Two Localization Algorithms

This documentation presents a MATLAB program containing two different localization algorithms: the least squares method and the weighted least squares method. These algorithms are applicable for locating various targets such as drones, robots, or mobile devices. The standard least squares method, widely used in engineering and scientific fields, enhances localization accuracy by minimizing the sum of squared errors through matrix operations typically implemented using MATLAB's backslash operator (\) or pinv() function for pseudo-inverse calculations. In contrast, the weighted least squares method incorporates weight matrices to better handle measurement noise and outliers, achieved through diagonal weighting matrices that assign higher confidence to more reliable measurements. This approach delivers more robust results by solving weighted normal equations. The program structure includes modular functions for data preprocessing, algorithm implementation, and result visualization, making it suitable for both beginners and experienced MATLAB users to understand algorithmic principles. It provides a foundational framework that allows users to modify weighting strategies, optimize matrix computations, or integrate additional sensor data for specific application requirements.