Abstract

The transient stimulated Brillouin scattering (SBS) effect, enabled by optical chirp chain (OCC) technology, has already been proposed and demonstrated for microwave frequency identification with high temporal resolution. Through increasing the OCC chirp rate, the instantaneous bandwidth can be effectively extended without loss of the temporal resolution. However, the higher chirp rate results in more asymmetric transient Brillouin spectra, which worsens the demodulation accuracy when using the traditional fitting method. In this Letter, advanced algorithms, including image processing and artificial neural network, are employed to improve the measurement accuracy and demodulation efficiency. A microwave frequency measurement scheme is implemented with 4 GHz instantaneous bandwidth and 100 ns temporal resolution. Through the proposed algorithms, the demodulation accuracy of transient Brillouin spectra under 50 MHz/ns high chirp rate is improved from 9.85 MHz to 1.17 MHz. Moreover, owing to the matrix computations of the proposed algorithm, the time consumption is reduced by two orders of magnitude compared with the fitting method. The proposed method allows a high-performance OCC transient SBS-based microwave measurement, which provides new possibilities to realize real-time microwave tracking for diverse application fields.

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