A Review of High-Sensitivity Tracking Techniques for Satellite Navigation Signals - Zhiqiang Gong; Honglei Lin; Zhe Liu; Zengjun Liu; Long Huang; Gang Ou (Remote Sensing)
With the increasing demand for high-sensitivity signal tracking in complex environments, GNSS receiver technologies have continuously evolved in both architecture and algorithmic design. This paper presents a systematic review of the development of high-sensitivity tracking techniques, with a focus on the transition from closed-loop to open-loop, hybrid, and deeply integrated architectures. Key strategies—such as coherent integration time extension, discriminator and loop filter optimization, vector tracking (VT), and Direct Position Estimation (DPE) are evaluated in the context of weak signal scenarios. To address the limitations of existing methods, including strong dependence on filter models, oscillator instability, and computational complexity, this study also outlines future research directions, including (1) integrating deep learning techniques into filter structures to enhance adaptability and robustness; (2) developing multi-channel collaborative estimation schemes to mitigate oscillator noise in weak signal environments; and (3) designing low-complexity open-loop tracking approximations to align with hardware resource constraints. Thus, enhancing the necessity of navigation continuity and robustness under low-signal-to-noise-ratio (SNR) conditions.