# Design and Validation of a Cascading Vector Tracking Loop in High Dynamic Environments
## 1 Introduction  
Since the advent of the global positioning system (GPS), the global navigation satellite system (GNSS) has become the most efficient technology for positioning. Normally, according to some location solution methods, such as the Real Time Kinematic (RTK) or the Precise Point Positioning (PPP), the accuracy of GNSS positioning is guaranteed, but the upper limit of positioning accuracy is determined by the quality of signal tracking. In some special circumstances (e.g., low signal to noise ratio or high dynamics), the GNSS receiver has no tracking ability or low tracking quality, causing invalid positioning. In 1998, NF Krasner [1] introduced the automatic frequency control (AFC) loop into the GNSS receiver for locking carriers for better navigation signal tracking. The AFC method tracks the carrier frequency by repeatedly adjusting a series of CNC oscillators with simple structures and low accuracies [2]. In 1987, maximum likelihood estimation (MLE) was used to track GPS signals [3], with high estimated frequency accuracy but a complex structure [4]. Many estimation methods are being used in signal tracking, such as fast Fourier transform [5] and adaptive least mean square [6]. However, the many tracking methods are limited to the signal field, only utilizing a single channel to deal with signal tracking. The carrier loop structure using Kalman filter (KF) is more flexible than MLE and other estimation technologies [7; 8], and the estimation accuracy varies with the KF type selected. We used unscented KF (UKF) technology in our subsequent carrier tracking solutions because UKF has been proven equally accurate as the third order EKF [9]. In 1996, [PERSON] first proposed the vector tracking loop [9], which combines the tracking loop with the positioning module as an integral loop. In the traditional receiver structure, the tracking loop and the positioning module are independent of each other, with data flowing in one direction and independent signal channels. Thus, no information exchange occurs between channels, which makes aiding weak signals according to the strong signals of channels impossible. Compared with the traditional loop, the vector loop can make full use of the information of each channel [10; 11] and the positioning message feedback in the tracking loop to easily achieve deep integration with other sensors [12; 13]. The vector loop completely utilizes signal information for the receiver to work in a low Carrier to Noise Ratio (CNR) environment [14]. The vector loop is an advanced structure that provides performance improvements in many circumstances. The advantage of vector tracking technology in a highly sensitive receiver is explained with a theoretical formula in [14]. On the basis of the vector loop, the structure of the ultra-tight integration navigation system was explored. The advantages of vector tracking in anti-jamming were verified [15]. Vector tracking is a navigation signal processing structure in which different estimation methods form different vector loops. The influences of different KFs on the ultra-tight integrated navigation system based on vector tracking are discussed in [16], which can serve as a reference for the implementation of subsequent projects. Given the tracking loop and positioning module combination, the frequency of positioning must be promoted to guarantee the accuracy of tracking. Therefore, the computational cost of vector tracking must be considered. Continuous explorations are conducted to reduce the calculation cost. In terms of structural improvement, a study [17] provides a balance between the pure Vector Phase Lock Loop (VPLL) and the classic scalar tracking loops and results in increased tolerance to ionospheric disturbances. According to the corresponding decision conditions of the vector structure, optimal positioning results can be obtained with the minimum computation based on indoor navigation [18]. A study [19] used the vector tracking structure to minimize the effect of multipath interference and aid NLOS detection.