在测量数据有限情况下，由于难以获得频响函数(FRF)的准确估计，使用FRF 作为原始数据的传统模态参数识别方法将不再适用。针对该问题，提出一种基于频响函数左矩阵分式模型的模态参数识别方法。该方法直接使用输入输出数据FFT 谱(IO 谱)作为原始数据，避免了频响函数估计。通过最小二乘估计在Z 域内求解模态参数，改善了矩阵的求解性态。针对左矩阵分式模型的特点，给出了一种通过主分量分析(PCA)建立稳定图的方法。最后采用GARTEUR 飞机模型建立仿真算例对所提出的方法进行了验证。

Owing to the FRF cannot be estimated exactly when only a limited test data is available, classical modal
parameters identification algorithms using FRF as primary data are not suit anymore. Focusing on the problems, a
modal parameters identification algorithm based on left matrix fraction description of FRF is proposed. The
algorithm uses FFT spectrum of input and output data as primary data. The modal parameters are achieved by using
LS estimator. The bad numerical condition of matrix can be avoided in Z domain. Considering the feature of left
matrix fraction description, a construction method of stabilization diagram is presented by principal component
analysis (PCA). A simulation case of GARTEUR model is employed to validate the algorithm.