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检索条件"任意字段=Proceedings of the 1999 Signal and Data Processing of Small Targets"

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A three-dimensional image processing method based on data layered two-dimensional normalization

A three-dimensional image processing method based on data la...

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IEEE International Conference on signal processing, Communications and Computing (ICSPCC)

作者： Zhu, Bibo Jiang, Hanlei Cong, Weihua Hangzhou Appl Acoust Res Inst Sci & Technol Sonar Lab Hangzhou Peoples R China

ISBN: (纸本)9781728117089

Three-dimensional high-resolution imaging is a new technology for long-range detection of underwater small targets, This technology enables three-dimensional mapping of targets in water, sinking and buried environments. The three-dimensional imaging sonar adopts the ultra-wideband low-frequency emission array with large glancing angle and the two-dimensional acoustic array with wide directivity reception, which effectively acquires underwater target depth dimension, navigation dimension and azimuth dimension information. The pulse compression processing, synthetic aperture tomography processing, and anti-reverberation high-resolution array processing are used to realize three-dimensional high-resolution imaging of underwater targets. However, since the underwater echoes come from different azimuths, depths, and media environments, the significant difference causes the reverberation of the target image area to be severely unbalanced, which directly affects the background brightness and feature contrast of the target image area, and ultimately increases the artificial identify the risk of errors. In this paper, A three- dimensional image processing method based on data layered two-dimensional normalization is studied. Firstly, by tracking the three-dimensional seabed interface, the distribution law of seafloor reflection echo energy in different azimuths is statistically obtained. Then, the acoustic energy attenuation loss of different geological strata is compensated. After that, the dynamic range of the three-dimensional acoustic image and the target feature contrast are improved by the two-dimensional normalization processing of the layered water and the stratum. The method has been processed and verified by experimental data, so as to achieve stable and efficient realization of 3D acoustic image background equalization and target enhancement, which has strong robustness, certain innovation and good engineering use value.

关键词： Three-dimensional acoustic image reverberation interference layered media processing background equalization

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Building Scene Recognition Based on Deep Multiple Instance Learning Convolutional Neural Network Using High Resolution Remote Sensing Image 2019

Building Scene Recognition Based on Deep Multiple Instance L...

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proceedings of the 2019 International Conference on Video, signal and Image processing

作者： Jiafen Xie Kai Xu Zhili Li Qi Bi Kun Qin China University of Geosciences Wuhan China Wuhan China School of Remote Sensing and Information Engineering Wuhan University Wuhan China Wuhan city China

ISBN: (纸本)9781450371483

As the typical man-made objects, buildings play a special role in remote sensing images. This paper proposes a building scene recognition method based on deep multiple instance convolutional neural network. Scene classification is formulated as a multiple instance learning (MIL) problem in which local scene regions are regarded as instances and assigned with different labels. Through a trainable MIL pooling based on a spatial attention mechanism to select the most relevant instances adaptively and produce the scene-level predictions. Experimental results on UCM data set and small targets data set collected based on the GF-2 show that the method can improve the accuracy of building scene recognition using high resolution remote sensing image. Particularly, it solves the problem that it is difficult to detect the small buildings correctly and provide a new idea of scene recognition of buildings.

关键词： building scene recognition convolutional neural network(CNN) multiple instance learning(MIL) small building targets

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XY-DemoRad - Novel K- and mm-Band Radar Demo Kit for Educational and Commercial Applications 20

XY-DemoRad - Novel K- and mm-Band Radar Demo Kit for Educati...

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20th International Radar Symposium (IRS)

作者： Samczynski, P. Stasiak, K. Gromek, D. Kulpa, K. Misiurewicz, J. XY Sensing Ltd Ul Nowowiejska 15-19Pok 022A PL-00665 Warsaw Poland

ISBN: (纸本)9783736998605

This paper presents novel K- and mm-band radar demo kits operating on carrier frequencies of 24 GHz, and 120 GHz, respectively. The presented solution is a new innovative low-cost and small size radar for a wide area of applications, from education and research via the detection of drones, animals, humans and cars, to micro Doppler analyses and imaging. The system allows raw radar data to be collected, which makes this system attractive for educational and R&D purposes also, where the researchers can test their algorithms using live data collected on their own, as well as for the development of new applications like gesture recognition. In this paper, the radar demo kit architecture and its main system parameters are presented. Real results from a measurement campaign showing the system's capabilities of detecting different kinds of targets are also shown in the paper.

关键词： Doppler radar Radar applications Sensors Radar signal processing Hardware Software architecture"

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Separation of small targets in Multi-Wavelength Mixtures Based on Statistical Independence 27

Separation of Small Targets in Multi-Wavelength Mixtures Bas...

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Conference on signal processing, Sensor/Information Fusion, and Target Recognition XXVII

作者： Mowakeaa, Rami Emge, Darren K. Univ Maryland Baltimore Cty 1000 Hilltop Circle Baltimore MD 21228 USA US Army Edgewood Chem Biol Ctr RDCB DRC P Aberdeen Proving Ground MD 21010 USA

ISBN: (数字)9781510618046

ISBN: (纸本)9781510618046

small target detection is a problem common to a diverse number of fields such as radar, remote sensing, and infrared imaging. In this paper, we consider the application of feature extraction for detection of small hazardous materials in multiwavelength imaging. Since various materials may exist in the area of study each with varying degrees of reflectivity and absortion at different wavelengths of light, flexible, data-driven methods are needed for feature extraction of relevant sources. We propose the use of independent component analysis (ICA), a widely-used blind source separation method based on the statistical independence of the underlying sources. We compare 3 different prominent flavors of ICA on simulated data in a variety of environments. Then, we apply ICA to 2 multi-wavelength imaging datasets with results that suggest that features extracted are useful.

关键词： small-target detection ICA BSS multi-wavelength machine learning

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EMPACT 3D: An Advanced EMI Discrimination Sensor for CONUS and OCONUS Applications 23

EMPACT 3D: An Advanced EMI Discrimination Sensor for CONUS a...

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Conference on Detection and Sensing of Mines, Explosive Objects, and Obscured targets XXIII

作者： Keranen, Joe Miller, Jonathan S. Schultz, Gregory Sander-Olhoeft, Morgan Laudato, Stephen J. White River Technol 115 Etna Rd Lebanon NH 03766 USA Night Vis & Elect Sensors Directorate 10221 Burbeck Rd Ft Belvoir VA 22060 USA

ISBN: (纸本)9781510617681

We recently developed a new, man-portable, electromagnetic induction (EMI) sensor designed to detect and classify small, unexploded sub-munitions and discriminate them from non-hazardous debris. The ability to distinguish innocuous metal clutter from potentially hazardous unexploded ordnance (UXO) and other explosive remnants of war (ERW) before excavation can significantly accelerate land reclamation efforts by eliminating time spent removing harmless scrap metal. The EMI sensor employs a multi-axis transmitter and receiver configuration to produce data sufficient for anomaly discrimination. A real-time data inversion routine produces intrinsic and extrinsic anomaly features describing the polarizability, location, and orientation of the anomaly under test. We discuss data acquisition and post-processing software development, and results fromlaboratory and field tests demonstrating the discrimination capability of the system. data acquisition and real-time processing emphasize ease-of-use, quality control (QC), and display of discrimination results. Integration of the QC and discrimination methods into the data acquisition software reduces the time required between sensor data collection and the final anomaly discrimination result. The system supports multiple concepts of operations (CONOPs) including: 1) a non-GPS cued configuration in which detected anomalies are discriminated and excavated immediately following the anomaly survey;2) GPS integration to survey multiple anomalies to produce a prioritized dig list with global anomaly locations;and 3) a dynamic mapping configuration supporting detection followed by discrimination and excavation of targets of interest.

关键词： unexploded ordnance explosive remnants of war munitions response signal processing ordnance classification humanitarian demining electromagnetic induction

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Long-term testing of acoustic system for tracking low-flying aircraft 10

Long-term testing of acoustic system for tracking low-flying...

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10th International Conference on Knowledge and Systems Engineering (KSE)

作者： Sedunov, Alexander Salloum, Hady Sutin, Alexander Sedunov, Nikolay Stevens Inst Technol STAR Ctr Hoboken NJ 07030 USA

ISBN: (纸本)9781538661130

Stevens Institute of Technology conducted a long-term test of an acoustic system designed to track low-flying small aircraft in remote locations. The system consists of 4 nodes located between 1 and 4 km apart in a mountainous terrain. Each node is comprised of a pyramid-shaped volumetric cluster of 5 microphones, an embedded computer, and a pan-tilt-zoom camera steered to detected targets in real time. A communication device was used to transfer data to a centralized location. Each node estimates the direction of arrival toward the sound sources and sends it along to a central processing computer. The central computer combines the data from all nodes to generate tracks and classify targets. The duration and the scale of the deployment allowed to identify and solve many problems, including the effects of propagation delays between nodes on cooperative localization and tracking, the seasonal changes in environmental noise, persistent and transient noise sources, and the diversity of targets of opportunity and their signatures. The propagation delay effects led to the development of separate trackers for review of target trajectories and for immediate action such as automatically steering the camera.

关键词： signal processing passive acoustics low-flying aircraft

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Extended dwell Doppler characteristics of birds and micro-UAS at L-Band 18

Extended dwell Doppler characteristics of birds and micro-UA...

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18th International Radar Symposium (IRS)

作者： Jahangir, Mohammed Baker, Chris J. Aveillant Ltd 300 Sci Pk Cambridge England

ISBN: (纸本)9783736993433

Unmanned Aerial Systems (UAS), commonly referred to as drones, are rapidly proliferating bringing about new challenges for security and safety. The reason being their small size and ability to fly low in a highly irregular manner makes them particularly difficult to detect with conventional wide-area surveillance sensors such as a scanning radar. Here, we use staring radar that employs a 2-D antenna array and appropriate signal processing to create a multibeam, 3-D, wide-area, continuously staring surveillance sensor capable of achieving high detection sensitivity, whilst providing fine Doppler resolution with update rates of fractions of a second. Whilst staring radar is able to detect miniature UAS against a background of complex clutter, the necessary high detection sensitivity means that many other small moving targets are detected, birds being a principle example. Good Doppler discrimination is central to the ability to distinguish between genuine drones and other confuser targets such as birds that are reported by the radar sensor. Results from field trials are presented illustrating the signal characteristics of rotary wing micro-drones and birds. Analysis of the detailed data features leads to refinements enabling better discrimination between low observable micro-drones and birds.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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Unambiguous Determination of Oscillation Frequency for Multiple Objects using Quadrature Doppler Radar 30

Unambiguous Determination of Oscillation Frequency for Multi...

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Asia-Pacific Microwave Conference (APMC)

作者： Whitworth, Avon Ishmael, Khaldoon Yavari, Ehsan Boric-Lubecke, Olga Univ Hawaii Dept Elect Engn Holmes Hall 4832540 Dole St Honolulu HI 96822 USA Adnov LLC 2800 Woodlawn DrSuite 297 Honolulu HI 96822 USA

ISBN: (纸本)9784902339451

Doppler radar can potentially be used to detect respiration and heart rates of human subjects without the inconvenience of attaching transducers to the subjects. We simulated breathing rates of two subjects with two oscillating targets, and recorded the resulting data received when the targets are subject to a continuous wave signal transmitted by a 2.4GHz quadrature channel receiver. Using small changes in the initial center position of one target which passed through the null and optimum positions in the I and Q channels, and then applying a Fast Fourier Transform, we demonstrated that it is possible to remotely distinguish the oscillation frequency of each target.

关键词： Biomedical signal detection biomedical signal processing Doppler radar frequency measurement Fourier transforms

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On the use of deep neural networks for the detection of small vehicles in ortho-images 24

On the use of deep neural networks for the detection of smal...

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24th IEEE International Conference on Image processing, ICIP 2017

作者： Terrail, Jean Ogier Du Jurie, Frederic Safran Electronics and Defense Normandie Univ UNICAEN ENSICAEN CNRS France Normandie Univ UNICAEN ENSICAEN CNRS France

ISBN: (纸本)9781509021758

This paper addresses the question of the detection of small targets (vehicles) in ortho-images. This question differs from the general task of detecting objects in images by several aspects. First, the vehicles to be detected are small, typically smaller than 20×20 pixels. Second, due to the multifarious-ness of the landscapes of the earth, several pixel structures similar to that of a vehicle might emerge (roof tops, shadow patterns, rocks, buildings), whereas within the vehicle class the inter-class variability is limited as they all look alike from afar. Finally, the imbalance between the vehicles and the rest of the picture is enormous in most cases. Specifically, this paper is focused on the detection tasks introduced by the VEDAI dataset [1]. This work supports an extensive study of the problems one might face when applying deep neural networks with low resolution and scarce data and proposes some solutions. One of the contributions of this paper is a network severely outperforming the state-of-the-art while being much simpler to implement and a lot faster than competitive approaches. We also list the limitations of this approach and provide several new ideas to further improve our results. © 2017 IEEE.

关键词： Deep neural networks

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Preliminary Design of a small Tracking RADAR for LEO Space Objects

Preliminary Design of a Small Tracking RADAR for LEO Space O...

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IEEE Aerospace Conference

作者： Pecoraro, Giovanni Cianca, Ernestina Marino, Gaetano Ruggieri, Marina Italian Minist Def SICRAL Space Control Ctr Via Raffaele Giacomelli 2 I-00062 Rome Italy Univ Roma Tor Vergata Dept Elect Engn Via Politecn 1 I-00133 Rome Italy

ISBN: (纸本)9781509016136

The near Earth environment has radically changed since the first launch of Sputnik in 1957. So far, the number of uncontrolled artificial objects orbiting around the Earth has incredibly increased and the need of protecting space systems has become almost common to all spacecraft operators. Even though they are currently supported by the large U.S. Space Surveillance Network, most of them have noticed the necessity of creating their own space surveillance sensors. This paper presents a preliminary design of a small and easy to implement radar able to track LEO objects and provide orbits that are more accurate than Two-Line Element (TLE) orbits available online, which do not allow to perform a safe collision avoidance analysis. The adopted configuration is a monostatic pulsed radar with a maximum unambiguous range of 3000 km, a range resolution and angular resolutions of 20 m and 0.01 degrees, respectively. According to the theoretical assessment, the proposed radar is able to detect targets with a Radar Cross Section (RCS) of at least 1 sq. m., which means circular targets with a minimum radius of 50 cm, with a detection probability of 0.9 and a false alarm probability of 0.1. To assess the radar performance, it has been developed CASSIM (Collision Avoidance System SIMulator), which models the system at all stages, from the targets to the signal processing techniques, going through the synthesis of the transmitted and received signals. The simulations have been conducted considering a scenario described in a Collision data Message (CDM) sent by the U.S. Space Surveillance Network. The simulations have involved the less accurate TLE orbit as radar input and the CDM State Vector orbits as reference to model the simulated target. Results have shown that the radar orbit is comparable to the accurate CDM orbit and that the closest approach distance is very similar to the one indicated in the message (less than 30 m error on all components). The analysis presented in this

关键词： Transportation Supply and demand Programming Linear programming Approximation algorithms Resource management

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