Impact of Excitation and Weighting Errors on Performance of Compact OTA Testing Systems

TL;DR

This study examines how excitation and weighting errors affect the accuracy of compact over-the-air testing systems, emphasizing the importance of considering these errors in setup design and algorithm performance evaluation.

Contribution

It introduces a method to evaluate the impact of complex excitation errors on compact OTA test setups and compares the robustness of matched filter and zero-forcing algorithms under these errors.

Findings

Excitation errors significantly affect test accuracy in compact setups.

Zero-forcing algorithm is more sensitive to errors than matched filter.

Proper error consideration is crucial for reliable OTA testing.

Abstract

This paper investigates the impact of complex excitation errors of the chamber array antenna on the accuracy of the test zone of a random line-of-sight over-the-air testing setup. First, several combinations of compact chamber arrays of lengths L and short distances D between the test zone and the chamber array, which emulate a plane wave impinging at the test zone are obtained. The chamber array is linear and uniform with 100 antenna elements, and a linear taper was applied to some of the elements to emulate a plane wave impinging at the test zone with more compact setups. A subset of L and D was chosen, providing compact over-the-air test setups that fulfilled the defined figures of merit, which assess the similarity of the obtained field distribution to that of a plane wave. The tolerance of the chosen setups to complex excitation errors of the chamber array was then investigated, concluding that these errors must be considered when defining appropriate L and D combinations. Moreover, the performance of the matched filter and zero-forcing algorithms is evaluated for errors of the device under test array weighting coefficients. A random line-of-sight over-the-air testing setup with two arrays was simulated, where one of the arrays emulated the desired signal and the other emulated the interference, observing that the errors were more significant at higher signal-to-noise ratios. Additionally, the zero-forcing algorithm was more sensitive to errors than the matched filter, which was expected since the accuracy of the former for interference suppression is critical.