Use of super resolution algorithms for indoor positioning keeping novel designed WLAN signal structure

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 Orthogonal Frequency Division Multiplexing (OFDM) transceiver. Optimal reduction in Distance Measurement Error (DME) is achieved. We have utilized OFDM/Single Carrier-Decision Feedback Equalizer (OFDM/SC-DFE) signal structure presented in our previous works. The super resolution algorithms Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Root Multiple Signal Classification (Root-MUSIC) and Matrix Pencil (MP) are compared for DME estimation. We have applied Minimum Descriptive Length (MDL) criterion to these algorithms, that provides optimized estimate of the length of actual Channel Impulse Response (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 the object to be positioned.