MATLAB Implementation of Indoor Positioning Algorithm

This indoor positioning algorithm is implemented as a MATLAB program that utilizes RSSI (Received Signal Strength Indicator) measurements for location estimation. The core implementation involves processing RSSI values through polynomial interpolation methods to model signal strength patterns and weighted averaging techniques to combine multiple sensor readings. The algorithm incorporates error correction mechanisms to mitigate environmental interference and supports real-time position updates through dynamic data processing loops. Key MATLAB functions likely include polyfit for curve fitting, mean with weighted parameters for sensor fusion, and optimization tools for error minimization. This implementation demonstrates practical applications in indoor positioning systems while being adaptable for outdoor positioning scenarios and wireless sensor network data processing, showcasing MATLAB's computational capabilities for signal processing and localization algorithms.