Matched subspace detectors

Time-Frequency Subspace Detectors and Application to Knock Detection

Abstract We consider a composite hypotheses detection problem involving a subspace and an energy level, and we show that for this problem the matched subspace detector is uniformly most powerful and the generalized likelihood ratio detector. We present a generalization of the matched subspace detector and time-frequency methods for the formulation and design of subspace detectors. Finally, we a...

Matched Subspace Detectors for Distinguishingbetween Two Signals with Extensions to BlindMaximum Likelihood Sequence

| The problem of distinguishing between two signals when only a ltered version of the transmitted signals is available and the coeecients of the lter are unknown gives rise to matched subspace detector. In this paper we will investigate the performance of matched subspace detectors for distinguishing between two signals. We will demonstrate that the matched subspace detector is equivalent to a ...

A Comparative Analysis of Kernel Subspace Target Detectors for Hyperspectral Imagery

Several linear and nonlinear detection algorithms that are based on spectral matched (subspace) filters are compared. Nonlinear (kernel) versions of these spectral matched detectors are also given and their performance is compared with linear versions. Several well-known matched detectors such as matched subspace detector, orthogonal subspace detector, spectral matched filter, and adaptive subs...

Matched subspace detectors and distributed detection

Matched Subspace Detectors for Stochastic Signals

Our aim in this paper is to extend the matched subspace detectors (MSDs) of [1–3] to the detection of stochastic signals. In [1–3] the signal to be detected was assumed to be placed deterministically at an unknown location in a known signal subspace. The basis for the subspace was irrelevant. In this paper the signal is assumed to be placed randomly at an unknown location in a known subspace. I...

Robust Gaussian and non-Gaussian matched subspace detection

We address the problem of matched filter and subspace detection in the presence of arbitrary noise and interference or interfering signals that may lie in an arbitrary unknown subspace of the measurement space. A minmax methodology developed to deal with this uncertainty can also be adapted to situations where partial information on the interference or other uncertainties is available. This met...