GLOBECOM 2015, IEEE Global Communications Conference, "Localization and Tracking: Indoors, Outdoors and Emerging Networks (LION)" workshop, December 6-10, 2015, San Diego, CA, USA
This paper presents and analyses two computationally attractive Maximum Likelihood (ML) estimators for joint Angle of Arrival (AoA) and Time of Arrival (ToA) using a Single Input Multiple Output (SIMO) link in an OFDM communication setting. We consider a rich multipath channel, which is the case of an indoor environment, where the received signal is a sum of scaled and delayed versions of the original transmit OFDM symbol. The first algorithm is a modification of the two dimensional
Iterative Quadratic ML (2D-IQML) algorithm, where an additional constraint is added for joint ToA and AoA estimation. We show that 2D-IQML gives biased estimates of ToAs/AoAs and performs poorly at low SNR due to noise induced bias. The 2DIQML
cost function can be "denoised" by eliminating the noise contribution: the resulting algorithm, two dimensional Denoised IQML (2D-DIQML), gives consistent estimates and outperforms 2D-IQML. Furthermore, 2D-DIQML is asymptotically globally
convergent and hence insensitive to the initialisation. Also, we show that the 2D-DIQML algorithm behaves asymptotically at any SNR as the 2D-IQML algorithm behaves at high SNR. A simulation example has been presented to show the asymptotic behaviour of both algorithms at low SNR. Finally, joint AoA/ToA estimates could bring very useful information for localisation purposes, especially in a rich multipath channel, that could allow single anchor-based localisation.
Systèmes de Communication
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