Abstract: This paper presents a new demodulation approach for optical fiber temperature sensors based on GaAs, leveraging reference filtering and a cross-correlation algorithm. It preprocesses the data through double Gaussian filtering for smoothing and implements an enhanced cross-correlation algorithm adopting a long-pass filter (LPF) waveform as the reference signal to demodulate the GaAs optical fiber temperature sensor. Using the correlated data from cross-correlation operations, it applies a multiple polynomial fitting strategy to further augment the precision of the cross-correlation algorithm’s demodulation. Across a temperature sensing range of −30 to 250 ℃, the wavelength demodulation error of this method can reach ±0.0016 nm, and the temperature demodulation accuracy is ±0.388 ℃. Relative to the prevailing normalized optical intensity demodulation method, the cross-correlation algorithm employing an LPF waveform as the reference demonstrates a 2.64-fold increase in noise immunity and a 2.08-fold improvement over cross-correlation algorithms without the LPF reference waveform.