Simulation of the Classic Chan Algorithm for TDOA Localization

In this article, we will discuss the simulation of the classic Chan algorithm for TDOA localization. First, we will provide a brief introduction to the concept of TDOA positioning, including its advantages and practical applications. Next, we will delve into the principles of the Chan algorithm and its specific implementation in TDOA localization. We will detail each step of the Chan algorithm, explaining how it calculates time differences using hyperbolic positioning principles and matrix operations for solving nonlinear equations. We will then demonstrate how to implement the Chan algorithm simulation using MATLAB. This includes setting up the simulation environment by defining anchor positions, signal parameters, and noise models; generating received signals through cross-correlation techniques for time difference extraction; and running the simulation with proper error handling and visualization components. The implementation will showcase key MATLAB functions such as corr for signal processing and matrix operations for solving the weighted least squares problem at the core of the Chan algorithm. Finally, we will analyze the simulation results and discuss the algorithm's performance in terms of positioning accuracy, computational efficiency, and robustness under various noise conditions. Through this article, readers will gain a comprehensive understanding of TDOA localization and the Chan algorithm, along with practical skills for conducting simulation analysis using MATLAB.