前向增益(FPG)是影响光纤陀螺检测信噪比和死区非线性效应的重要参数。从光纤陀螺物理模型出发推导FPG 表达式，分析了FPG 中各物理环节在空间环境下的性能变化及其对FPG 的影响。在数字闭环光纤陀螺相干检测的基础上提出采用伪随机相关辨识法对FPG 进行在线估计的方法，通过在反馈阶梯波上叠加伪随机扰动作为辨识的输入信号，在数字信号处理器内进行相关解调的同时进行伪随机相关辨识，实时提取出FPG 的值。对陀螺正常工作时的被调制信号、方波解调信号、伪随机扰动辨识输入信号和伪随机解调信号的相关性进行了仿真计算，结果表明伪随机扰动辨识法能够在不影响陀螺的正常工作的情况下实现FPG 的实时在线估计。介绍了伪随机扰动辨识法在硬件中的实现方式，并在光纤陀螺SFS 光源组件辐照试验中对FPG 进行了实时估计，结果表明FPG 的估计能够反映出SFS 光源出纤功率的降低及陀螺随机游走系数的变化情况。

The Forward Passage Gain (FPG) is an important factor that affects the detection Signal-to-noise Ratio (SNR) and dead band nonlinearity of Fiber Optic Gyroscope (FOG). If FPG's value becomes lower, the SNR and dead band nonlinearity will be worse. The mathematical formula of FPG is deduced from the physical model, and the influence of space environment on the FPG is analyzed. The pseudo-random identification method is used to on-line estimate the FPG of the FOG. The pseudo-random signal is put on the sawtooth as the identification input signal. The pseudo-random demodulation works to extract the FPG. At the same time, the square-wave demodulation works to extract FOG's error signal. The correlation among modulated error signal, square-wave demodulation signal, pseudo-random disturbance and the pseudo-random demodulation signal is calculated, and the conclusion is made that pseudo-random demodulation will not bother the working of the FOG's demodulation process. The hardware realization is introduced and during the radiation test of the SFS components, the pseudo-random identification is validated. The test result shows that FPG can reveal the changing of output power from the SFS and the Random Walk Coefficient (RWC) of FOG.