7 resultados para Clutter


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On the basis of the technique of time reversal (TR), a new method for low dielectric contrast target detection in clutter by adding dispersive delay lines (DDLs) to each element of the TR mirror (TRM) is proposed. When compared with a conventional TR system, the proposed method improves refocusing to a target by reducing the impact of other scatterers in the environment. The proposed method makes it unnecessary to estimate the position of the target and removes the need for subsequent subtraction as traditionally required. Theoretical and numerical simulated results demonstrate the proposed method.

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The problem of recognising targets in non-overlapping clutter using nonlinear N-ary phase filters is addressed. Using mathematical analysis, expressions were derived for an N-ary phase filter and the intensity variance of an optical correlator output. The N-ary phase filter was shown to consist of an infinite sum of harmonic terms whose periodicity was determined by N. For the intensity variance, it was found that under certain conditions the variance was minimised due to a hitherto undiscovered phase quadrature effect. Comparison showed that optimal real filters produced greater SNR values than the continuous phase versions as a consequence of this effect.

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A system capable of deployment as a microwave security sensor which can automatically reject background clutter is presented. The principle of operation is based on analog homodyne detection using 1. Q single side-band down conversion of an AM backscattered modulating signal envelope. A demonstrator is presented which operates with a carrier frequency of 2 GHz and 500 KHz backscattered signal. When deployed in a multipath rich open plan office environment the S/N ratio obtained at the detection output was better than 20 dB at 20 in range with 20 dBm EIRP in a 2 MHz detection bandwidth despite the presence of time varying and static clutter. (C) 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 2492-2495, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24636

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Much is known about the way bats adjust their echolocation behaviour in response to environmental structure or to locate insect prey. By contrast, little is known about how echolocation calls are modulated in response to familiarity of the environment and objects within it. Here we show that the echolocating Megachiropteran bat Rousettus aegyptiacus produces echolocation signals at the same rate whether an obstacle is predictable or unpredictable in location, but that it has a reduced rate of echolocation signal production in a familiar environment with no obstacle present. This suggests that signal production is reduced in a familiar environment absent of 'clutter' but that probing the environment for maximum information is more important for this species than minimizing any cost of probing the environment in a cluttered space.

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This paper presents an approach to improve the detection of an artificial target with low radar cross-section in presence of clutter. The target proposed in the paper modulates the phase response of the circularly polarized incident signal by means of rotation. The same physical phenomenon can be used to steer the modulated response in a non-specular direction. The bi-static measurements of the response of the target have demonstrated good agreement with theoretical prediction as well as with full-wave simulation.

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Ear recognition, as a biometric, has several advantages. In particular, ears can be measured remotely and are also relatively static in size and structure for each individual. Unfortunately, at present, good recognition rates require controlled conditions. For commercial use, these systems need to be much more robust. In particular, ears have to be recognized from different angles ( poses), under different lighting conditions, and with different cameras. It must also be possible to distinguish ears from background clutter and identify them when partly occluded by hair, hats, or other objects. The purpose of this paper is to suggest how progress toward such robustness might be achieved through a technique that improves ear registration. The approach focuses on 2-D images, treating the ear as a planar surface that is registered to a gallery using a homography transform calculated from scale-invariant feature-transform feature matches. The feature matches reduce the gallery size and enable a precise ranking using a simple 2-D distance algorithm. Analysis on a range of data sets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees, and up to 18% occlusion. In addition, recognition remains accurate with masked ear images as small as 20 x 35 pixels.

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Significant recent progress has shown ear recognition to be a viable biometric. Good recognition rates have been demonstrated under controlled conditions, using manual registration or with specialised equipment. This paper describes a new technique which improves the robustness of ear registration and recognition, addressing issues of pose variation, background clutter and occlusion. By treating the ear as a planar surface and creating a homography transform using SIFT feature matches, ears can be registered accurately. The feature matches reduce the gallery size and enable a precise ranking using a simple 2D distance algorithm. When applied to the XM2VTS database it gives results comparable to PCA with manual registration. Further analysis on more challenging datasets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees and with over 20% occlusion.