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Leslie M Collins - One of the best experts on this subject based on the ideXlab platform.

  • frequency domain Electromagnetic Induction sensor data feature extraction and processing for improved landmine detection
    International Conference on Multimedia Information Networking and Security, 2011
    Co-Authors: Stacy L Tantum, Leslie M Collins, Kenneth D Morton, Peter A Torrione
    Abstract:

    Frequency-domain Electromagnetic Induction (EMI) sensors have the ability to provide target signatures which enable discrimination of landmines from harmless clutter. In particular, frequency-domain EMI sensors are well-suited for target characterization by inverting a physics-based signal model. In many model-based signal processing paradigms, the target signatures can be decomposed into a weighted sum of parameterized basis functions, where the basis functions are intrinsic to the target under consideration and the associated weights are a function of the target sensor orientation. The basis function parameters can then be used as features for classification of the target as landmine or clutter. In this work, frequency-domain EMI sensor data feature extraction and processing is investigated, with a variety of physics-based models and statistical classifiers considered. Results for data measured with a prototype frequency-domain EMI sensor at a standardized test site are presented. Preliminary results indicate that extracting physics-based features followed by statistical classification provides an effective approach for classifying targets as landmine or clutter.

  • performance of a four parameter model for modeling landmine signatures in frequency domain wideband Electromagnetic Induction detection systems
    International Conference on Multimedia Information Networking and Security, 2007
    Co-Authors: Eric B Fails, Waymond R Scott, Peter A Torrione, Leslie M Collins
    Abstract:

    This work explores possible performance enhancements for landmine detection algorithms using frequency domain wideband Electromagnetic Induction sensors. A pre-existing four parameter model for conducting objects based on empirically collected data for UXO is discussed, and its application for accurately modeling landmine signatures is also considered. Discrimination of mines versus clutter based on the extracted model parameters is considered. Furthermore, this work will compare the effectiveness of discrimination based on the four parameter model to a matched subspace detection algorithm. Experimental results using data from government run test sites will be presented.

  • performance of a four parameter model for modeling landmine signatures in frequency domain wideband Electromagnetic Induction detection systems
    International Conference on Multimedia Information Networking and Security, 2007
    Co-Authors: Eric B Fails, Waymond R Scott, Peter A Torrione, Leslie M Collins
    Abstract:

    This work explores possible performance enhancements for landmine detection algorithms using frequency domain wideband Electromagnetic Induction sensors. A pre-existing four parameter model for conducting objects based on empirically collected data for UXO 1 is discussed, and its application for accurately modeling landmine signatures is also considered. Discrimination of mines versus clutter based on the extracted model parameters is considered. Furthermore, this work will compare the effectiveness of discrimination based on the four parameter model to a matched subspace detection algorithm. 2,3 Experimental results using data from government run

  • a statistical approach to landmine detection using broadband Electromagnetic Induction data
    IEEE Transactions on Geoscience and Remote Sensing, 2002
    Co-Authors: Leslie M Collins, Deborah Schofield, J Moulton, Larry Makowsky, Denis Michael Reidy, Richard Weaver
    Abstract:

    The response of time-domain Electromagnetic Induction (EMI) sensors, which have been used almost exclusively for landmine detection, is related to the amount of metal present in the object and its distance from the sensor. Unluckily, there is often a significant amount of metallic clutter in the environment that also induces an EMI response. Consequently, EMI sensors employing detection, algorithms based solely on metal content suffer from large false alarm rates. To mitigate this false alarm problem for mines with substantial metal content, statistical algorithms have been developed that exploit models of the underlying physics. In such models it is commonly assumed that the soil has a negligible effect on the sensor response, thus the object is modeled in "free space." We report on studies that were performed to test, the hypotheses that for broadband EMI sensors: 1) soil cannot be modeled as free space when the buried object has low metal content and 2) advanced signal processing algorithms can be applied to reduce the false alarm rates. Our results show that soil cannot be modeled as free space and that when modeling soil correctly our advanced algorithms reduced the false alarm probability by up to a factor of 10 in blind tests.

  • classification of landmine like metal targets using wideband Electromagnetic Induction
    IEEE Transactions on Geoscience and Remote Sensing, 2000
    Co-Authors: Leslie M Collins, P M Garber, Norbert Geng, Lawrence Carin
    Abstract:

    In their previous work, the authors have shown that the detectability of landmines can be improved dramatically by the careful application of signal detection theory to time-domain Electromagnetic Induction (EMI) data using a purely statistical approach. In this paper, classification of various metallic land-mine-like targets via signal detection theory is investigated using a prototype wideband frequency-domain EMI sensor. An algorithm that incorporates both a theoretical model of the response of such a sensor and the uncertainties regarding the target/sensor orientation is developed. This allows the algorithms to be trained without an extensive data collection. The performance of this approach is evaluated using both simulated and experimental data. The results show that this approach affords substantial classification performance gains over a standard approach, which utilizes the signature obtained when the sensor is centered over the target and located at the mean expected target/sensor distance, and thus ignores the uncertainties inherent in the problem. On the average, a 60% improvement is obtained.

I J Won - One of the best experts on this subject based on the ideXlab platform.

  • automated identification of buried landmines using normalized Electromagnetic Induction spectroscopy
    IEEE Transactions on Geoscience and Remote Sensing, 2003
    Co-Authors: Haoping Huang, I J Won
    Abstract:

    Electromagnetic Induction spectroscopy (EMIS) is used to identify a buried metallic object such as a landmine, based on its EMI spectrum. EMIS, however, depends on the object's electrical conductivity, magnetic permeability, shape, size, depth, and orientation. For a given mine made of specific metals, shape, and size, however, the only variables are the mine's burial depth and orientation. This paper describes a method of identifying a landmine using a normalized EMIS spectrum, which is independent of the orientation or depth. We assume that the target is small compared with its distance to or size of the sensor so that the source field at a target is uniform. In this case, the normalized spectrum will be range-independent and, therefore, the target identification is based on only spectral shapes. We have developed and tested an algorithm that matches a normalized EMIS spectrum to those of library targets. We applied the new process to 1) numerically simulated data, 2) experimental data from controlled sites using inert mines, mine simulants, and clutter items, and 3) finally extensive field data collected at a blind test site established by the U.S. Army. Test results show that targets are correctly identified with a misfit of less than 10%; they also show that 80% of clutter may be rejected, based on a misfit over 30%.

  • detection and identification of landmines using Electromagnetic Induction spectroscopy
    International Geoscience and Remote Sensing Symposium, 2002
    Co-Authors: I J Won, Haoping Huang, S Norton, B Sanfilipo
    Abstract:

    Reducing the false alarm rate is one of the most outstanding problems in clearing landmines. A broadband EMI sensor combined with a spectral matching method, known as Electromagnetic Induction Spectroscopy (EMIS), has shown great potential to address this complex problem. The common EMIS discrimination approach is to match the spectrum of an unknown target to a library of known spectra. A broadband EM sensor works like a metal detector, but it can operate at multiple programmable frequencies suitable to a given geologic environment. Once it detects a potential target, the sensor will interrogate the target and measure its spectral responses over the entire operating bandwidth. The sensor will then compare the measured spectrum with a library of spectra stored for mines that are known or presumed to occur in the area. The process will generate a rank-ordered list of spectral matches. We have developed and field-tested several spectral matching algorithms for detecting and identifying buried landmines. Recent EMIS test surveys at a controlled military site have produced a high detection rate at a very low false alarm rate. This paper will present results from the surveys including the spectral matching algorithms employed for the identification process.

  • identification of buried unexploded ordnance from broadband Electromagnetic Induction data
    IEEE Transactions on Geoscience and Remote Sensing, 2001
    Co-Authors: S J Norton, I J Won
    Abstract:

    A procedure is described for computing range and orientation invariant spectral signatures of buried unexploded ordnance (UXO) from Electromagnetic Induction (EMI) data. The normalized eigenvalues of the magnetic polarizability tensor that characterizes the target response are used as the orientation-invariant spectral signatures. It is shown that the eigenvalues can be normalized with respect to depth under the assumption that a multiplicative scale factor can be applied at all frequencies. The eigenvalues are derived by measuring the matrix elements of the polarizability tensor from above-ground spatial data and then by diagonalizing this matrix. This method is linear, and does not require a nonlinear parameter search. After normalizing for depth, the eigenvalues derived from an unknown object can then be compared with library eigenvalues using the L2 norm as a goodness-of-fit measure. The procedure is demonstrated using data obtained from cylinders and UXO at different orientations.

  • Electromagnetic Induction spectroscopy
    International Conference on Multimedia Information Networking and Security, 1998
    Co-Authors: I J Won, Dean Keiswetter
    Abstract:

    An object, made partly or wholly of metals, has a distinct combination of electrical conductivity, magnetic permeability, and geometrical shape and size. When the object is exposed to a low-frequency Electromagnetic field, it produces a secondary magnetic field. By measuring the secondary field in a broadband spectrum, we obtain a distinct spectral signature that may uniquely identify the object. Based on the response spectrum, we attempt to 'fingerprint' the object. This is the basic concept of Electromagnetic Induction Spectroscopy (EMIS). EMIS technology may be particularly useful for detecting buried landmines and unexploded ordnance. By fully characterizing and identifying an object without excavation. We should be able to reduce significantly the number of false targets. EMIS should be fully applicable to many other problems where target identification and recognition (without intrusive search) are important. For instance, an advanced EMIS device at an airport security gate may be able to recognize a particular weapon by its maker and type.

  • Electromagnetic Induction spectroscopy
    Journal of Environmental and Engineering Geophysics, 1998
    Co-Authors: I J Won, Dean Keiswetter, Elena Novikova
    Abstract:

    An object, made partly or wholly of metals, has a distinct combination of electrical conductivity, magnetic permeability, and geometrical shape and size. When the object is exposed to a low‐frequency Electromagnetic field, it produces a secondary magnetic field. By measuring the broadband spectrum of the secondary field, we obtain a distinct spectral signature that may uniquely identify the object. Based on the response spectrum, we attempt to “fingerprint” the object. This is the basic concept of Electromagnetic Induction Spectroscopy (EMIS).EMIS technology can be particularly useful for detecting buried landmines and unexploded ordnance. By fully characterizing and identifying an object without excavation, we should be able to reduce significantly the number of false targets. EMIS is applicable to many other problems where target identification and recognition (without intrusive search) are important. For instance, an advanced EMIS device at an airport security gate may be able to identify a particular ...

Zhong Li Wang - One of the best experts on this subject based on the ideXlab platform.

  • hybridizing triboelectrification and Electromagnetic Induction effects for high efficient mechanical energy harvesting
    ACS Nano, 2014
    Co-Authors: Ji Yang, Simiao Niu, Zhong Li Wang
    Abstract:

    The recently introduced triboelectric nanogenerator (TENG) and the traditional Electromagnetic Induction generator (EMIG) are coherently integrated in one structure for energy harvesting and vibration sensing/isolation. The suspended structure is based on two oppositely oriented magnets that are enclosed by hollow cubes surrounded with coils, which oscillates in response to external disturbance and harvests mechanical energy simultaneously from triboelectrification and Electromagnetic Induction. It extends the previous definition of hybrid cell to harvest the same type of energy with multiple approaches. Both the sliding-mode TENG and contact-mode TENG can be achieved in the same structure. In order to make the TENG and EMIG work together, transformers are used to match the output impedance between these two power sources with very different characteristics. The maximum output power of 7.7 and 1.9 mW on the same load of 5 kΩ was obtained for the TENG and EMIG, respectively, after impedance matching. Benef...

Ping Wang - One of the best experts on this subject based on the ideXlab platform.

  • experimental investigation of non linear multi stable Electromagnetic Induction energy harvesting mechanism by magnetic levitation oscillation
    Applied Energy, 2018
    Co-Authors: Mingyuan Gao, Yuan Wang, Yifeng Wang, Ping Wang
    Abstract:

    Abstract The objective of this study is to present a multi-stable Electromagnetic-Induction energy harvesting (MEH) system by magnetic levitation oscillation. The MEH system has a non-linear restoring force and a multi-well restoring force potential, offering an improvement upon their linear counterparts by broadening its frequency response. This paper presents the mechanics of the Electromagnetic-Induction MEH system and describes the multi-stable mechanism by magnetic levitation oscillation. Experimental investigations reveal phenomena of dynamical bifurcation, escape from potential wells, high energy orbits, and chaotic oscillation. Two quad-stable and one tri-stable configurations are experimentally achieved and analyzed by means of phase portraits, Poincare section, largest Lyapunov exponent, and bifurcation diagram. Algorithm of stroboscopic illustration of bifurcation diagram is elaborated. The results indicate that the Electromagnetic-Induction MEH system by magnetic levitation oscillation can be utilized to create a multi-well restoring force potential and increase the output current (i.e. electrical load capacity) of energy harvesters.

Zhong Lin Wang - One of the best experts on this subject based on the ideXlab platform.

  • hybridizing triboelectrification and Electromagnetic Induction effects for high efficient mechanical energy harvesting
    ACS Nano, 2014
    Co-Authors: Jin Yang, Simiao Niu, Zhong Lin Wang
    Abstract:

    The recently introduced triboelectric nanogenerator (TENG) and the traditional Electromagnetic Induction generator (EMIG) are coherently integrated in one structure for energy harvesting and vibration sensing/isolation. The suspended structure is based on two oppositely oriented magnets that are enclosed by hollow cubes surrounded with coils, which oscillates in response to external disturbance and harvests mechanical energy simultaneously from triboelectrification and Electromagnetic Induction. It extends the previous definition of hybrid cell to harvest the same type of energy with multiple approaches. Both the sliding-mode TENG and contact-mode TENG can be achieved in the same structure. In order to make the TENG and EMIG work together, transformers are used to match the output impedance between these two power sources with very different characteristics. The maximum output power of 7.7 and 1.9 mW on the same load of 5 kΩ was obtained for the TENG and EMIG, respectively, after impedance matching. Benefiting from the rational design, the output signal from the TENG and the EMIG are in phase. They can be added up directly to get an output voltage of 4.6 V and an output current of 2.2 mA in parallel connection. A power management circuit was connected to the hybrid cell, and a regulated voltage of 3.3 V with constant current was achieved. For the first time, a logic operation was carried out on a half-adder circuit by using the hybrid cell working as both the power source and the input digit signals. We also demonstrated that the hybrid cell can serve as a vibration isolator. Further applications as vibration dampers, triggers, and sensors are all promising.