This paper presents a novel approach for estimating the direction of arrival (DoA) at any instant using subspace-based classical estimators. The aim is to mitigate the reliance of classical estimators on the quantity of snapshot data. The strategy involves leveraging instantaneous data from multiple channels, treating them as equivalent to multiple snapshots, to effectively address the impact of noise. The proposed approach is tested on a realistic data set generated using the embedded radiation patterns (ERPs), at multiple frequencies, of an antenna array developed for Bluetooth Low Energy (BLE) applications. The preliminary analysis affirms the capabilities of the proposed approach in handling noise. Across various levels of noisy data, the performance of the proposed approach consistently surpasses that of standard methods at any given moment.
Fast Direction of Arrival Estimation Using Subspace-Based Methods for BLE Applications
Hannan M. A.;Crisafulli O.;Pavone S. C.;Di Donato L.;Sorbello G.
2024-01-01
Abstract
This paper presents a novel approach for estimating the direction of arrival (DoA) at any instant using subspace-based classical estimators. The aim is to mitigate the reliance of classical estimators on the quantity of snapshot data. The strategy involves leveraging instantaneous data from multiple channels, treating them as equivalent to multiple snapshots, to effectively address the impact of noise. The proposed approach is tested on a realistic data set generated using the embedded radiation patterns (ERPs), at multiple frequencies, of an antenna array developed for Bluetooth Low Energy (BLE) applications. The preliminary analysis affirms the capabilities of the proposed approach in handling noise. Across various levels of noisy data, the performance of the proposed approach consistently surpasses that of standard methods at any given moment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
