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Subspace Processors for Physics-Based Application
- Source :
- Model-Based Processing ISBN: 9781119457695
- Publication Year :
- 2019
- Publisher :
- John Wiley & Sons, Inc., 2019.
-
Abstract
- In this chapter, we develop a suite of case studies applying model‐based identification (MBID) techniques to extract models for processing using both subspace and parametrically adaptive schemes. We start with a complex mechanical (structural) system applying subspace techniques followed by the development of a physics‐based model for Kalman filtering in a scintillation system applying both identification approaches. Two MBID schemes using Bayesian particle filters (PF) are developed from the underlying phenomenology in order to identify/detect fission processes as well as modal functions propagating in a shallow ocean environment. Finally, we extract (estimate) chirp and frequency‐shift key (FSK) signals from noisy data using the parametrically adaptive, unscented Kalman filter (UKF) approach.
Details
- ISBN :
- 978-1-119-45769-5
- ISBNs :
- 9781119457695
- Database :
- OpenAIRE
- Journal :
- Model-Based Processing ISBN: 9781119457695
- Accession number :
- edsair.doi...........b7113173ad0a43ba0fd879a77f1b5252