A novel localization algorithm for Internet of Things in 3D

With the increasing demand of smart objects in our everyday life promotes an advance generation of communications under the umbrella of the Internet of Things (IoT). For IoT, location-based service is one of the main service, while localization accuracy is a primary problem. Rather than linearizing the nonlinear cost function, we propose a novel subspace algorithm by using the time of arrival (TOA) measurements. Our propose algorithm provide closed-form solution and is validated to be robust even for large measurement noise, as the dimension awareness and eigenstructure of scalar product matrix is used. We evaluate the proposed algorithm by comparing with Cramér-Rao Lower Bound (CRLB) and show its performance through simulation experiments using MATLAB.