## 1 Introduction  
The problem of indoor localization has been the subject of intense study and research in recent years. So far, successful proposals have been developed to provide solutions for specific applications, with varying degrees of accuracy and complexity. However, universal implementation of global positioning systems for outdoor areas is still far from being achieved. The ultimate objective is to combine indoor and outdoor positioning systems. The challenge is to be able to provide an end user with a continuous and transparent navigation solution, regardless of whether one has outdoor coverage or is in an indoor environment. Knowing the user's position can be of great added value; it can expand the capabilities of multiple applications, especially for activities in indoor environments. In indoor positioning, where the environment is complex (walls, objects, etc. ), no technology prevails as global navigation satellite systems (GNSS) do in outdoor positioning systems. Sometimes the target environment restricts the design to a particular indoor positioning system (IPS) technology, directly related to accuracy, range, or scalability [1, 2, 3, 4, 5]. Indoor positioning data shall enable numerous relevant applications, such as pedestrian tracking [6]; location-based services [7, 8] in public and commercial centers [9]; assistance services in daily activities (ambient assistant living (AAL)) [10]; location and tracking of users in geriatric and hospital centers [11, 12]; location and tracking of emergency intervention agents (e.g., police/firefighters) [13, 14, 15]; location and guidance of autonomous vehicles in industrial environments and automated car parks [16, 17]; tracking of high value goods during storage; extra information for users via augmented reality [18; 19]; and Internet of Things (IoT) [20]. Multiple IPSs have already been deployed, such as [9; 21; 22; 23]. As there is no prevailing technology for indoor positioning, several research efforts have used mixed indoor positioning hybrid systems based on different technologies. Many different IPSs have been proposed over the years [3; 24], some of which are based on computer vision [24]; radio waves, such as ultrawideband (UWB) [25] and radio frequency identification (RFID) [26]; ultrasound [27]; optical signals [28]; and more recently, inertial measurement units (IMUs) [6; 29; 30] and radio frequency (RF) communications networks such as the global systems for mobile communications (GSM) and wireless local area networks (WLANs) [31]. Some technologies, such as infrared and ultrasound, are very low-cost IPS solutions that are easy to deploy, low maintenance, provide highly accurate location results, and can be used in a wide range of applications. There are many requirements and parameters to consider when making the choice of technology for a given IPS application. As [1] indicates, the following parameters can be considered: measurement accuracy, location accuracy, coverage area, required infrastructure, market maturity, data security and privacy, update speed of infrastructure nodes and mobile agents, end-user interface, system integrity, robustness, availability, scalability, number of potential users, possible degree of intrusion, legal coverage, etc. Advances in materials, electronics, and communication technologies facilitate continuous improvement in the performance of available sensing systems. The choices of sensors clearly depend on the applications' and users' requirements. The continuous evolution of IPSs can be shown through various works aimed at reviewing the state of the art [1; 2; 3; 4; 5]. Due to the deployment of LED lighting, more and more solutions are being developed that use visible light to both illuminate and communicate/transmit data (VLC--visible light communication) and positioning (visible light positioning) [32; 33; 34; 35; 36; 37; 38; 39].