The problem addressed is source localization via time-difference-of-arrival estimation in a multipath channel. Solving this localization problem typically implies cross-correlating the noisy signals received at pairs of sensors deployed within reception range of the source. Correlation-based localization is severely degraded by the presence of multipath. The proposed method exploits the sparsity of the multipath channel for estimation of the line-of-sight component. The time-delay estimation problem is formulated as an ℓ1-regularization problem, where the ℓ1-norm is used as a channel sparsity constraint. The proposed method requires knowledge of the pulse shape of the transmitted signal, but it is blind in the sense that information on the specific transmitted symbols is not required at the sensors. Simulation results show that the proposed method delivers higher accuracy and robustness to noise compared to conventional or even super-resolution MUSIC time-difference-of-arrival source localization methods.

Ultra-wideband indoor line-of-sight frequency-domain channel measurements have been performed in the 2-6 GHz frequency band using three different transmit/receive antenna combination pairs. The effects of antenna directivity on path loss and multipath propagation in the channel are analyzed extensively for various omnidirectional and directional antenna combinations. A statistical model of the path loss in the channel is presented, in which all path loss exponents result in better than free space loss. The shadow fading experienced in the channel is shown to highly agree with the normal probability assumption. There is a significant reduction in root mean square delay spread when directional antennas are used at the transmitter and receiver or solely at the receiver with respect to an omnidirectional/omnidirectional antenna pair. Finally, a distance-dependent statistical impulse response model of the channel is presented along with simulation results that significantly concur with the measured data.