Wireless Network Localization via Alternating Projections with TDOA and FDOA Measurements.

Localization is particularly important in wireless networks. With the rapid development of the Internet of Things and mobile Internet, mobility is becoming an increasingly growing topic. In this paper, we consider wireless network localization with the time difference of arrival (TDOA) and the frequency difference of arrival (FDOA) measurements which represent the mobility. To solve the maximum likelihood problem with the constraints that are imposed due to both TDOA and FDOA measurements, we adopt the alternating projection onto convex sets for source localization in sensor networks. Leveraging the convex approximation, we propose a convex boundary projection algorithm to estimate the source location. Numerical simulations show that our method is more efficient in distributed manner and the result is close to the Cramer-Rao lower bound performance under noisy measurements. [ABSTRACT FROM AUTHOR]