General Detection Scheme Research Articles

Macro detection using fluorescence detectors

Macroscopic dark matter (aka macros) constitutes a broad class of alternatives to particulate dark matter. We calculate the luminosity produced by the passage of a single macro as a function of its physical cross section. A general detection scheme is developed for measuring the fluorescence caused by a passing macro in the atmosphere that is applicable to any ground based or space based Fluorescence Detecting (FD) telescopes. In particular, we employ this scheme to constrain the parameter space (σx vs Mx) of macros than can be probed by the Pierre Auger Observatory and by the Extreme Universe Space Observatory onboard the Japanese Experiment Module (JEM-EUSO). It is of particular significance that both detectors are sensitive to macros of nuclear density, since most candidates that have been explored (excepting primordial black holes) are expected to be of approximately nuclear density.

A Robust Regularization Kernel Regression Algorithm for Passive Millimeter Wave Imaging Target Detection

This letter deals with small target detection in passive millimeter wave (PMMW) imaging. Specifically, it focuses on a general detection scheme, where, first, the background is suppressed through a background prediction algorithm, and then the detection is accomplished. A precise prediction of the background is essential to a successful outcome. In practical applications, background estimation problem is more suitable to be considered as a nonlinear regression problem. Kernel methods are effective to solve the nonlinear problem. To improve the accuracy of the background prediction with kernel methods, we utilize robust loss function, to tolerate the noise outliers, and regularization methods, to avoid overfitting of the data. Experiments are conducted on PMMW images collected by a synthetic aperture imaging radiometer. The results demonstrate the effectiveness of the proposed algorithm.

An Automatic Approach to Adaptive Local Background Estimation and Suppression in Hyperspectral Target Detection

This paper deals with subspace-based target detection in hyperspectral images. Specifically, it focuses on a general detection scheme where, first, background is suppressed through orthogonal-subspace projection and then target detection is accomplished. An adequate estimation of the background subspace is essential to a successful outcome. The background subspace has been typically estimated globally. However, global approaches may be ineffective for small-target-detection applications since they tend to overestimate the background interference affecting a given target. This may result in a low target residual energy after background suppression that is detrimental to detection performance. In this paper, we propose a novel and fully automatic algorithm for local background-subspace estimation (LBSE). Local background has typically a lower inherent complexity than that of global background. By estimating the background subspace over a local neighborhood of the test pixel, the resulting background-subspace dimension is expected to be low, thus resulting in a higher target residual energy after suppression which benefits the detection performance. Specifically, the proposed LBSE acts on a per-pixel basis, thus adaptively tailoring the estimated basis to the local complexity of background. Both simulated and real hyperspectral data are employed to investigate the detection-performance improvements offered by LBSE with respect to both global and local methodologies previously presented.

Detection of O and N atoms by two-photon laser-induced fluorescence

The sensitive detection of ground-state atomic species under nonideal experimental conditions, such as those found in combustion reseach or plasmas, has been a problem for many years. Single-photon detection techniques such as resonance fluorescence are not applicable, since the medium is generally opaque at VUV wavelengths. We describe a new general detection scheme for atomic species based on two-photon excitation using wavelengths that will be transmitted and its application to the detection of oxygen1 and nitrogen atoms.