The present invention relates to the ﬁeld of artiﬁcial intelligence technology, and provides a multi-source target tracking method for complex scenes, including the following steps: forming 5 an initial deep learning network, setting weights of the initial deep learning network, performing steepest gradient dimensionality reduction on the weights of the initial deep learning network, and forming an initial feature matrix of a multi-source target, performing simpliﬁed sparse representation and sparsif1cation processing on the initial feature matrix of the multi-source target to obtain a sparsified target feature matrix, and classifying the sparsified target feature 10 matrix, and establishing feature matrix representations of different feature targets, A multi-source target feature matrix library established through the deep learning network in the present invention has a good modeling characteristic and data statistical structure, and a multi-source target tracker model is generated for unlabeled training data. 12
MULTI-SOURCE TARGET TRACKING METHOD FOR COMPLEX SCENES