Computationally Attractive and Location Robust Estimator for IoT Device Positioning

Locating a device is a basic element for many Internet of Things (IoT) applications. In particular, it often demands an algorithm having low complexity to limit the energy consumption and most important, sufficient robustness without knowing the device in the near-field for point localization or in the far-field for direction of arrival (DOA) estimation. This article proposes a new localization algorithm that can achieve the two purposes, with the theoretical analysis to validate the optimal accuracy and the real data experiment to support the promising performance. The first objective is achieved by a closed-form solution and the second is accomplished by using the modified polar representation (MPR) of the source position, based on a new formulation for the localization problem. While the MPR localization method has been introduced before, it is not sufficiently robust for IoT application to handle the large equal radius (LER) scenario or the presence of sensor position errors. The proposed algorithm uses a different MPR formulation, which is able to handle the LER scenario, sensor position errors, and has low computational complexity.