Numerical Analysis of Positioning Errors in Irregular Near-Field Antenna Measurements Using Robot-Based Systems

Robotic positioning systems have a wide range of applications in antenna measurements due to their high flexibility and configurability. One application are spherical nearfield antenna measurements, where robotic systems enable the efficient implementation of irregular sampling grids to reduce the measurement time among others. However, the absolute positioning uncertainty of industrial robots is usually larger than the uncertainty for traditional antenna positioning systems, and is characterized in Cartesian space rather than the spherical domain. Therefore, a careful analysis of the measurement uncertainty due to the positioning errors is required. Here, a simulation framework is presented, which can be used to analyze the uncertainty for an antenna measurement due to Cartesian positioning errors. It is shown that the sampling grid type, oversampling ratio, and measurement radius affect the measurement error and uncertainty. Furthermore, a relation between the maximum positioning error and the error in the reconstructed far-field pattern is established.