Polymorphic enhancement of random noise injection in mechanically dithered laser gyroscopes

This study aims to tackle the issue of low efficiency in random noise injection in a mechanically dithered laser gyroscope. It comprehensively examines the impact of various frequency components of random noise on eliminating the dynamic lock-in region in the laser gyroscope and establishes a functional relationship between noise frequency components and the dynamic lock-in region. Utilizing a pseudorandom sequence and an analysis of the noise injection transfer function for the laser gyroscope, a polymorphic random noise enhancement injection technique is proposed. An algorithm for polymorphic random noise enhancement injection is developed in field programmable gate array (FPGA), followed by experimental verification of the technique. The results demonstrate 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%, enhancing gyroscope accuracy by about 33.62%, and reducing the angular random walk coefficient by approximately 17.62%. The polymorphic enhanced random noise injection technique offers valuable insights for improving the performance of mechanically dithered laser gyroscopes.