Exploiting vibration-based spectral signatures for automatic target recognition

Lauren Crider; Scott Kangas

doi:10.1117/12.2052860

10 June 2014 Exploiting vibration-based spectral signatures for automatic target recognition

Lauren Crider, Scott Kangas

Proceedings Volume 9079, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V; 90790N (2014) https://doi.org/10.1117/12.2052860
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

Feature extraction algorithms for vehicle classification techniques represent a large branch of Automatic Target Recognition (ATR) efforts. Traditionally, vehicle ATR techniques have assumed time series vibration data collected from multiple accelerometers are a function of direct path, engine driven signal energy. If data, however, is highly dependent on measurement location these pre-established feature extraction algorithms are ineffective. In this paper, we examine the consequences of analyzing vibration data potentially contingent upon transfer path effects by exploring the sensitivity of sensor location. We summarize our analysis of spectral signatures from each accelerometer and investigate similarities within the data.

Citation Download Citation

Lauren Crider and Scott Kangas "Exploiting vibration-based spectral signatures for automatic target recognition", Proc. SPIE 9079, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V, 90790N (10 June 2014); https://doi.org/10.1117/12.2052860

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