THE PRINCIPAL COMPONENT INVERSE ALGORITHM FOR DETECTION IN THE PRESENCE OF REVERBERATION USING AUTOREGRESSIVE MODEL

Document Type: Research Paper

10.22099/ijste.2014.2100

Abstract

Reverberation noise in active sonar leads to a very complicated situation for target
detection. Reverberation is often modeled as the autoregressive model. In this paper, the
autoregressive model is considered for reverberation and the Principal Component Inverse (PCI)
algorithm is used to separate target echo signal from reverberation. This consideration helps us to
propose a new method to improve computational complexity for the rank determination of the
observation matrix via singular value decomposition. It is shown that this new method is efficient
on real data to separate target echo signal from reverberation.

Keywords