Optimal Post-Detection Integration Technique for the Reacquisition of Weak GNSS Signals

TL;DR

This paper develops optimal non-coherent detection methods for reacquiring weak GNSS signals, improving detection probability over conventional methods, with practical considerations of complexity and performance trade-offs.

Contribution

It introduces Bayesian and GLRT-based detectors for weak GNSS signal reacquisition, including simplified versions with reduced complexity and minimal performance loss.

Findings

Proposed detectors outperform conventional high sensitivity GNSS detectors.

Approximate detectors offer similar performance with lower computational cost.

Guidelines for selecting the best technique based on performance and complexity.

Abstract

This paper tackles the problem of finding the optimal non-coherent detector for the reacquisition of weak Global Navigation Satellite System (GNSS) signals in the presence of bits and phase uncertainty. Two solutions are derived based on using two detection frameworks: the Bayesian approach and the generalized likelihood ratio test (GLRT). We also derive approximate detectors of reduced computation complexity and without noticeable performance degradation. Simulation results reveal a clear improvement of the detection probability for the proposed techniques with respect to the conventional detectors implemented in high sensitivity GNSS (HS-GNSS) receivers to acquire weak GNSS signals. Finally, we draw conclusions on which is the best technique to reacquire weak GNSS signals in practice considering a trade-off between performance and complexity.