Topological multimodal sensor data analytics for target recognition and information exploitation in contested environments

Paul T. Schrader

doi:10.1117/12.2662383

14 June 2023 Topological multimodal sensor data analytics for target recognition and information exploitation in contested environments

Paul T. Schrader

Author Affiliations +

Proceedings Volume 12547, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII; 125470C (2023) https://doi.org/10.1117/12.2662383
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

A modern, contested environment produces exponential amounts of data from a vast array of multimodal sensory inputs for intelligence actively updating our situational awareness (SA). The effective management and interpretation of this digital information for (near) real-time decision processes has obscured resulting in imminent costs. This data’s mathematical structures (e.g., its topology) provides a rich, alternative information space where SA could be transformed. Recent successes in topological data analysis (TDA) for a wide array of applications forecast its target recognition capability derived from a sensing grid’s multimodal data and its aggregates. This research introduces novel artificial intelligence/machine learning (AI/ML) pipeline designs invoking TDA-based feature engineering from acoustic, electro-optical (EO), and infrared (IR) data which produce efficient models with near perfect accuracy, precision, and recall in target recognition capability on a range of small unmanned aerial systems (SUASs), ground vehicles, and dismounts (or ground personnel) involving real world environments.

Conference Presentation

Citation Download Citation

Paul T. Schrader "Topological multimodal sensor data analytics for target recognition and information exploitation in contested environments", Proc. SPIE 12547, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII, 125470C (14 June 2023); https://doi.org/10.1117/12.2662383

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