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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.
2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting
The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science
The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.
2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.
The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.
The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.
Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.
IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), 2011
In this paper, the design, analysis and test results of a 24 GHz FMCW radar for small RCS target detection under the ground clutter environment are presented. The radar system is composed of a 24 GHz FMCW radar transceiver, a microcontroller unit (MCU) and a signal processing PC server. We designed a VCO based FMCW radar controlled by the MCU ...
Radio Science, 2018
Atmospheric radars have the ability to continuously observe the height profiles of wind velocity vectors, across a wide height range, with high temporal resolution. They have been used for research, such as atmospheric gravity waves and meteorological phenomena, as well as for weather forecasting. For atmospheric radars, strong clutter echoes from surrounding hard targets, such as mountains or buildings, are ...
IET Radar, Sonar & Navigation, 2008
The superiority of multiple-input multiple-output (MIMO) radars over conventional phased-array radars has been recently shown in many aspects. The MIMO radars have better detection performance and can extract target information more precisely than phased-array radars. The problem of adaptive target detection using temporal coherent pulse train in the presence of nonhomogeneous clutter (different clutter statistics in receivers) is considered for ...
Radio Science, 2005
The generation of a posteriori distribution of a statistic of propagation loss conditioned on observed radar sea clutter is described. The statistic u is the 20th percentile level of the two-way propagation loss at a 5-m height over the 10–60 km range interval. A discrete implementation of the Bayesian paradigm is employed. The forward mapping from the space of environmental ...
IEEE Geoscience and Remote Sensing Letters, None
In this letter, we focus on the statistical modeling of sea clutter amplitudes. Due to its non-Gaussian nature, the existing statistical models are sometimes difficult to represent well the heavy-tailed portion of amplitude distribution. To address this problem, we propose a compound Gaussian (CG) model with a generalized inverse Gaussian (GIG) texture to describe sea clutter amplitudes. In this regard, ...
Richard Klemm - IEEE Dennis J. Picard Medal for Radar Technologies and Applications, 2019 IEEE Honors Ceremony
8-Element, 1-3GHz Direct Space-to-Information Converter - Matthew Bajor - RFIC Showcase 2018
2011 IEEE Dennis J. Picard Medal for Radar Technologies and Applications - James M. Headrick
Micro-Apps 2013: Rapid Simulation of Large Phased Array T/R Module Networks
ICASSP 2010 - Radar Imaging of Building Interiors
Micro-Apps 2013: Creating and Analyzing Multi-Emitter Environment Test Signals with COTS Equipment
In this paper, the design, analysis and test results of a 24 GHz FMCW radar for small RCS target detection under the ground clutter environment are presented. The radar system is composed of a 24 GHz FMCW radar transceiver, a microcontroller unit (MCU) and a signal processing PC server. We designed a VCO based FMCW radar controlled by the MCU to be cost effective system. The 24 GHz of ISM band was divided into 3 different channels (BW = 75 MHz) to avoid interference at the same site. In signal processing part, four algorithms (Averaging, Correlation 1, Correlation 2, Ordering & Selection) were compared and weighting function of standard deviation was used to increase small RCS target detection probability. Experimental results show that the proposed system can detect small RCS of human targets (RCS ≈ 0.5 m2) up to 100 m.
Atmospheric radars have the ability to continuously observe the height profiles of wind velocity vectors, across a wide height range, with high temporal resolution. They have been used for research, such as atmospheric gravity waves and meteorological phenomena, as well as for weather forecasting. For atmospheric radars, strong clutter echoes from surrounding hard targets, such as mountains or buildings, are the major source of interference. As they utilize very weak scattering from radio refractive index fluctuations produced by atmospheric turbulence, even weak echoes from low- level sidelobes become a serious problem. In order to reject or suppress clutter echoes, it is effective to use the norm constrained-directionally constrained minimization of power (NC-DCMP) method, which creates a null toward the direction of the clutter, while maintaining the main lobe shape. We successfully implemented the NC-DCMP adaptive processing in the real-time processing system of the middle and upper atmosphere radar. This study demonstrates the effectiveness of real-time processing of the clutter rejection. The primary advantage is enabling the estimation of wind velocity profiles in real time and the reduction of the amount of recorded data. The improvement of the wind estimation accuracy, especially for vertical flow, was confirmed from observation data recorded over a long period.
The superiority of multiple-input multiple-output (MIMO) radars over conventional phased-array radars has been recently shown in many aspects. The MIMO radars have better detection performance and can extract target information more precisely than phased-array radars. The problem of adaptive target detection using temporal coherent pulse train in the presence of nonhomogeneous clutter (different clutter statistics in receivers) is considered for MIMO radars. This problem has been formulated as a hypothesis test. For clutter with unknown statistics three adaptive decision rules have been developed using the generalised likelihood ratio test. The results show the superiority of the MIMO radars with temporal coherent processing over conventional phased arrays in the presence of clutter.
The generation of a posteriori distribution of a statistic of propagation loss conditioned on observed radar sea clutter is described. The statistic u is the 20th percentile level of the two-way propagation loss at a 5-m height over the 10–60 km range interval. A discrete implementation of the Bayesian paradigm is employed. The forward mapping from the space of environmental parameters into the space of radar clutter incorporates a random process model such that many realizations of modeled clutter are generated for each environmental refractivity parameter combination. The algorithm is adjusted such that over a series of simulated inversion runs, it is seen that for intervals between percentile levels (e.g., between the 20th and 80th percentile levels), a posteriori distributions of u contain the ground truth values of u the correct percentage of the time (60% for the used interval). For real data cases, it is observed that the a posteriori distributions are too narrow. The inversion algorithm is used to examine the behavior of the a posteriori distribution as the noise floor is raised. An abrupt reduction in the information obtained from the clutter (indicated by a widening of the a posteriori distribution) occurs when peak clutter levels over the ranges of 25–50 km drop below about 15 dB for both simulated and real data cases.
In this letter, we focus on the statistical modeling of sea clutter amplitudes. Due to its non-Gaussian nature, the existing statistical models are sometimes difficult to represent well the heavy-tailed portion of amplitude distribution. To address this problem, we propose a compound Gaussian (CG) model with a generalized inverse Gaussian (GIG) texture to describe sea clutter amplitudes. In this regard, the probability density function and the cumulative distribution function of the clutter amplitudes for the proposed model are derived. Moreover, we provide an approach to estimate the unknown parameters of the proposed CG-GIG distribution. The experimental results indicate that the CG-GIG distribution is more suitable to describe the amplitudes of non-Gaussian sea clutter than its competitors.
Opportunistic array radar is a new radar system that can improve the modern radar performance effectively. In order to improve its radio frequency stealth ability, a novel coordination method of opportunistic array radars in the network for target tracking in clutter is presented. First, the database of radar cross section for targets is built, then the signal-to-noise ratio for netted radars is computed according to the radar cross section and range of target. Then the joint probabilistic data association algorithm of tracking is improved with consideration of emitted power of the opportunistic array radar, which has a main impact on detection probability for tracking in clutter. Finally, with the help of grey relational grade and covariance control, the opportunistic array radar with the minimum radiated power will be selected for better radio frequency stealth performance. Simulation results show that the proposed algorithm not only has excellent tracking accuracy in clutter but also saves much more radiated power comparing with other methods.
In this letter, we consider the varying detection environments to address the problem of detecting small targets within sea clutter. We first extract three simple yet practically discriminative features from the returned signals in the time and frequency domains and then fuse them into a 3-D feature space. Based on the constructed space, we then adopt and elegantly modify the support vector machine to design a learning-based detector that enfolds the false alarm rate (FAR). Most importantly, our proposed detector can flexibly control the FAR by simply adjusting two introduced parameters, which facilitates to regulate detector's sensitivity to the outliers incurred by the sea spikes and to fairly evaluate the performance of different detection algorithms. Experimental results demonstrate that our proposed detector significantly improves the detection probability over several existing classical detectors in both low signal to clutter ratio (up to 58%) and low FAR (up to 40%) cases.
Analyzing the statistical property of polarization ratio of radar sea clutter provides a reference for radar detection. In this paper, statistical distributions of the amplitude and phase of polarization ratio for radar sea clutter are analyzed. The sea clutter amplitude distributions in horizontal and vertical polarization channels are analyzed with real sea clutter data at first. Based on this, statistical distributions of the amplitude of the polarization ratio are derived. Analysis results of real sea clutter data are coincident with the theoretical derivation of the distribution of polarization ratio amplitude for sea clutter and show that the distribution of polarization ratio phase approximates to Gaussian distribution.
This paper describes estimation of low-altitude atmospheric refractivity from radar sea clutter observations. The vertical structure of the refractive environment is modeled using five parameters, and the horizontal structure is modeled using six parameters. The refractivity model is implemented with and without an a priori constraint on the duct strength, as might be derived from soundings or numerical weather-prediction models. An electromagnetic propagation model maps the refractivity structure into a replica field. Replica fields are compared to the observed clutter using a squared-error objective function. A global search for the 11 environmental parameters is performed using genetic algorithms. The inversion algorithm is implemented on S-band radar sea-clutter data from Wallops Island, Virginia. Reference data are from range-dependent refractivity profiles obtained with a helicopter. The inversion is assessed (1) by comparing the propagation predicted from the radar-inferred refractivity profiles and from the helicopter profiles, (2) by comparing the refractivity parameters from the helicopter soundings to those estimated, and (3) by examining the fit between observed clutter and optimal replica field. This technique could provide near-real-time estimation of ducting effects. In practical implementations it is unlikely that range- dependent soundings would be available. A single sounding is used for evaluating the radar-inferred environmental parameters. When the unconstrained environmental model is used, the “refractivity-from-clutter,” the propagation loss generated and the loss from this single sounding, is close within the duct; however, above the duct they differ. Use of the constraint on the duct strength leads to a better match also above the duct.
Refractivity from clutter (RFC) refers to techniques that estimate the atmospheric refractivity profile from radar clutter returns. A RFC algorithm works by finding the environment whose simulated clutter pattern matches the radar measured one. This paper introduces a procedure to compute RFC estimator performance. It addresses the major factors such as the radar parameters, the sea surface characteristics, and the environment (region, time of the day, season) that affect the estimator performance and formalizes an error metric combining all of these. This is important for applications such as calculating the optimal radar parameters, selecting the best RFC inversion algorithm under a set of conditions, and creating a regional performance map of a RFC system. The performance metric is used to compute the RFC performance of a non- Bayesian evaporation duct estimator. A Bayesian estimator that incorporates meteorological statistics in the inversion is introduced and compared to the non-Bayesian estimator. The performance metric is used to determine the optimal radar parameters of the evaporation duct estimator for six scenarios. An evaporation duct inversion performance map for a S band radar is created for the larger Mediterranean/Arabian Sea region.
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