Terahertz enhancements through Kalman filtering

Terahertz (THz) technologies utilise wavelengths ranging from 30 to 3000 μm; a non-ionising segment of the electromagnetic spectrum. Efforts are ongoing to leverage THz technologies for commercial sensing and defence applications. However, the signal strength of free-space THz waves is reduced from atmospheric water vapour—a significant challenge to overcome. A typical mitigation strategy is to displace the water vapour with nitrogen in a controlled setting. This mitigation strategy is not feasible for many imaging and remote sensing applications. To address this, signal processing techniques for the enhancement of free-space THz signals via a nonlinear filtering method, such as the extended Kalman filter (EKF), have been initially explored by Spotts et al. We present an extension of these initial works by modelling the atmospheric water vapour for a 2 state EKF filtering algorithm towards the enhancement of THz signals. Pulsed THz waves are heavily influenced by the presence of water vapour manifesting as perturbations in the time-domain signal, corresponding to attenuated spectral content in the frequency-domain. We validate a vapour model through application of a 2 state EKF non-linear estimator on a dry nitrogen THz signal. The treated time-domain THz signal shows high levels of agreement with a control measurement, being a water vapour THz signal. The EKF vapour model is further validated in the frequency-domain, with the spectral content of the water vapour vibrational modes matching that of the control water vapour THz signal and the HITRAN database. The treated THz signal corresponds to a 95% reduction in error between vapour THz signal (control) and the dry THz signal. It is envisioned that these initial findings can be leveraged in future works to enhance the application of THz technologies towards commercial sensing and defence, by reducing the effects of water vapour interference on THz signals via the EKF.