针对红外成像的小型化稳定平台参数辨识的问题，对系统中非线性因素进行尽可能抑制，并在高速环境下对系统进行辨识。在辨识过程中，利用伪随机信号（Pseudo random binary signal，PRBS）作为调制的输入电压信号对系统激励，相应的系统输出响应为速度信号，并应用增广最小二乘方法辨识线性离散模型参数，最后通过参数化和非参数化两种方式，对辨识模型的精确度进行了验证。结果表明：辨识得到的用来衡量实际系统输出随输入变化的传函关系的参数模型，能够反映真实系统的动态特性，满足辨识精度要求。

This study focuses on parameter identification for miniature stabilized platforms based on infrared imaging and offers a linearization technique to reduce the nonlinear effect on modeling identification. During the identification process, a pseudorandom binary sequence is used as the modulated input signal to drive the system, and the corresponding system output is a velocity signal. In addition, the augmented least square method is applied to identify the discrete modeling parameter. Finally, the precision of the modeling is tested in two ways: parameterization and non-parameterization. The results show that parameter modeling can adequately describe the dynamic character, similar to the real system.