Abstract
The ability to extract weak signal components, or micro-signatures, from acoustic array data can be used to help classify targets with greater detail. In order to discover and evaluate micro-signatures in actual circular acoustic array data, a signal collection system and a new micro-signature extraction algorithm was developed. This micro-signature extraction algorithm replaces traditional time-frequency analysis techniques with a new high-resolution subspace-enhanced linear predictive extrapolation technique. This technique is used to extend the data within each analysis window in order to create a longer data sequence for conventional STFT time-frequency analysis. This paper presents this algorithm along with the results of applying it to actual acoustic array data.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
