# A Novel SINS/SRS/CNS Multi-Information Fusion Global Autonomous Navigation Method
## 1 Introduction  
High-altitude and long-endurance flight requires UAVs (unmanned aerial vehicles) to have global autonomous navigation capability [1]. The unique geographical environment of the polar regions puts forward higher requirements for the continuity and smoothness of navigation. SINS (the strapdown inertial navigation system) is applicable to global navigation because of its concealment, real-time operation, and independence from complex environments. However, with the increase in latitude, the east-north-up navigation coordinate frame extensively used in the middle-low latitudes is ineffective because of meridian convergence [2, 3, 4]. Consequently, the transverse geographic coordinate frame that rotates the traditional longitude and latitude lines by 90\({}^{\circ}\) and the grid coordinate frame that is based on the Greenwich meridian plane are presently used [5, 6, 7]. In addition, the SINS errors gradually accumulate, making it difficult to accomplish a UAV high-precision and long-endurance global flight mission. Consequently, it is essential to introduce other navigation information for SINS correction [8]. In recent years, many studies have been carried out on polar navigation. A fault-tolerant grid SINS/DVL (Doppler velocity log)/USBL (ultra-short baseline) integrated algorithm was proposed to improve the reliability and accuracy of polar navigation for ocean space applications [9]. The integrated navigation scheme of transverse SINS/DVL based on the virtual sphere model was proposed, and the navigation accuracy could meet the requirements of an autonomous underwater vehicle [10]. The rotation modulationinertial navigation system algorithm under a grid coordinate frame was studied, and the applied basis of polar navigation was established [11]. An interacting dual-model-based adaptive filter was proposed in INS/GNSS/DVL integrated navigation to overcome nonstationary noise and certain non-Gaussian factors, and ship sailing simulations demonstrated that the proposed architecture and algorithms enhanced navigational performance in the Arctic [12]. A SINS/CNS/GPS integrated navigation system that combines the azimuth navigation algorithm and the grid navigation algorithm was obtained, and the feasibility in the high latitudes was verified [13]. Related studies have achieved remarkable results. However, autonomous navigation technology of multi-information fusion for an airborne application background and transregional switching between middle and high latitudes need further research. To meet the demand for fully autonomous, high-accuracy, and long-endurance navigation, correcting SINS errors with CNS (the celestial navigation system) has already become one research focus of aerospace engineering [14]. The U.S. Air Force has developed various typical airborne SINS/CNS integrated navigation products to meet the requirements of strategic reconnaissance missions [15]. SRS (the spectral redshift navigation system) is a novel autonomous navigation technology that uses the Doppler shift effect of astronomical spectra to realize aircraft navigation with preferable real-time operation and autonomy [16]. The fusion of SINS with SRS and CNS could guarantee the reliability of the navigation system while maintaining a high level of autonomy. In this article, a SINS/SRS/CNS multi-information fusion global autonomous navigation method based on parameter conversion is proposed. Our main contribution is to establish the SINS/SRS/CNS multi-information fusion system equations in different navigation coordinate frames and to derive the navigation and filter parameter conversion relationships between different coordinate frames, ensuring the high autonomy and precision of the UAV global navigation system. The sections of this article are arranged as follows: The design of the scheme of multi-information fusion global autonomous navigation is detailed in Section 2. Section 3 analyzes the principle of spectral redshift navigation.