We introduce geometric and topological methods to develop a new framework for fusing multi-sensor time series. This framework consists of two steps: (1) a joint delay embedding, which reconstructs a high-dimensional state space in which our sensors correspond to observation functions, and (2) a simple orthogonalization scheme, which accounts for tangencies between such observation functions, and produces a more diversified geometry on the embedding space. We conclude with some synthetic and real-world experiments demonstrating that our framework outperforms traditional metric fusion methods.
@article{arxiv.2002.11201,
title = {Geometric Fusion via Joint Delay Embeddings},
author = {Elchanan Solomon and Paul Bendich},
journal= {arXiv preprint arXiv:2002.11201},
year = {2020}
}