channels in two steps. Despite this robustness, DPE can still succumb to the effects of RFI. This thesis discusses the performance capabilities of two DPE architectures that utilize dedicated and opportunistic low Earth orbit (LEO) positioning, navigation, and timing (PNT) sources, respectively, to supplement the Global Positioning System (GPS) in various RFI scenarios. Specifically, a Bayesian DPE approach is applied to each architecture, and necessary modifications are introduced for each LEO source. Furthermore, a methodology that prevents the obfuscation of GNSS information by high-powered LEO signals is presented.

Each architecture’s performance is evaluated using a Monte Carlo analysis that employs a correlator-level simulation of GPS L1 C/A. It is shown that including dedicated and opportunistic LEO sources substantially reduces the root mean square errors (RMSE) associated with the estimated position, velocity, and timing (PVT) states in high GPS attenuation regimes compared to other architectures. Specifically, the proposed architectures are compared to standalone GPS DPE, LEO-aided GPS Vector Processing (VP), and standalone GPS VP. The VP comparisons are included to gauge performance against a two-step methodology. The results also indicate that the probability of tracking GPS in the scenario with the highest RFI increases by up to 85.12 % compared to the additional architectures. Furthermore, a simple computational efficiency study assesses the benefits of aiding the naturally computationally expensive. DPE architecture with dedicated LEO signals. Lastly, an open-source satellite navigation simulation environment is introduced.