SINGLE-SAMPLE DIRECTION-OF-ARRIVAL ESTIMATION FOR FAST AND ROBUST 3D LOCALIZATION WITH REAL MEASUREMENTS FROM A MASSIVE MIMO SYSTEM
Stephan Mazokha (Florida Atlantic University); Sanaz Naderi (Florida Atlantic University); Georgios Orfanidis (Florida Atlantic University); George Sklivanitis (Florida Atlantic University); Dimitris Pados (Florida Atlantic University); Jason Hallstrom (Florida Atlantic University)
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Fast, robust, high-accuracy localization is a key enabler for future location-aware applications in streetscape communication networks and next-generation networked autonomous agents. Specifically, massive multiple-input and multiple-output (MIMO) antenna systems have received increasing attention due to high angular resolution. However, in dense multipath environments, such as urban areas, pure direction-of-arrival (DoA)-based techniques have not been very popular due to large localization errors. In this paper, we present and evaluate, on real measurements from the POWDER-RENEW platform, a novel method to carry out DoA estimation from just one antenna array snapshot. The measurements are taken from an indoor testbed that is based on a massive MIMO orthogonal frequency-division multiplexing (OFDM) system. Experimental results -- in the presence of spatial aliasing -- show that for certain emitter locations our proposed universal one-shot DoA estimator outperforms in azimuth/elevation accuracy state-of-the-art subspace-based methods that involve collection of a sufficiently large data record of antenna array snapshots.