An Interior Point Source Localization Algorithm in Multi-agent Systems

This paper considers the constrained least squares (CLS) approach for source localization problem based on range-difference (RD) measurements collected from a multi-agent system. We provide an interior point algorithm for efficiently computing the CLS estimate of the source position by analyzing the special structure of the corresponding optimization problem. Numerical simulations suggest that the proposed algorithm is much more efficient than the Lagrange multiplier algorithm as well as the Matlab toolbox CVX.