Papers by Keyword: Drift Error

Abstract: Frequency locking of resonator gyro (R-FOG) is a key technology in gyro signal detection, the frequency locking stability determines the performance of the gyro. Based on transmission theory of ring resonator, this paper analyzes the resonant characteristics, builds the R-FOG system, realizes the output of resonance spectral line first harmonic by using sine wave phase modulation and demodulation technology. According to the source of circuit drift error in the traditional analogue proportion integral (PI), the T-type feedback network which can effectively inhibit the drift error was proposed and applied to the frequency locking of resonator gyro, which obtained better effect. By Allan variance analysis, the locking stability of resonant frequency for 4000s is better than 9×10^-12.

Abstract: With the rapid development of quantum manipulation technique, atomic spin gyroscope has been demonstrated in recent years. Understanding the sources and the influence of error on the performance of atomic spin gyroscope is important during the design of such devices. The basic principle of atomic spin gyroscope was reviewed and the analysis of error sources presented began with the coupled Bloch equations describing the dynamics of atomic spin gyroscope including magnetic field, light shift and pump-probe non-orthogonality. It was shown analytically that the first order effects of the transverse magnetic fields and imperfections can be eliminated by turning the longitudinal magnetic field on the magnetic field compensation point. The effects of longitudinal magnetic field and light shift imperfections with other terms zeroed contributed only to scale factor of the atomic spin gyroscope. Furthermore, the effects magneto-optical crystal and magnetic shielding due to temperature drift were described and according approaches to suppress these errors were also proposed.

Abstract: The characteristic of the drift error of inertial platform is a high-order nonlinear dynamic system, using the neural networks’ abilities of universal approximation of differentiable trajectory and capturing system dynamic information, this paper presents the drift error identifying project of inertial platform based on Elman networks structure. First, the drift error model of inertial platform is established, after selecting the input and output for network, momentum and alterable speed algorithm is used to speed up the network convergence. On the basis of the algorithm, the extended nonlinear node function in the hidden network does not only improve the learning speed of network, but also satisfies the need of accuracy on system identification. Through the drift error data measured on inertial platform, the training result shows that the scheme achieves satisfied identification results.