Time Difference of Arrival estimation using super resolution algorithms to minimize Distance Measurement Error for indoor positioning systems

Abstract

This paper presents the utilization of super resolution algorithms for the indoor positioning applications in order to estimate Time difference of Arrival (TDOA) and distances using OFDM transceiver. Optimal reduction in Distance Measurement Error (DME) is achieved. We have utilized OFDM/SC-DFE signal structure presented in our previous works. Three super resolution algorithms i.e. Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Root-Multiple Signal Classification (RootMUSIC) and Matrix Pencil (MP) are being compared for DME estimation. We have applied Minimum Descriptive Length (MDL) criteria to these algorithms, that provides optimize estimate of the length of actual CIR by eliminating the noise component from the dispersive CIR. Our scheme is based on two different antennas used to transmit the pre-half-zero-carriers and post-half-zero-carriers OFDM symbols respectively, mapped to multiple carriers using Wireless Local Area Network (WLAN) system and received by a single to be positioned object. An analysis of DME estimation is presented for varying Signal to Noise Ratio (SNR). DME reduction approaching to zero is achieved by the MP algorithm using our scheme.