# An Algorithm to Assist the Robust Filter for Tightly Coupled RTK/INS Navigation System
## 1 Introduction
Furthermore, INS is subject to error accumulation, which means a standalone INS without external correction can drift from the ground truth rapidly [6; 20]. Cameras, Lidars, and odometers can also be used to assist RTK [21; 22; 23]. There are three main GNSS/INS integration strategies: loosely coupled (LC), tightly coupled (TC), and deeply coupled (DC) integration [24]. The integration implementation is usually based on an Extended Kalman Filter (EKF). In LC integration, GNSS and INS work independently to generate their own navigation solution. Then, the GNSS outputs, including position and velocity, are used as measurements to correct the bias of INS. The LC integration process is easy to implement and achieves higher accuracy and integrity when compared to standalone GNSS. However, LC integration does not contribute to GNSS receiver acquisition and tracking. Furthermore, LC integration can only depend on standalone INS during GNSS outages as the GNSS receiver cannot generate a navigation solution when visible satellites are less than four [25; 26]. TC integration replaces the separate filter for the GNSS receiver with a centralized EKF that simultaneously processes INS parameters and GNSS raw observations, including pseudo range, carrier phase, and Doppler. TC integration is optimal in preventing GNSS outages because the INS correction is continuous even though there are less than four available satellites. However, the implementation complexity of TC integration is higher when compared to that of LC integration. In addition, TC integration still does not improve the GNSS tracking loop [27; 28]. DC integration is developed from TC integration. DC integration uses the GNSS tracking loop's parameters, including code phase error and carrier frequency error estimations, to form the measurements of the integration EKF. Then, the dynamic information from INS is fed back to assist the tracking loop. The optimal fusion of GNSS and INS brings higher accuracy and disturbance resistance. Furthermore, DC integration provides better acquisition performance. However, researchers have to face the highest cost and complexity. What is more, DC integration is limited in commercial use because users can hardly have access to the baseband processing systems of commercial GNSS chipsets [29; 30; 31]. Notably, LC integration uses the GNSS positioning results for EKF, whereas TC integration and DC integration use separate satellite measurements for EKF. TC integration and DC integration provide the possibility to use INS to assist in excluding potential outlying satellite measurements [31]. The characteristics of these three integration strategies are summarized in Table 1 to make the comparison clearer. In this study, we focus on the TC RTK/INS integration. Many researchers have studied the improvement of the TC RTK/INS integration when compared to standalone RTK and LC RTK/INS. The introduction of INS can help detect and repair cycle slips caused by signal loss. INS is particularly useful in single-frequency RTK cycle slip detection because dual-frequency RTK can fully utilize the geometry-free phase combination [32]. Commonly used INS-based methods for detecting cycle slip include innovation tests [33] and time-differenced residuals methods [34; 35]. AR also benefits from INS aiding as prior information from INS can be used to improve the accuracy of float solution and reduce the search space of AR [12; 36]. Studies have shown INS can provide high-precision short-term positioning results, which act as a strong constraint or \"virtual measurements\" to improve the probability of correctly fixing the ambiguities [12; 37]. In recent years, researchers have continued improving the architecture of TC RTK/INS integration, which attains better accuracy and stability of AR [38]. Furthermore, TC RTK/INS integration can utilize some innovation-based strategies to detect and resist large errors in the measurements, which makes the filter more robust and reliable [39].