UDP identification for high-resolution wireless indoor positioning based on IEEE 802.11ac

This contribution is addressed to the problem of highly resolving the propagation time delays and the relative amplitudes associated with signals in multipath communication channels. The Unitary Matrix Pencil (UMP) algorithm is applied in a new way to estimate these parameters from the measured channel frequency response (CFR) using wideband orthogonal multicarrier signals. The mobile unit (MU) is often in a non-line-of-sight (NLOS) state, and the direct path could be completely blocked due to the harsh nature of indoor environments. There-fore, the estimated time delay of the first path should be identified either as a very weak detected direct path (DDP) or even as an undetected direct path (UDP). Consequently, precise estimation of the channel profile parameters is not enough for high-resolution wireless indoor positioning system. However, it stays representing a key element to identify the UDP condition. In this work, the accurate estimation of channel profile parameters and the proper modeling of DDP and UDP channel profiles will be treated and addressed to the problem of UDP identification. Experimental results using the emerging IEEE 802.11ac standard reveal that the achieved probability of correct identification can be more than 96.6% at the smallest bandwidth.