This paper proposes a space target recognition algorithm based on the trace feature of ISAR (Inverse Synthetic Aperture Radar) image. Firstly

the ISAR images are segmented and normalized. The Canny edge detection and Hough transform method are used to extract the longest axis of the ISAR image of space target to ensure the rotation invariance of the proposed feature. Then

Trace transformation is only carried out in the local area where the longest axis is located to generate the local trace matrix of ISAR image

so that the trace features proposed can meet the requirements of low dimension; then each column of the trace matrix is shifted and aligned to eliminate the impact of ISAR image translation on the recognition and take it as the feature vector of the space target recognition; finally

taking the minimum Euclidean distance as the dissimilarity in the feature space

AdaBoost.M2-KNN

an ensemble classifier

is used to classify and recognize the five types of space objects. The method is validated by the ISAR data of five types of space targets

and compared with several existing ISAR image feature extraction methods. The results show that the proposed algorithm is feasible and effective

and can significantly improve the recognition rate.