## 1 Introduction  
The fatality rate of firefighters is still at a high and unacceptable level. For the last 10 years, despite improvement in procedures, equipment and protective gear, there are still, on average, 60 firefighter deaths annually in the United States of America [1]. Due to this fact and the high respect that societies hold for the firefighter occupation, the social pressure has increased to find solutions that increase firefighter safety. The social willingness to protect firefighters is manifested in a form of various funding focused on seeking a solution to the problem in question through new technologies. One such societal initiative is [PERSON]\). [PERSON] Memorial Research Grant ([[http://foundation.sfpe.org/chief-donald-j-burns-memorial-research-grant](http://foundation.sfpe.org/chief-donald-j-burns-memorial-research-grant)]([http://foundation.sfpe.org/chief-donald-j-burns-memorial-research-grant](http://foundation.sfpe.org/chief-donald-j-burns-memorial-research-grant))). Our contribution to the field, as a recipient of this grant, is based on the analysis of contributing factors which lead to the unsafe events. The Firefighter Near-Miss ([[http://www.firefightreemearmiss.com/](http://www.firefightreemearmiss.com/)]([http://www.firefightreemearmiss.com/](http://www.firefightreemearmiss.com/))) is an organization which aims to prevent injuries and save the lives of firefighters by collecting, sharing and analyzing unintentionally unsafe events. According to the annual reports provided by this organization, 28.5% of casualties were caused by communication problems or by bad situational awareness [2]. Situational awareness, as described above, corresponds to the amount of attention and understanding of the actual state of the environment. Conditions affecting situational awareness can be broken down into three groups: a lack of information, a lack of knowledge and a lack of cognition. Therefore, the reasons underlying incorrect assessment of the situation correspond to more general problems related to acquisition and processing of relevant information. The position of firefighters in danger zones is reported as the most relevant information for the proper assessment of the situation [2]. Our goal, defined within this grant, was to design an indoor navigation system for firefighters that may fill the information gap related to firefighter positioning. We decided to address this problem by developing an Inertial Dead Reckoning approach. Inertial Dead Reckoning is a process of calculating the current position of a individual, using the previous position estimates and based purely on the readings of inertial sensors [3]. Modern solutions for individual navigation exploit mostly foot-mounted Micro Electro Mechanical Sensors (MEMS), that are able to gather acceleration and angular rates with high sampling rates and high precision. The basic theory of their operation relies on double integration of recorded acceleration force rotated in a navigational frame of reference, estimated using gyroscope integration. Most of the time, the navigation algorithm is expressed by means of the Kalman Filter with an additional Zero-Velocity update technique [4], that uses a simplified model of walk to reduce computational errors. This technique is proven to be effective in many reports [5; 6; 7; 8; 9; 10]. Nevertheless, due to sensor drift, measurement errors and floating point precision, the error in such an Inertial Navigation System (INS) accumulates over time [11] and therefore additional corrections are required. One of the possible approaches to correct INS positioning is the use of an infrastructure-based positioning system (GPS is a good example) or short range radio infrastructure such as WiFi or Bluetooth Low Energy (BLE) [12; 13]. Radio-based solutions use a number of techniques from Received Signal Strength Indicator (RSSI) mapping, Time-of-Flight (ToF) solutions combined with triangulation or machine learning approaches.