Jan Scheuing

Cramer-Rao bound and optimum sensor array for source localization from time differences of arrival

This paper presents a theoretical analysis of the Cramer-Rao lower bound for source localization from time differences of arrival. We derive properties of the Cramer-Rao bound and design optimum sensor arrays which minimize the bound.

Disambiguation of TDOA Estimation for Multiple Sources in Reverberant Environments

This paper presents a novel approach to estimate the time difference of arrival (TDOA) for multiple sources in reverberant environments. It resolves ambiguities in TDOA estimation caused by multipath propagation and multiple sources. By exploiting two TDOA constraints, the raster condition and the zero cyclic sum condition, we are able to identify and reject the echo path TDOAs and to assign the direct path TDOAs correctly to different sources. For the latter purpose, an efficient algorithm for the synthesis of approximately consistent TDOA graphs has been developed. A real experiment demonstrates the superior performance of our algorithms.

A Theoretical Analysis of 2D Sensor Arrays for TDOA Based Localization

In source localization from time difference of arrival, the impact of the sensor array geometry to the localization accuracy is not well understood yet. A first rigorous analysis can be found in B. Yang and J. Scheuing (2005). It derived sufficient and necessary conditions for optimum array geometry in terms of minimum Cramer-Rao bound. This paper continues the above work and studies theoretically the localization accuracy of two-dimensional sensor arrays. It addresses different issues: a) optimum vs. uniform angular array b) near-field vs. far-field array c) using all sensor pairs vs. those with a common reference sensor as required from spherical position estimators. The paper ends up with some new insights into the sensor placement problem

Efficient Synthesis of Approximately Consistent Graphs for Acoustic Multi-Source Localization

Due to ambiguities and estimation errors, combining time differences of arrival (TDOAs) for simultaneous localization of multiple acoustic sources is a challenging task. This paper studies this problem under the framework of consistent graphs and proposes an efficient algorithm to determine TDOAs originating from the source.