Smoother Integral Sliding Mode Filter for RSSI-Based Localization

Abstract

This study advances our previous research on radio frequency (RF) source localization using unmanned aerial vehicles (UAVs) through a novel geometrical Received Signal Strength Indicator (RSSI) approach. Our methodology utilizes four UAVs, split into two groups, which adjust their positions until the power received by each UAV matches that of its counterpart, allowing the calculation of intersecting lines that pinpoint the source location. Recognizing the challenges posed by environmental noise which can alter signal values leading to inaccurate estimations, we introduce a smoother integral sliding mode filter. This enhanced filter incorporates the integral of the error into the sliding mode control framework to address the high-frequency chattering typically associated with sliding mode filters in noisy environments. This adaptation not only reduces the chattering effect but also stabilizes the UAV’s response to fluctuating signal strengths, resulting in more accurate and reliable localization. Simulation results demonstrate a marked improvement in localization accuracy and robustness against noise.

Keywords

• Localization
• received signal strength indicator
• sliding mode filter
• unmanned aerial vehicles