Deep learning-based fiber laser sub-aperture coherent synthesis phase control method

Abstract

The invention provides a deep learning-based fiber laser sub-aperture coherent synthesis phase control method. According to the method, firstly, a non-Fourier plane light spot image is acquired as a training sample, and an analysis model is trained by the training sample. Secondly, a non-Fourier plane light spot image corresponding to a to-be-controlled optical fiber laser emission surface array light beam containing phase noise is acquired in real time in an optical fiber laser sub-aperture coherent synthesis system. Thirdly, the obtained non-Fourier plane light spot image is input into the trained analysis model for analysis. Fourthly, the relative phase information of each light beam in the optical fiber laser emission surface array light beam corresponding to the non-Fourier plane light spot image is obtained. Fifthly, the preliminary compensation is performed on the piston phase error of the optical fiber laser emission surface array light beam. Fifthly, the secondary compensationis performed on the piston phase error after preliminary compensation by using a random parallel gradient descent algorithm to ensure that all light beams in the optical fiber laser emission surfacearray light beam are effectively controlled to be output in the same phase. The method has the advantages of high control precision, high convergence speed, high control bandwidth and the like.

Description

technical field [0001] The present invention relates to the field of fiber laser coherent combination, in particular to a method for controlling the phase of fiber laser sub-aperture coherent combination based on deep learning. Background technique [0002] Coherent combination technology is an effective way to achieve high average power and high beam quality laser output. The key to realize coherent combination is to control the phase of each beam to ensure that the output of each beam is in phase. [0003] But in the prior art: the heterodyne method (J.Anderegg, et al., Proc.of SPIE 6102, 61020U (2006).) uses a beam splitter to split the array beam, one part is output as the main laser, and the other part is combined with the reference light Interference, which detects and compensates the phase of each beam by detecting the interference signal, so as to ensure that the phase of the array beam is consistent, but this method needs to provide the same number of detectors and ...

AI Technical Summary

Problems solved by technology

[0003] But in the prior art: the heterodyne method (J.Anderegg, et al., Proc.of SPIE 6102, 61020U (2006).) uses a beam splitter to split the array beam, one part is output as the main laser, and the other part is combined with the reference light Interference, which detects and compensates the phase of each beam by detecting the interference signal, so as to ensure that the phase of the array beam is consistent, but this method needs to provide the same number of detectors and demodulation circuits as the number of synthesized channels, the complexity of the system and the difficulty of adjustment Expand the number of limited array beams

[0004] The multi-jitter method (T.M.Shay, Opt.Express 14, 12188-12195(2006).) uses high-frequency oscillation signals of different frequencies as the carrier of phase noise to perform small-amplitude phase modulation on the phase modulator, and uses band-pass filters and The phase-lock detection demodulates the phase noise at the performance evaluation function analysis module, and then obtains and compensates the phase noise of each beam, and realizes the output of each beam in the same phase. However, with the increase of the number of array beams, the phase noise The characteristic frequency increases. In order to ensure that the bandwidth of the phase control system is higher than the characteristic frequency of the phase noise, the carrier frequency of the phase modulation increases. The difficulty of circuit production limits the expansion of the number of array beams.

[0005] The single-frequency dithering method (Y.Ma, et al., Opt.Lett.35, 1308-1310(2010).) adopts the same experimental structure as the multi-jittering method, and improves the control algorithm. Only one modulation signal is required, According to the way of time division multiplexing, it is loaded to the corresponding phase modulator of each beam, and the signal processor demodulates the modulation signal of each beam in time division, and then obtains and compensates the phase noise of each beam, and realizes the phase noise of each beam. Synchronization, the number of expansion ability of this method is better than that of the multi-jitter method, but it needs multiple iterations to converge to the global optimum

[0006] The stochastic parallel gradient descent method (P.Zhou, et al., IEEE J.Sel.Top.Quant.Elect.15, 248-256(2009).) takes the phase of each beam as a variable, and executes the algorithm to analyze the phase of each beam The phase is optimized and controlled, and the system performance evaluation function (usually the Strehl ratio in the far field of the synthesized beam or the power in the bucket is selected) converges to the extreme value after multiple iterations. However, with the expansion of the number of array beams, the effective control bandwidth of the algorithm for phase noise decreases, which limits the realization of coherent combination of large numbers of laser beams.

[0007] In summary, the existing technologies can be effectively implemented when the number of synthesis channels is small, but with the further expansion of the number of synthesis channels, factors such as the system complexity of the prior art and the control bandwidth for phase noise will limit the array beam. Efficient Implementation of Phase Control

Images