IFT paper “A joint manifold leaning-based framework for heterogeneous upstream data fusion” has been published in Journal of Algorithms & Computational Technology. In this work a joint manifold learning fusion (JMLF) approach is proposed for nonlinear or mixed sensor modalities with large streams of data. The multimodal sensor data are stacked to form joint manifolds, from which the embedded low intrinsic dimensionalities are discovered for moving targets.