# An Indoor DFEC Ranging Method for Homologous Base Station Based on GPS L1 and BeiDou B1 Signals
## 1 Introduction  
Indoor navigation and positioning technology can be understood as the use of various technical means to achieve the positioning and tracking of people and objects in indoor spaces. With the development of the Internet of Things technology, there are more and more positioning needs of people and objects in economic behavior, personal activities, and military applications. In the outdoor environment, the global satellite navigation system is a universal and mature positioning method that allows people to achieve navigation and positioning outdoors. However, with the increasing indoorspace today, the continuous construction of various factory workshops, large shopping malls, office buildings, and subway stations, indoor-based navigation and positioning is essential for the safety and monitoring of people and objects. The demand for location services in an indoor environment has become increasingly significant. People's location service needs in indoor environments have become increasingly significant. According to the country's future comprehensive PNT system construction needs, indoor navigation will be one of the three major national development directions. Scholars at home and abroad have conducted a lot of exploration and research. The previous positioning methods are roughly divided into three categories: sensor positioning based on recursive navigation, positioning based on feature point matching, and positioning based on base station signal ranging. The three methods have been developed in recent years, but there are still constraints. Here, this article only discusses the way of base station ranging  
In the environment of indoor complex spatial characteristics, the biggest problem facing the current base station ranging method is the problem of inaccurate ranging. Due to the complex indoor spatial environment and serious signal multipath effects, the ranging values obtained indoors are usually difficult to meet the positioning needs. In the current positioning technology means, there are two methods of direct ranging and indirect ranging. For example, positioning methods based on signal strength and feature matching, we can consider that indirect ranging methods are used for location estimation. [PERSON], AU uses the combination of WIFI and Bluetooth data for location research [1], [PERSON] and [PERSON] explores the mechanism of indoor location through algorithm combination based on signal strength [2; 3; 4]. Vazhenin, N.A. used mobile base stations to perform positioning tests by modifying existing WIFI signal characteristics [5]. [PERSON] and [PERSON] Improve the WIFI positioning accuracy from the perspective of proximity weighted matching and distance constraint by constructing a fingerprint database [6; 7]. [PERSON] In the research process, the recursive principle of PDR was used to improve the indoor positioning service through the combination of recursion and WIFI correction [8]. [PERSON] Using the principles of WIFI RTT and RSS ranging, combined with the hyperbolic positioning algorithm, to carry out related positioning research on mobile phones [9]. However, at present, the positioning accuracy based on WIFI is still poor, and the positioning accuracy is usually 5-10 m. Visible light, which uses the intensity of light signal arrival or the flicker frequency of the light signal to achieve indoor positioning, [PERSON] and [PERSON]'s technical team analyzed the factors affecting the positioning accuracy from multiple angles [10; 11]. The team of [PERSON] analyzed the influence of this phenomenon on positioning based on the instability of visible light power [12]. [PERSON] used the RF Carrier Allocation Technique to construct a visible light system that integrates communication and navigation [13]. [PERSON] used visible angle to achieve indoor positioning [14; 15]. This method has good positioning accuracy in a certain area, but requires a specific lamp design, so there is difficulty in promotion.