Abstract: Atmospheric turbulence is the key process of regulating the exchange of atmospheric materials and energy. As one of the core parameters of atmospheric turbulence, the turbulent energy dissipation rate (ε), its accurate inversion is very important for the fields of weather forecast, remote sensing communication, aviation safety, wind energy development and so on. Through the traceability of the K41 theory—the theoretical basis of meteorological radar inversion ε, the development of the main retrieval technologies such as the structure function method, the power spectrum method and the spectral width method in the past few decades is combed in detail, including the application conditions, advantages and disadvantages, application scenarios and technical improvements of the methods. The application characteristics, detection cases and comparison verification of the retrieval of ε by wind profiler radar, weather radar, cloud radar and lidar are analyzed and summarized.this study identifies that future technological development will focus on multi-band radar collaborative observation and multi-source data fusion driven by deep learning, This work aims to provide theoretical and technical references for the optimization and innovation of ε retrieval method.