RSSI Simulation-Based Localization Algorithm

The RSSI (Received Signal Strength Indication) simulation-based localization algorithm is a wireless positioning technique that leverages signal strength measurements. This algorithm estimates the distance between a target device and reference points using received signal strength values (RSSI), subsequently determining the target's position through geometric computations.

In wireless communication environments, signal strength typically attenuates as propagation distance increases. The RSSI algorithm measures signal strength from multiple reference points with known positions (such as Wi-Fi access points or Bluetooth beacons), combining these measurements with signal propagation models (e.g., the log-distance path loss model) to calculate the approximate location of the target device. Common computational methods include trilateration or least squares approximation, where trilateration uses geometric circles from multiple reference points while least squares minimizes error in overdetermined systems.

RSSI simulation-based localization is frequently applied in indoor positioning systems and IoT device tracking scenarios. Due to susceptibility to environmental interference (such as multipath effects and obstacle occlusion), practical implementations often incorporate filtering algorithms (like Kalman filters) or machine learning methods to enhance positioning accuracy. Code implementations typically involve signal preprocessing, path loss parameter calibration, and iterative position refinement algorithms.