Optical Current Sensing Based on Bias-Added Measurement and Main-Component Reconstruction

Low-current measurement is a challenging task for polarimetric fiber-optic current-sensing (FOCS) systems due to low signal-to-noise ratio (SNR) and sensitivity to current (STC). To tackle the challenges, this paper proposes a FOCS approach on bias-added measurement and main-component reconstruction. To enhance STC, the adopted FOCS structure is based on bias-added measurement using a bias-current coil and a single-axis working circulator instead of traditional polarizers. However, the unavoidable noise would decrease the SNR of FOCS output. An algorithm of main-component reconstruction is presented to filter out the noise. The main-component distribution of the FOCS output is analyzed by a feature vector based on the spectral sub-zones. Using an appropriate threshold, the sub-zones with prominent features are self-adaptively decomposed to extract the main components by fast matrix decomposition. Lastly, the main components are adopted to reconstruct the FOCS signal. In comparison with other reflective methods, the experimental data suggest that the STC and SNR of the proposed approach can be increased by 200% and 22%, respectively. The similarity between the expected and reconstructed signals reaches 0.9993 under the premise of a small measurement error.