The transmission of optical signals in atmospheric turbulent channels causes signal fading and light intensity flicker, and the baseband signal cannot be recovered correctly by fixed threshold detection at the receiving end, so adaptive adjustment of the received signal decision threshold is required. Adaptive threshold detection technology can effectively suppress the atmospheric turbulence effect, which is an important means to improve the bit error rate performance of optical wireless communication systems and enhance system reliability. Its detection performance is mainly optimized and improved for the threshold detection algorithm and feedback mechanism. Reviewing the development process of adaptive threshold detection technology, starting from the structure of optical wireless communication system, deriving the optimal decision threshold model for the received signal based on Bayesian maximum likelihood estimation and maximum posterior probability criteria, and the realization of baseband signal demodulation by comparing the received signal with the optimal decision threshold. The typical adaptive threshold detection models based on the minimum mean square error filter, Kalman filter and fading Kalman filter are analyzed, which are suitable for stationary input signals and non-stationary input signals respectively. At the same time, the related research work of Xi′ an University of Technology using high-order cumulants instead of traditional second-order statistics in the field of adaptive threshold detection is introduced. Finally, the future development trend of this field is summarized and foreseen, which can provide some reference for the future research and development of adaptive threshold detection technology for optical wireless communication.