A Study of Wireless Indoor Positioning Based on Joint TDOA and DOA Estimation Using 2-D Matrix Pencil Algorithms and IEEE 802.11ac

This contribution addresses the problem of highly resolving the propagation time delays and the relative direction of arrivals (DOAs) associated with signals in multipath communication channels for wireless indoor positioning. The recent subspace based algorithms, represented by two-dimensional matrix pencil (2-D MP) algorithms, are applied in a new way to estimate these parameters simultaneously from the measured space channel frequency response (S-CFR) using multiple antennas and wideband orthogonal multicarrier signals. The performance of using spatial multiplexing and orthogonal frequency-division multiplexing (OFDM) systems for wireless positioning are presented. A non-iterative hybrid least square estimator has been presented to estimate the mobile unit (MU) coordinates based on the time difference of arrival (TDOA) and DOA estimates. The proposed estimator solves the problem of the initial guess and that of partitioning. It is a robust estimator against channel fading and low signal-to-noise ratio (SNR). Experimental results using the emerging IEEE 802.11ac standard show that accuracy in the range of 1.5 cm can be achieved for 2-D wireless indoor positioning.

I. Introduction

WIRELESS Indoor Positioning can be defined as the estimation of the mobile unit (MU) coordinates in a reference map. This can be obtained by periodically transmitting properly designed signals from the MU and receiving them at a number of fixed base stations (BSs) with known coordinates. The MU coordinates are then estimated by processing the received signals. The opportune signals of IEEE 802.11 standards can be used for an effective wireless indoor positioning. To support wider channel bandwidths, 802.11ac defines its channelization for 20, 40, 80, and 160 MHz channels [1]. It provides as a maximum 8 8 multiple-input multiple-output (MIMO) antenna configuration. While the main advantage of MIMO is to enhance data throughput, it can also be used to estimate the direction of arrival (DOA) . In addition, it is used as a kind of spatial diversity for time difference of arrival (TDOA) estimation besides the frequency diversity coming from the orthogonal frequency-division multiplexing (OFDM) . Therefore, a framework for wireless indoor positioning using recent wireless networks needs to be developed and investigated. The developed algorithms should use a very efficient computational methodology for real time implementation on a DSP chip.