Fang Algorithm for 2D Signal Source Localization Using Three Base Stations

The Fang algorithm utilizes three base stations to perform two-dimensional localization of signal source positions, representing a fundamental method in passive source localization. This MATLAB-based program simulates the complete localization process of the Fang algorithm. We hope this provides valuable assistance to researchers studying passive localization. To provide more detailed information, we can further elaborate on the principles and application scenarios of the Fang algorithm. The algorithm estimates signal source positions based on received signal strength and distance differences between base stations, implementing hyperbolic positioning equations through TDOA measurements. The MATLAB code includes functions for calculating time differences, solving nonlinear equations using iterative methods, and performing error analysis through covariance matrix calculations. The Fang algorithm finds widespread applications in wireless communications, indoor positioning systems, and passive sensor networks. Through simulation, we can validate the algorithm's accuracy and reliability while enabling parameter adjustment and optimization. The program incorporates configurable parameters for base station coordinates, signal propagation models, and noise characteristics, allowing researchers to test various scenarios. This simulation program serves as a valuable tool for passive localization researchers, offering modular code structure with separate functions for data preprocessing, position estimation, and result visualization. The implementation demonstrates practical approaches for handling measurement uncertainties and improving localization precision through statistical methods. We hope this expanded explanation better illustrates the significance and application scope of the Fang algorithm, along with the functionality and advantages of this simulation program for educational and research purposes.