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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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Time-Frequency Analysis of Millimeter-Wave Radar Micro-Doppler data from small UAVs 7

Time-Frequency Analysis of Millimeter-Wave Radar Micro-Doppl...

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7th conference of the Sensor signal processing for Defence, SSPD 2017

作者： Rahman, Samiur Robertson, Duncan SUPA School of Physics and Astronomy University of St Andrews St Andrews United Kingdom

ISBN: (纸本)9781538616635

Micro-Doppler feature analysis of small UAVs (sUAVs) is of great importance for identifying such targets. This paper discusses methods that can be used for analyzing various Doppler features present in the radar signal return from sUAVs. A 94 GHz radar is used in both CW and FMCW modes for data collection, and produces high fidelity micro-Doppler returns. Wavelet decomposition method is then used to extract the high frequency components of the signal that correspond to the characteristic fast moving parts of the sUAVs. Finally, time-frequency analysis is performed to visualize and interpret the features. © 2017 IEEE.

关键词： Drones

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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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Three-dimensional Imaging Sonar signal processing System Based on Blade Server

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Journal of Physics: conference Series 2019年第4期1213卷

作者： Xiangrui Zeng Jingyang Liu Bo Gao Science and Technology on Sonar Laboratory Hangzhou Research Institute of Applied Acoustics Hangzhou 310012 China

The three-dimensional high-resolution imaging sonar uses multi-beam technology combined with synthetic aperture technology to achieve centimeter-level imaging of small underwater targets. It has a good imaging effect on underwater anchoring, sinking mine and buried mine target detection and underwater topography, and has a wide range of military and civil engineering applications. The system has a large amount of data transmission and computation, including multiple functional modules such as synthetic aperture, high resolution array processing, image processing, and target recognition. The software architecture is complex and real-time system development faces serious challenges. The blade servers have been widely used in the telecommunications, financial and other big data processing fields as for the high efficiency, stability and autonomy. This paper introduces a cluster 3D imaging signal processing system based on x240m5 blade server. The message queue communication (ZMQ) is used to realize the stable transmission of large data volume. At the same time, the mixed programming technology of C language and Matlab language combines the convenience of real-time and software integration, which greatly shortens the development cycle. The system runs stably and realizes the imaging recognition of the small spheres and their clump weights in the simulated target water.

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Adaptive Kalman Filter for Tracking of Fast Accelerating targets 14

Adaptive Kalman Filter for Tracking of Fast Accelerating Tar...

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14th European Radar conference (EURAD)

作者： Hudec, Premysl Panek, Petr Czech Tech Univ Fac Elect Engn Dept Electromagnet Field Tech 2 Prague 16627 6 Czech Republic Acad Sci Czech Republ Inst Photon & Elect Chaberska 57 Prague 8 Czech Republic

ISBN: (纸本)9782874870491

Active defense (AD) is a new method for protecting military vehicles. Instead of using thick and extremely heavy armors, the actively protected vehicles monitor approaching threatening missiles and de-active them by a suitable active counter-measures. The majority of AD systems is based on radar sensors capable of detecting the concerned missiles and measuring their parameters important for the protective functions. Often, these radar sensors are required to operate in a near-zone (from zero to tens of meters) and find and track relatively small and fast-flying targets. Beside that, it is necessary to take into account the fact that the velocity of the monitored targets can instantaneously vary. This problem especially refers to ignition of rocket engines which can abruptly introduce extremely high accelerations. If the concerned radar sensors employ signal-processing methods based on Kalman filtration, these high-order time-derivatives can cause substantial convergence problems. The main purpose of this article is to present the newly developed adaptable filtering which can reduce these effects. The designed procedures were verified using practically recorded data from flight of RPG-7 missiles.

关键词： Kalman filtration adaptive filtration radar sensor pseudo-noise CW radar

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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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Supervised Semi-Autoencoder Learning for Multi-Layered Neural Networks 17

Supervised Semi-Autoencoder Learning for Multi-Layered Neura...

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Joint 17th World Congress of International-Fuzzy-Systems-Association / 9th International conference on Soft Computing and Intelligent Systems (IFSA-SCIS)

作者： Kamimura, Ryotaro Takeuchi, Haruhiko Tokai Univ IT Educ Ctr 4-1-1 Kitakaname Hiratsuka Kanagawa 2591292 Japan Natl Inst Adv Ind Sci & Technol Human Informat Res Inst 1-1-1 Higashi Tsukuba Ibaraki 3058566 Japan

ISBN: (纸本)9781509049172

The present paper proposes a new type of layer-wise learning for multi-layered neural networks. Multi-layered neural networks have the serious problem of vanishing information, where information contained in input patterns is gradually lost, and preventing neural networks from learning input patterns. In particular, the autoencoders used in the greedy layer-wise pre-training tend to lose the original information by going through multiple layers. For this problem, we propose a new approach called "supervised semi-autoencoder" to solve the problem of vanishing information. The new method is close to the ordinary autoencoder, but the outputs are the original inputs and the corresponding targets for amplifying information in input patterns. In addition, the computational procedures are simplified by using potential learning, in which the potentiality of neurons is determined before learning, and is given as initial weights. Thus, the complicated adjustment of parameters is not necessary. The method was applied to the well-known crab data set as well as the real data set of eye-tracking records. In both cases, with relatively small-sized data, neural networks could find internal representations close to those obtained by larger ones, and better generalization performance could be observed.

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

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Multi-channel quasi-adaptive processing based on low and slow targets in complex environment

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AIP conference Proceedings 2018年第1期1967卷

作者： Tonghui Xue Tao Shan Yuan Feng Beijing Institute of Technology Beijing China

Because there are many kinds of clutter interference in the detection of low and slow small targets, clutter suppression is always an important issue in radar signal processing. In this paper, clutter in complex environment is first analyzed based on a large amount of measured data, In theory, the clutter suppression algorithm with narrow spectral width and broad spectrum width is effectively studied: the weighted mean filter algorithm and the noise subspace algorithm, and the improved algorithm of weighted mean filter is proposed. Secondly, Multi-channel quasi-adaptive clutter suppression filter, simple and practical, can effectively suppress clutter in complex environments, and the algorithm is implemented, verified by the measured data, and confirmed good results.

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Adaptive Kalman filter for tracking of fast accelerating targets

Adaptive Kalman filter for tracking of fast accelerating tar...

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European Radar conference (EURAD)

作者： Premysl Hudec Petr Panek Department of Electromagnetic Field Czech Technical University in Prague Prague 6 Czech Republic Academy of Sciences of the Czech Republic Institute of Photonics and Electronics Czech Republic

关键词： Standards Estimation Radar Kalman filters Missiles Sensors Engines

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