# A Review of High-Sensitivity Tracking Techniques for Satellite Navigation Signals
## 1 Introduction  
With improvements in living standards and advancements in science and technology, the demand for accurate positioning in daily life has increased significantly. This has driven the development of various positioning technologies, including the Global Navigation Satellite System (GNSS), Bluetooth, Ultra-Wideband (UWB), and Wi-Fi [1]. Among these, GNSS stands out due to its wide coverage and diverse range of applications [2]. Since its successful introduction, GNSS has been deployed extensively in various scenarios [3], and the rise of automation and intelligent systems has expanded its applications even further. Technological advancements such as autonomous driving and Unmanned Aerial Vehicle (UAV) navigation have heightened the demand for Positioning, Navigation, and Timing (PNT) solutions capable of providing high accuracy, even in challenging environments like urban canyons and indoor spaces [4]. Currently, standard GNSS technology meets most positioning needs under Line-of-Sight (LOS) conditions. However, it faces significant limitations in complex environments, such as urban canyons and indoor spaces. The primary factor affecting GNSS performance in these settings is the signal-to-noise ratio (SNR), which is typically 10 to 30 dB lower thanin open areas [5]. As a result, standard GNSS technology struggles to deliver sufficient positioning accuracy and reliability in these environments [6]. To address these challenges, the development of high-sensitivity positioning technologies is essential. These technologies are designed to provide precise and reliable positioning information even in low SNR and complex environments [7]. High-sensitivity positioning is particularly crucial in applications that require high accuracy and reliability. For smart unmanned systems, such as autonomous vehicles and drones, reliable positioning is vital for real-time decision-making, path planning, and mission execution. High-sensitivity positioning ensures safe navigation and operation in challenging environments like cities, forests, and mountains. Furthermore, the demand for high-sensitivity positioning is becoming more urgent with the advent of miniaturized, consumer-grade smart wearable devices [8]. Compact antenna designs, with their negative gain and high front-end loss, often result in low equivalent carrier-to-noise ratios, thus compromising signal reception quality. Additionally, for other smart mobile devices, such as smartphones, high-sensitivity positioning can significantly improve the accuracy of indoor navigation, location-based services, and augmented reality applications [9]. A key component in achieving high-sensitivity positioning is the effective tracking of navigation signals [10]. The satellite signal tracking module consists of two main components: carrier tracking and pseudo-code tracking. Notably, the sensitivity of the code tracking loop is typically 5 to 9 dB higher than that of the carrier tracking loop, and the frequency change rate of the pseudo-code is only 1/1000 th of that of the carrier frequency [5]. In complex environments, the sensitivity of carrier tracking becomes the decisive factor in determining the overall tracking performance of the receiver. Although the importance of high-sensitivity tracking techniques is increasingly recognized, the existing literature still lacks a systematic and structured review of this field. To address this gap, this paper makes the following key contributions. First, it proposes a unified classification framework that systematically categorizes high-sensitivity GNSS signal tracking techniques into four major types: scalar tracking, vector tracking, conventional open-loop processing, and Direct Position Estimation (DPE). This classification clearly delineates their fundamental principles and applicable scenarios.