In response to the significant dependency on empirical judgment in measuring the prompt neutron decay constant with the traditional Rossi-alpha method and the issue of requiring an excessive number of detectors with the DMD-Rossi-alpha method, this paper introduces a calculation method for the prompt neutron decay constant based on a combination of Latin Hypercube Sampling (LHS), Dynamic Mode Decomposition (DMD), and the Rossi-alpha method. Initially, the method uses LHS to expand the sample dataset of neutron noise data to reduce the number of detectors required. It then employs the Rossi-alpha method to construct a Rossi-alpha distribution model from neutron noise data. Finally, it utilizes DMD for feature extraction from the Rossi-alpha distribution model, thereby determining the prompt neutron decay constant. Research findings demonstrate that, by simulating the KUCA facility using RMC3.5 in a near-critical state, the relative error of the α value calculated by the LHS-DMD-Rossi-alpha method model is 9% less than that calculated by the Rossi-alpha method. This approach, capable of enhancing the precision of measuring the prompt neutron decay constant with just a single detector, holds significant theoretical value and engineering significance for the advancement of reactor physics and experimental techniques.