Taylor Series Expansion Algorithm - A Recursive Localization Method Requiring Initial Position Estimation

Source localization using the Taylor Series Expansion algorithm is a recursive method that requires an initial position estimate. During each iteration, the algorithm improves the estimated position by solving the local least squares of TDOA (Time Difference of Arrival) measurement errors. The MATLAB implementation typically involves calculating TDOA measurements from received signals, constructing the Jacobian matrix for linearization, and solving the weighted least squares problem at each iteration step. While initial position selection is critical for convergence, this algorithm can be combined with simpler localization methods like Centroid or LLS (Linear Least Squares) to provide more accurate source positioning. Alternative source localization algorithms beyond Taylor Series Expansion include Chan's algorithm, spherical interpolation, and maximum likelihood estimation. This information aims to assist researchers working on signal source localization problems, particularly those implementing iterative algorithms with error minimization techniques.