Adaptive subspace-based background normalizer for sea mine classification

Manuel F. Fernandez; Tom Aridgides

doi:10.1117/12.396267

22 August 2000 Adaptive subspace-based background normalizer for sea mine classification

Manuel F. Fernandez, Tom Aridgides

Proceedings Volume 4038, Detection and Remediation Technologies for Mines and Minelike Targets V; (2000) https://doi.org/10.1117/12.396267
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

Background normalizers are used, among other things, to obtain an estimate of the local signal-to-clutter ratio (SCR), for the cell under test, under 'target present' assumptions. The classical implementation of these normalizers utilize a sliding 'split window' configuration to estimate the standard deviation of the background, with the 'split' or 'gap' in the window aiming to avoid the possibility of target signal leaking into the estimate. Unfortunately, there are tradeoffs between gap size and estimation accuracy: if the gap is too small, target signal leakage will taint the estimate; if the gap is too large, the estimate will not be representative of the background in the vicinity of the target. These drawbacks translate into reduced spatial resolution or lack of detection sensitivity.

Citation Download Citation

Manuel F. Fernandez and Tom Aridgides "Adaptive subspace-based background normalizer for sea mine classification", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); https://doi.org/10.1117/12.396267

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