Time-of-flight estimation based on covariance models

Abstract

We address the problem of estimating the time-of-flight (ToF) of a waveform thatis disturbed heavily by additional reflections from nearby objects. Theseadditional reflections cause interference patterns that are difficult to predict. Theintroduction of a model for the reflection in terms of a non-stationaryauto-covariance function leads to a new estimator for the ToF of an acoustic toneburst. This estimator is a generalization of the well known matched filter. In manypractical circumstances, for instance beacon-based position estimation in indoorsituations, lack of knowledge of the additional reflections can lead to largeestimation errors. Experiments show that the application of the new estimator canreduce these errors by a factor of about four. The cost of this improvementis an increase in computational complexity by a factor of about seven.