An empirical regressive model to improve the metrological performance of mobile spatial coordinate measuring systems

Abstract The mobile spatial coordinate measuring system (MScMS) is a system to perform dimensional measurements of large-scale objects. It consists of a wireless measuring probe with ultrasonic (US) transceivers, the position of which is determined using a distributed constellation of analogous transceivers arranged around the measuring area. The principle is to measure the time-of-flight (TOF) of the US signals exchanged between pairs of transceivers and, consequently, to obtain an estimate of their distances. The accuracy of TOF measurements can be attributed to many factors; the most influential are those associated with US signal attenuation. The purpose of this paper is to build an experimental correction model to reduce the MScMS’ error in TOF measurements. First, a two-way block design, which is based on exploratory experiments, is created to show that transmitter—receiver distance and relative orientation between US transceivers have significant effects on TOF measurement error. Next, an empirical regressive model is constructed on the basis of additional detailed experiments. After performing an extensive experimental validation, the model is automatically implemented by MScMS, with an iterative procedure. The most important benefit of such a model is an important reduction in the dispersion and an improved accuracy associated with TOF measurements.