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Generalized likelihood ratio test change detection with optical theorem constraint.

Jing Tu, Edwin A Marengo

Journal of the Optical Society of America. A, Optics, Image Science, and Vision

|November 19, 2016

Summary

This summary is machine-generated.

We present a novel method using the optical theorem to improve the detection of unknown scatterers in noisy data. This technique leverages background information and a physics-based constraint for enhanced signal detection.

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Area of Science:

Wave physics
Inverse scattering problems
Signal processing

Background:

Detecting unknown scatterers in noisy environments is challenging.
Existing methods often struggle with unknown background media.
Background field information is crucial but underutilized.

Purpose of the Study:

To develop a new method for enhancing scatterer detection using the optical theorem.
To incorporate a physics-based constraint derived from the optical theorem into detection algorithms.
To demonstrate the effectiveness of this approach in noisy conditions with unknown backgrounds.

Main Methods:

A generalized likelihood ratio test detector was developed.
An optical theorem constraint was integrated into the detector.
The method was formulated within a general Hilbert space framework.
Nonlinear programming was used to incorporate the constraint.

Main Results:

The optical theorem constraint enhances detection of unknown scatterers from noisy data.
Background field information is shown to be highly relevant beyond simple suppression.
The method demonstrates successful detection performance in various scenarios.
Compact forms of the constraint were derived for spherical and cylindrical systems.

Conclusions:

The optical theorem provides a powerful constraint for improving scatterer detection.
This physics-based approach offers significant advantages over traditional methods.
The methodology is broadly applicable to various scattering systems and practical applications.