## 1 Introduction  
In the context of intelligent transportation systems, vehicle localization plays a pivotal role in enabling autonomous and semi-autonomous functionalities. Accurate localization allows vehicles to determine their position with high precision, which is essential for safe navigation, decision-making, and interaction with dynamic environments. As intelligent vehicles become increasingly integrated with advanced perception and control systems, the demand for robust and reliable localization methods continues to grow [1, 2]. Localization plays a critical role in various aspects of our daily lives, from aiding vehicle rescue operations to simplifying parking and enhancing navigation. Beyond these practical applications, localization data have taken on a pivotal role in the broader landscape of the Internet of Things (IoT). In scenarios where human presence or direct involvement may be limited, the provision of precise location information to IoT devices has become indispensable. There are two basic ways to obtain a navigation solution: dead reckoning (DR) and position fixing [3; 4]. DR is a navigation method that estimates position based on prior knowledge of the initial location, heading, and velocity. This principle is analogous to the operational concept of an inertial navigation system (INS) in autonomous mode, where position updates are derived from initial conditions and the continuous integration of inertial sensor outputs. In contrast, position fixing, where the location is derived from external references such as Global Navigation Satellite Systems (GNSSs), serves as an excellent example. The navigation system can be independent, rely on external sources, or combine both. A Global Positioning System (GPS) requires the assistance of other sources, such as cellular base stations, motion sensors such as (compass, inertial sensors, odometer), Wi-Fi, aiding sensors such as Radar, LIDAR and cameras, and digital maps to enhance localization [5; 6]. Among the numerous navigation techniques available, satellite navigation and inertial navigation are the most common. It is possible to unlock new levels of connectivity and location-based services in the IoT landscape by integrating GNSS/INS capabilities into smartphones. This will have a significant impact on a variety of businesses as well as our daily lives. The IoT gains an essential layer of spatial awareness thanks to the inclusion of GNSS and INS in smartphones. Smartphones can determine their precise position on the Earth's surface using GNSS technology, which offers accurate Position, Velocity, and Time (PVT) solutions through satellite constellations such as GPS, GLONASS, Galileo, and BeiDou. However, standard GNSS receivers are not capable of independently determining device orientation. To overcome this limitation, smartphones integrate GNSS with INS, which utilize onboard sensors--such as accelerometers, gyroscopes, and, sometimes, magnetometers--to track motion and orientation. Additionally, orientation information can be further enhanced through the use of multi-antenna GNSS configurations or other complementary sensors [3]. This fusion enables smartphones to provide robust navigation capabilities, including not only position and velocity but also reliable orientation estimation [2; 7]. The seamless integration of GNSS and INS technologies in smartphones not only extends the capabilities of the IoT but also brings new dimensions to the world of intelligent vehicles. 1. It allows for the continuous surveillance and monitoring of assets and resources. This integration can be used to optimize operations, increase efficiency, and reduce costs in industries such as logistics, supply chain management, and transportation. Companies, for example, may properly track shipments in real-time, monitor routes, and ensure timely deliveries by equipping delivery vehicles with cellphones equipped with a GNSS/INS [2]. 2. Context-aware services and personalized experiences are made possible by the integration of GNSS/INS in smartphones.