Source localization using TDOA and FDOA measurements based on modified cuckoo search algorithm

This paper introduces a new algorithm for solving the localization problem of moving multiple disjoint sources using time difference of arrival and frequency difference of arrival. The localization of moving sources can be considered as a least-square problem. There are many algorithms used to solve this problem such as, two-step weighted least squares, constrained total least-square and practical constrained least-square. However, most of these algorithms suffer from either slow convergence or numerical instability and don't attain Cramer-Rao lower bound. We introduce a free-gradient algorithm called cuckoo search which avoids the slow convergence problem. The cuckoo search provides a combined global and local search method. Simulation results show that the proposed algorithm achieves better performance than other algorithms and attains Cramer-Rao lower bound.