aNGLE: aNGular Location Estimation algorithms

Abstract

In this paper, we present two localization algorithms that exploit the angle of arrival (aoa) parameters of the received signal. The proposed aNGular Location Estimation (aNGLE) algorithms utilize a probabilistic model to describe the angular response of the received signal. Consequently, the aNGLE algorithms can estimate the location of a transmitter using a single step Hadamard product. The first algorithm utilizes a Single Sample of the received signal (aNGLE-SS). The second algorithm, on the other hand, employs the signal Subspace Decomposition technique (aNGLE-SD). The localization capabilities of the aNGLE algorithms have been experimentally investigated in an office environment. The performances of the aNGLE algorithms have been validated against the performances of several aoa-based localization systems. The experimental results show that the aNGLE-SD algorithm outperforms all the studied aoa-based localization systems. The aNGLE-SS algorithm, on the other hand, outperforms every localization system that utilizes less than 50 samples of the received signal. The aNGLE algorithms are flexible, generic and computationally very efficient. These features allow the aNGLE algorithms to be easily deployed in any existing aoa-based localization system.