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IEEE Transactions on Aerospace and Electronic Systems, 2023
Modern radars face challenging scenarios characterized by high levels of heterogeneity that make conventional detection/estimation algorithms no longer effective since most of them rely on the well-known homogeneous environment. In this article, we propose innovative classification schemes capable of identifying the radar operating scenario in terms of
Sudan Han +5 more
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Modern radars face challenging scenarios characterized by high levels of heterogeneity that make conventional detection/estimation algorithms no longer effective since most of them rely on the well-known homogeneous environment. In this article, we propose innovative classification schemes capable of identifying the radar operating scenario in terms of
Sudan Han +5 more
openaire +2 more sources
Representation and segmentation of a cluttered scene using fused edge and surface data
Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003An intermediate representation based on combined edge and surface data is proposed to support the recognition of objects in cluttered scenes. The representation is based on the premise that local structure of surface and edge (wings) can be reliably sensed without higher-level models, while global edge, surface, and part structures cannot be. A sensing
Gongzhu Hu, George C. Stockman
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Performance analysis of GOSCA CFAR detector in clutter edge situation
Proceedings International Radar Conference, 2002This paper studies the performance of the GOSCA CFAR detector in clutter edge situation. We derive the analytic expressions of false alarm probabilities in clutter edge situation, analyse its performance against clutter edge, and compare it with the OS, CA, GO and SO detectors.
null Jian Guan, null You He
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Modified distribution free CFAR processor for clutter edges and multi-target situations
ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005Performance of CFAR processors gets degraded at clutter edges and in multi target situations. Solutions suggested to tackle one problem degrades the performance in the other. In this paper, we show how both the problems can be handled reasonably well by using a modified version of distribution free CFAR processor[8].
V. Nagarajan +2 more
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Spatio-Temporal Degree of Hoarding Clutter Using SAM and Canny Edge Detection Against LMM
2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)Shun Hattori
exaly +2 more sources
Clutter statistics along edge features in synthetic aperture radar imagery
Journal of Electromagnetic Waves and Applications, 1995The K-distribution model for clutter over distributed targets in Synthetic Aperture Radar (SAR) images is extended to include clutter along edges and thin linear targets. The physical mechanisms generating edge features are analyzed. Assuming a boxcar system response, the detected field from a resolution cell along an edge is shown to be expressible in
R.G. Caves, P.J. Harley, S. Quegan
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Object Detection and Localization in Clutter Range Images Using Edge Features
2009We present an object detection technique that uses local edgels and their geometry to locate multiple objects in a range image in the presence of partial occlusion, background clutter, and depth changes. The fragmented local edgels (key-edgels) are efficiently extracted from a 3D edge map by separating them at their corner points.
Dipankar Das 0003 +2 more
openaire +1 more source
2009
Correlation trackers are in use for the past four decades. Edge based correlation tracking algorithms have proved their strength for long term tracking, but these algorithms suffer from two major problems: clutter and slow occlusion. Thus, there is a requirement to improve the confidence measure regarding target and non-target object. In order to solve
Muhammad Imran Khan 0004 +3 more
openaire +1 more source
Correlation trackers are in use for the past four decades. Edge based correlation tracking algorithms have proved their strength for long term tracking, but these algorithms suffer from two major problems: clutter and slow occlusion. Thus, there is a requirement to improve the confidence measure regarding target and non-target object. In order to solve
Muhammad Imran Khan 0004 +3 more
openaire +1 more source
A CFAR Detector in a Nonhomogenous Weibull Clutter
IEEE Transactions on Aerospace and Electronic Systems, 2012Saeed Gazor
exaly