Análise de desempenho de métodos de trilateração baseados em RSSI utilizando tecnologia LoRa

Abstract

Advances in wireless technology improved its accessibility by most electronics, today it is relatively easy to find top shelf microcontrollers that use one or more wireless technologies, and those are often used in a wide range of applications. It is in this context that the Internet of Things (IoT) is present and is expanding exponentially, so, one not-so-obvious way to take advantage of this infrastructure, is to utilize the communication itself for the system localization, applying wave propagation models and trilateration methods. Thus, by searching for models and methods that can generate good accuracy and precision, this project brings a methodology to compare 4 different position estimation algorithms, based on the Received Signal Strength Indicator (RSSI) that are commonly used in the literature: Wheighted Centroid Localization (WCL), Modified Centroid Localization Algorithm (MCLA), MinMax algorithm and Minimum Mean Squared Error (MMSE). A fifth algorithm was developed based on the MMSE, considering the two metrics, accuracy and precision, and it was also compared to the other 4 methods. The implementation was done using a new technology that integrates well with Internet of Things, called Long Range (LoRa), so the wave propagation equation was modeled using empiric data of this communication RSSI. After the model step, the 5 trilateration algorithms were simulated through a series of different scenarios, varying the known anchor-node quantity in each step. Finally, all the methods were tested empirically using low cost LoRa hardware in a experimental campaign at an open field with no obstacles. The real results are compared with the simulation and the performance of each algorithm is analyzed.