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Multi Direction-of-Arrival Tracking Using Rigid and Flexible Antenna Arrays

Zhuqing Tang, A. Manikas

2021IEEE Transactions on Wireless Communications15 citationsDOIOpen Access PDF

Abstract

This paper is concerned with the problem of simultaneously tracking the direction-of-arrival (DOA) of far-field multiple moving sources/users in wireless communications using the vector-signal received by an antenna array of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> elements. The antenna array can be rigid (fixed array locations) or flexible (time-varying array locations), and it is used in conjunction with a “manifold extender”, a spatiotemporal state-space model and a Kalman-type tracking approach for non-stationary wireless channels. In particular, two tracking approaches are proposed. The first is based on an arrayed Extended Kalman Filter (arrayed-EKF) algorithm and the second on an arrayed Unscented Kalman Filter (arrayed-UKF) algorithm. Furthermore, if the array is rigid the spatiotemporal state-space model incorporates the DOAs and the angular velocities of the sources, while if it is flexible it also includes the array locations in the set of state-variables. The performance of the two approaches using both rigid and flexible arrays is evaluated using computer simulation studies and compared with a subspace tracking algorithm and a particle filter method under the same conditions. The results show that the arrayed-UKF and the arrayed-EKF show superior tracking performance, especially for low SNRs.

Topics & Concepts

Extended Kalman filterKalman filterSensor arrayComputer scienceAntenna arrayTracking (education)AlgorithmAntenna (radio)Direction of arrivalTopology (electrical circuits)Control theory (sociology)MathematicsArtificial intelligenceTelecommunicationsCombinatoricsControl (management)Machine learningPsychologyPedagogyDirection-of-Arrival Estimation TechniquesTarget Tracking and Data Fusion in Sensor NetworksIndoor and Outdoor Localization Technologies
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