Time-of-Flight Estimation Using Synchronized Chaotic Systems

Abstract

Time-of-Flight (ToF) estimation is a basic building block in many metrological applications. Performance criteria for these applications are the variance and the bias of the derived delay estimate. From a signal processing point of view chaotic signals exhibit properties which make them well suited for metrological applications. In this chapter we experimentally investigate the applicability of synchronized chaotic systems in a ToF measurement system. In particular, we show that the choice of the numerical solver has a significant impact on the estimation performance. We further present a new delay estimator based on Poincaré intersections and compare the resultant estimation performance with the performance of a standard correlation-based delay estimator.