# A Review of Pedestrian Indoor Positioning Systems for Mass Market Applications
## 2 Network Based Systems
### Range Free
#### 2.2.2 Fingerprinting  
Fingerprinting methods are based on the uniqueness of radio signals received at different positions, which is due to the propagation issues in the complex indoor environment. Usually, in indoor environments different kinds of radio signals can be received, such as the ones received from WiFi, WSN or Bluetooth networks deployed in the buildings among other signals as for example GSM or LTE signals. The complexity of the indoor environment produces big differences between the signals received at different locations due to multipath, shadowing or the propagation in NLOS environments. Figure 6 shows the distribution of the RSS in an indoor environment with three deployed anchor nodes under ideal propagation conditions. The color changes from blue to red as a function of the aggregated received power of the three anchors. The received power generates different subareas that can be easily identified. Note that this effect can be magnified by including the multipath and NLOS to the propagation model considered. Figure 6: Simulated distribution of RSS in an indoor scenario. The main idea behind the fingerprinting method is to generate a database of the characteristics of the signals at different positions (fingerprints) and then compare the signals received by the user with the database and estimate the position of the user as the position of the fingerprint that best matches the received signals. There are two kind of fingerprinting methods: (i) deterministic and (ii) probabilistic. One of the first deterministic fingerprinting system was the RADAR system developed by Microsoft [30]. The system collects the RSS and SNR as fingerprints from a WiFi network and reports an accuracy of 3 m. The position is estimated as the position of the fingerprint that minimizes the Euclidian distance between the online measurements and the fingerprints. The search methodology employed is the k Nearest Neighbours (kNN) approach. Similarly, in [31] authors present a fingerprinting method based on the weighted extension of the kNN algorithm. The advantage of the kNN approaches is the reduced computational complexity of these algorithms. There are other systems that increase the accuracy of the position estimation at the expense of a higher computational cost, such as systems based on Support Vector Machines (SVM) [76] or linear discriminant analysis [32]. In the group of the probabilistic approaches the aim is to find the location with maximum likelihood. The Horus system [35] uses a probabilistic model of the signal distribution in the environment and computes the position with maximum posterior probability. There are other systems based on Bayesian networks [36] or on the Kullback-Leibler divergence [37]. The collection of fingerprints is not reduced to the measurement of the characteristics of radio signals, recent works proved that it is possible to use the magnetic field [77]. A study of the feasibility of magnetic fingerprints is performed in [78]. The main advantage of magnetic field fingerprinting methods over RSS fingerprinting methods is that the magnetic field is more stable with time. However, the discernibility of the magnetic field is lower, the same value of the magnetic field can be found in many different parts of the building. Typically, the fingerprinting methods based on the magnetic field compare sequence of fingerprints instead of point to point comparisons. Then, the Dynamic Time Warping (DTW) algorithm is used to identify the correspondence between the online sequence of magnetic fingerprints and the stored database [33]. Similarly, in [34] authors propose the use of the Smith-Waterman algorithm for the alignment of the sequences. Alternatively, the signals transmitted by communications systems like GSM, LTE or Digital Audio Broadcast (DAB) also known as Signals of Opportunity (SOP) can be employed as fingerprints for a positioning system. A comparison of different opportunistic signals for localization can be found in [79].