The invention discloses a factor analysis model-based high resolution range profile self-adaptive framing method. The method includes the following steps that: the normalized spectrum amplitude feature of an actually measured high resolution range profile signal sample is extracted, the spectrum amplitude feature is evenly divided into small sub-frames; corresponding factor analysis models are established separately, the parameters of the models are calculated through using an EM iterative algorithm, so that the probability distribution of the sub-frames can be obtained; similarity measurement is performed on the sub-frame models through using the JS (Jensen-Shannon divergence) in the statistics, and adjacent sub-frames with high similarities are merged; and the operation of the second step and the third step is performed circularly until the Jensen-Shannon divergences between all the sub-frames are larger than a set threshold value, a frame merging process is terminated, and a framing result is outputted. According to the method of the invention, on the basis of the factor analysis models, and the Jensen-Shannon divergence is used to complete the merging of the frames; and as indicated by an experiment, the method of the invention enables a better framing effect and has higher recognition precision compared with a traditional uniform framing method and a newer probability principal component analysis model.