This paper presents a novel method for 3D angle of arrival (AOA) localization using a mobile receiver with limited number of antennas. We propose three convolutional neural networks to estimate elevation and azimuth AOAs, along with their pairing from recorded signals in sequential time windows. Then, a multi-source 3D-localization algorithm is proposed to estimate source positions across recorded time windows. Simulation results validate the effectiveness and robustness of the proposed method even in scenarios where uncertainties arise regarding the receiver’s position or direction during movement.
Localization Using Convolutional Neural Networks with Mobile Array
07.10.2024
438981 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Landmark localization on objects in images using convolutional neural networks
Europäisches Patentamt | 2019
|Europäisches Patentamt | 2019
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