Pulsed free space two-port photonic vector network analyzer with up to 2 THz bandwidth

Photonic-assisted fast broadband microwave vector network analyzer based on FMCW

In the paper, we propose a photonic-assisted fast broadband microwave vector network analyzer (FB-VNA) based on frequency modulated continuous wave (FMCW). A photonic recirculating frequency shift (RFS) loop is used to extend the bandwidth of optical FMCW. The bandwidth-extended optical FMCW beats with the continuous wave (CW) light to generate the broadband electrical FMCW, which serves as the incident signal of the device under test (DUT). The response signals of the DUT are modulated on the bandwidth-extended optical FMCW to perform de-chirping. After coherently beating the de-chirped light with the CW light, the broadband response signals of DUT are down-converted to a single-tone intermediate frequency (IF) signal carrying the frequency response of DUT, and the scattering parameters of DUT can be obtained. The single-tone IF signal relaxes the demand on the bandwidth and sampling rate of the electrical backend. Thanks to the RFS loop and the short period of FMCW, the measurement frequency range is highly extended and measurement speed is greatly accelerated at the same time, which can be applied in monitoring sudden changes of DUT features. A bandwidth multiplication of the FMCW from 6-18 GHz to 6-498 GHz is experimentally implemented. With available photodetectors (PDs) and Mach-Zehnder modulators (MZMs), a 6-54 GHz FB-VNA is demonstrated, and the S parameters of a 25-GHz low-pass filter (LPF) is measured within 6 μs. The sudden changes of S21 parameter of DUT simulated by fast adjusting the bias voltage of the MZM used for de-chirping are also characterized by the proposed FB-VNA. The sudden changes as short as 0.01 μs can be captured.

Characterisation of multi-layered structures using a vector-based gradient descent algorithm at terahertz frequencies

Material characterisation and imaging applications using terahertz radiation have gained interest in the past few years due to their enormous potential for industrial applications. The availability of fast terahertz spectrometers or multi-pixel terahertz cameras has accelerated research in this domain. In this work, we present a novel vector-based implementation of the gradient descent algorithm to fit the measured transmission and reflection coefficients of multilayered objects to a scattering parameter-based model, without requiring any analytical formulation of the error function. We thereby extract thicknesses and refractive indices of the layers within a maximum 2% error margin. Using the precise thickness estimates, we further image a 50 nm-thick Siemens star deposited on a silicon substrate using wavelengths larger than 300 µm. The vector-based algorithm heuristically finds the error minimum where the optimisation problem cannot be analytically formulated, which can be utilised also for applications outside the terahertz domain.