LYU Mingsen, MA Jiajun, YANG Hui, SUN Youxin, AO Xiaochun, XU Jintao, LIU Shangbo. Polymorphic enhancement of random noise injection in mechanically dithered laser gyroscopes[J]. Journal of Applied Optics, 2024, 45(6): 1284-1290. DOI: 10.5768/JAO202445.0607001
Citation: LYU Mingsen, MA Jiajun, YANG Hui, SUN Youxin, AO Xiaochun, XU Jintao, LIU Shangbo. Polymorphic enhancement of random noise injection in mechanically dithered laser gyroscopes[J]. Journal of Applied Optics, 2024, 45(6): 1284-1290. DOI: 10.5768/JAO202445.0607001

Polymorphic enhancement of random noise injection in mechanically dithered laser gyroscopes

  • Aiming at the issue of low efficiency in random noise injection in a mechanically dithered laser gyroscope, the effect of random noise on the elimination of dynamic lock-in region in laser gyroscope was intensively studied, and a functional relationship between noise frequency components and dynamic lock-in region was obtained. Based on the pseudo-random sequence and combined with the analysis of noise injection transfer function for the laser gyroscope, a polymorphic random noise enhancement injection technology was proposed, and an algorithm for polymorphic random noise enhancement injection was developed in field programmable gate array (FPGA), followed by experimental verification of the technique. The results show that, in comparison to conventional random noise injection methods, polymorphic enhanced random noise injection notably enriches the frequency components of random noise and boosts the noise amplitude in the high-frequency range. Consequently, the noise injection efficiency of the laser gyroscope rises by around 50.57%, the gyroscope accuracy is increased by about 33.62%, and the angular random walk coefficient is reduced by approximately 17.62%. The polymorphic enhanced random noise injection technology offers important reference for improving the performance of mechanically dithered laser gyroscopes.
  • loading

Catalog

    Turn off MathJax
    Article Contents

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return