Bayesian EM approach for GNSS parameters of interest estimation under constant modulus interference

Abstract

Abstract Interferences pose a significant risk to applications that rely on global navigation satellite systems (GNSSs). They have the potential to degrade GNSS performance and even result in service disruptions. The most notable type of intentional interference is characterized by a constant modulus, such as chirp and tone interferences. These interferences have a straightforward structure, leading to the creation of complex circles when attempting to identify their contribution. To address the interference and improve the situation, we calculate the maximum likelihood estimator for the relevant parameters (time delay and Doppler shift) while considering the presence of these latent variables. To achieve this, we employ the expectation–maximization algorithm, which has previously demonstrated its effectiveness in similar scenarios. Experiments conducted using synthetic signals confirm the efficiency of the proposed algorithm.

Keywords

• Maximum likelihood
• Expectation–maximization
• GNSS
• Interference
• Von Mises distribution