## 2 State of the Art--Underground Mining Localization Systems  
In the work presented by the United States government through the Institution of Occupational Safety and Health, a revision of the technologies used for tracking devices in underground mines indicates that technologies such as RFID, Wi-Fi, and Zigbee are preferred to meet this purpose [5]. Therefore, it can be seen that the technologies selected for tracking devices in underground mining environments are characterized by being short range radio frequency (RF) systems. Indoor applications which require the tracking of devices, normally use RFID based positioning technologies for locating objects or people. It has become an interesting research and development topic since the 1990's [7; 8; 9; 10]. RFID based localization technologies can track the movements of objects through a network of radio enabled scanning devices over a distance of several meters. In [13], a method is presented for the location of a vehicle equipped with an RFID reader in an underground environment. A particle filter and passive RFID tags are used in the creation of node maps to solve the localization problem. The reported location estimation error is between 0.30 m and 5 m. The study presented in [14] investigates the use of RFID labels randomly distributed for autonomous localization and navigation in underground environments. The reported location estimation error is between 35 cm and 98 cm. In [15], a hybrid algorithm based on RFID for simultaneous location and mapping (SLAM) is proposed. The algorithm allows autonomous navigation in environments denied by GPS. A particle filter along with a sensor model that characterizes the strength of the received signal (RSS) is used to create sub-maps. The average location estimation error is 30 cm. In [16], the locations of the mobile nodes are captured by the underground nodes using Wi-Fi networks. The result of the simulation shows the method reach location accuracy up to 1.6 m. The work presented in [17] studies the scheme known as Owl Positioning Systems (OwlPS) for underground mining tunnels. OwlPS is usable as a personal positioning system to track mine workers in the event of an incident. But the system has problems in terms of the propagation of the radio signal, similar to Wi-Fi networks. In [18] a positioning system is proposed based on Zigbee technology. The global positioning system is composed by the control center, monitoring base stations, gateways, reference nodes, and mobile nodes. The software and hardware design is detailed in the manuscript, but results of the proposed system are not indicated. In the work presented in [19], an underground location system based on Zigbee technology and Web geographic information systems (WebGIS) is proposed. The miners are equipped with sensors that communicate via Zigbee. The devices determine the location of the miners in real time by implementing an algorithm based on the received signal strength indicator (RSSI). The information is sent through Zigbee and Ethernet, technologies that act as main channels of data transmission. A server provides the service that shows the distribution of the miners in the e-map through the web. In [20], it is described and implemented as a new type of security surveillance system in the coal mines, which is a network system based on Zigbee technology. The wireless sensor network consists of fixed nodes, mobile nodes, and a gateway in the underground tunnels. A monitoring software is deployed on the surface. The average location estimation error is quantified as approximately 2.5 m.  
In [21], an underground personal positioning system is proposed. The system is composed of an underground personal positioning station based on Zigbee, which includes a wireless RF receiver, communications, and electronic device for data processing. The system uses the maximum probability estimation algorithm to determine the precise location of the device. Whereas in [22], a new location system for miners is presented. It is a wireless sensor network based on Zigbee.