## 3 Indoor Positioning Systems
### Systems Based on Radio Frequency
#### 3.1.1 Range-Based
The use of a large bandwidth allows implementing shorter pulses that increase the resolution of time and the accuracy of positioning estimates by the ToF method. The main problems of UWB technology, when applied to systems with a focus on large audiences, are the complexity and cost of implementation. Unlike Wi-Fi, UWB systems are not commonly found in indoor environments, and their deployment means an additional expense. However, this problem will be overcome with the implementation of the fifth generation (5G) of cellular networks worldwide, which will employ signals with high bandwidth and centimeter-level range accuracy [51]. Time-based location methods are susceptible to errors produced by clock inaccuracies, errors in time estimation, and a lack of synchronization between clocks [24]. For example, for a signal that travels at the speed of light, 1 \(\upmu\)s of error corresponds to an approximate distance error of 300.00 m. Also, conditions with non-line of sight (NLOS) produce a positive bias in the distance estimate and should be included in methods of location and distance determination. The critical point of the approach is related to the increased complexity of the algorithms by including NLOS. In general, time-based systems receive extremely accurate position estimates and can be applied over large areas due to their scalar characteristics. This scalability, however, does not guarantee users' safety from collisions. Thus, an obstacle detection mechanism must be implemented, increasing the general complexity of the algorithm. Finally, the cost of the system is determined by the network technology and the number of nodes required. Angle: Angle-based location methods adopt a signal's angle of arrival as a criterion for calculating the position of the receiver [44]. Its operation is like time-based methods, but instead of using the distances to the anchor nodes, it checks the angles. There are usually two main methods of obtaining the AoA of a signal [52; 53]:  
* Use a matrix of sensors whose locations relative to the center of the node are known and use the difference in ToA of the signal at each sensor to calculate the AoA of the anchor node. * Two or more directional antennas are pointed in different directions with overlapping main beams. The calculation of AoA takes place according to the RSSI proportion of the individual antennas. The AoA value is estimated by calculating the triangulation of the signals received from one or more anchor nodes, as shown in Figure 3. If the position of the vertices of a triangle is known, it is possible to calculate the location of any node within the triangle, and thus know the angle at which the point sees the vertices [44; 54]. In general, AoA systems are not widely used for the indoor location due to the need for additional hardware, such as sensor arrays or antennas [44]. Also, the calculation of angular estimates has high processing consumption. It is negatively affected by the low signal-to-noise ratio (SNR) and errors in the RSSI or ToA estimates [47]. These factors limit the scalability of the system due to the increase in monetary cost and consumption of computational resources. RSSI: Location methods based on RSSI estimate the distance between the user and an anchor node using the strength of the received signal [42; 55]. These methods consider that the attenuation suffered by a signal that travels from a transmitter to a receiver depends on the distance covered [56]. Thus, to estimate the distance between two points, it is necessary to model the environment with Wi-Fi devices using a signal propagation model.