TUTCRIS

TY - JOUR

T1 - DoA Estimation Using Compact CRLH Leaky-Wave Antennas

T2 - Novel Algorithms and Measured Performance

AU - Paaso, Henna

AU - Gulati, Nikhil

AU - Patron, Damiano

AU - Hakkarainen, Aki

AU - Werner, Janis

AU - Dandekar, Kapil R.

AU - Valkama, Mikko

AU - Mammela, Aarne

PY - 2017

Y1 - 2017

N2 - Traditional direction-of-arrival (DoA) estimation algorithms for multi-element antenna arrays are not directly applicable to reconfigurable antennas due to inherent design and operating differences between antenna arrays and reconfigurable antennas. In this paper, we propose novel modifications to existing DoA algorithms and show how these can be adapted for realtime DoA estimation using two-port composite right/left-handed (CRLH) reconfigurable leaky-wave antennas (LWAs). First, we propose a single/two-port multiple signal classification (MUSIC) algorithm and derive the corresponding steering vector for reconfigurable LWAs. We also present the power pattern cross correlation (PPCC) algorithm which is based on finding the maximum correlation between the measured radiation patterns and the received powers. For all algorithms, we show how to simultaneously use both ports of the two-port LWA in order to improve the DoA estimation accuracy and, at the same time, reduce the scanning time for the arriving signals. Moreover, we formulate the Cramer-Rao bound (CRB) for MUSIC-based DoA estimation with LWAs and present an extensive performance evaluation of MUSIC algorithm based on numerical simulations. Additionally, these results are compared to DoA estimation with conventional antenna arrays. Finally, we experimentally evaluate the performance of the proposed algorithms in an indoor multipath wireless environment with both line-of-sight (LoS) and non-line-of-sight (NLoS) components. Our results demonstrate that DoA estimation of the received signal can be successfully performed by using the two-port CRLH-LWA, even in the presence of severe multipath.

AB - Traditional direction-of-arrival (DoA) estimation algorithms for multi-element antenna arrays are not directly applicable to reconfigurable antennas due to inherent design and operating differences between antenna arrays and reconfigurable antennas. In this paper, we propose novel modifications to existing DoA algorithms and show how these can be adapted for realtime DoA estimation using two-port composite right/left-handed (CRLH) reconfigurable leaky-wave antennas (LWAs). First, we propose a single/two-port multiple signal classification (MUSIC) algorithm and derive the corresponding steering vector for reconfigurable LWAs. We also present the power pattern cross correlation (PPCC) algorithm which is based on finding the maximum correlation between the measured radiation patterns and the received powers. For all algorithms, we show how to simultaneously use both ports of the two-port LWA in order to improve the DoA estimation accuracy and, at the same time, reduce the scanning time for the arriving signals. Moreover, we formulate the Cramer-Rao bound (CRB) for MUSIC-based DoA estimation with LWAs and present an extensive performance evaluation of MUSIC algorithm based on numerical simulations. Additionally, these results are compared to DoA estimation with conventional antenna arrays. Finally, we experimentally evaluate the performance of the proposed algorithms in an indoor multipath wireless environment with both line-of-sight (LoS) and non-line-of-sight (NLoS) components. Our results demonstrate that DoA estimation of the received signal can be successfully performed by using the two-port CRLH-LWA, even in the presence of severe multipath.

KW - Antenna arrays

KW - Antenna measurements

KW - Cramer-Rao bound

KW - Direction-of-arrival estimation

KW - directional antennas

KW - Directive antennas

KW - Estimation

KW - Multiple signal classification

U2 - 10.1109/TAP.2017.2724584

DO - 10.1109/TAP.2017.2724584

M3 - Article

SP - 4836

EP - 4849

JO - IEEE Transactions on Antennas and Propagation

JF - IEEE Transactions on Antennas and Propagation

SN - 0018-926X

ER -