Showing papers on "Radar published in 2011"
27 May 2011
TL;DR: Approaches to the design of intelligent waveforms, that are suitable for simultaneously performing both data transmission and radar sensing, are proposed, based on classical phase-coded waveforms utilized in wireless communications.
Abstract: Since traditional radar signals are “unintelligent,” regarding the amount of information they convey on the bandwidth they occupy, a joint radar and wireless communication system would constitute a unique platform for future intelligent transportation networks effecting the essential tasks of environmental sensing and the allocation of ad-hoc communication links, in terms of both spectrum efficiency and cost-effectiveness. In this paper, approaches to the design of intelligent waveforms, that are suitable for simultaneously performing both data transmission and radar sensing, are proposed. The approach is based on classical phase-coded waveforms utilized in wireless communications. In particular, requirements that allow for employing such signals for radar measurements with high dynamic range are investigated. Also, a variety of possible radar processing algorithms are discussed. Moreover, the applicability of multiple antenna techniques for direction-of-arrival estimation is considered. In addition to theoretical considerations, the paper presents system simulations and measurement results of complete “RadCom” systems, demonstrating the practical feasibility of integrated communications and radar applications.
897 citations
TL;DR: A summary of the NASA Jet Propulsion Laboratory's 675 GHz imaging radar is presented, with an emphasis on several key design aspects that enable fast, reliable through-clothes imaging of person-borne concealed objects.
Abstract: A summary of the NASA Jet Propulsion Laboratory's 675 GHz imaging radar is presented, with an emphasis on several key design aspects that enable fast, reliable through-clothes imaging of person-borne concealed objects. Using the frequency-modulated continuous-wave (FMCW) radar technique with a nearly 30 GHz bandwidth, sub-centimeter range resolution is achieved. To optimize the radar's range resolution, a reliable software calibration procedure compensates for signal distortion from radar waveform nonlinearities. Low-noise, high dynamic range detection comes from the radar's heterodyne RF architecture, low-noise chirp source, and high-performance 675 GHz transceiver. The radar's optical design permits low-distortion fast beam scanning for single-pixel imaging, and a real-time radar image frame rate of 1 Hz is now possible. Still faster speeds are on the horizon as multi-beam THz transceivers are developed.
695 citations
TL;DR: Detailed comparisons between the RFT and the well-known moving target detection (MTD) method are provided and it is shown that MTD is actually a special case of R FT and RFT is a kind of generalized Doppler filter bank processing for targets with across range unit (ARU) range walk.
Abstract: Based on the coupling relationship among radial velocity, range walk, and Doppler frequency of the moving target's echoes, a novel method is proposed, i.e., Radon-Fourier transform (RFT), to realize the long-time coherent integration for radar target detection. The RFT realizes the echoes spatial-temporal decoupling via joint searching along range and velocity directions, as well as the successive coherent integration via the Doppler filter bank. Besides, four equivalent RFTs are obtained with respect to the different searching parameters. Furthermore, a generalized form of RFT, i.e., generalized Radon-Fourier transform (GRFT), is also defined for target detection with arbitrary parameterized motion. Due to the similarity between the RFT and the well-known moving target detection (MTD) method, this paper provides detailed comparisons between them on five aspects, i.e., coherent integration time, filter bank structure, blind speed response, detection performance, and computational complexity. It is shown that MTD is actually a special case of RFT and RFT is a kind of generalized Doppler filter bank processing for targets with across range unit (ARU) range walk. Finally, numerical experiments are provided to demonstrate the equivalence among four kinds of RFTs. Also, it is shown that the RFT may obtain the coherent integration gain in the different noisy background and the target's blind speed effect may be effectively suppressed. In the meantime, both the weak target detection performance and the radar coverage of high-speed targets may be significantly improved via RFT without change of the radar hardware system.
414 citations
TL;DR: First results on the simultaneous superposition of SatAIS and high-resolution radar images are presented and the velocity of a moving ship is estimated using complex TS-X data.
Abstract: Ship detection is an important application of global monitoring of environment and security. In order to overcome the limitations by other systems, surveillance with satellite synthetic aperture radar (SAR) is used because of its possibility to provide ship detection at high resolution over wide swaths and in all weather conditions. A new X-band radar onboard the TerraSAR-X (TS-X) satellite gives access to spatial resolution as fine as 1 m. In this paper, first results on the combined use of TS-X ship detection, automatic identification system (AIS), and satellite AIS (SatAIS) is presented. The AIS system is an effective terrestrial method for tracking vessels in real time typically up to 40 km off the coast. SatAIS, as a space-based system, allows almost global coverage for monitoring of ships since not all ships operate their AIS and smaller ships are not equipped with AIS. The system is considered to be of cooperative nature. In this paper, the quality of TS-X images with respect to ship detection is evaluated, and a first assessment of its performance for ship detection is given. The velocity of a moving ship is estimated using complex TS-X data. As test cases, images were acquired over the North Sea, Baltic Sea, Atlantic Ocean, and Pacific Ocean in Stripmap mode with a resolution of 3 m at a coverage of 30 km 100 km. Simultaneous information on ship positions was available from TS-X and terrestrial as well as SatAIS. First results on the simultaneous superposition of SatAIS and high-resolution radar images are presented.
405 citations
01 Jan 2011
TL;DR: In this article, through-the-wall radar images are used to detect and detect targets behind walls. But the authors focus on the detection of targets behind the walls and do not consider the detection and identification of targets in front of the walls.
Abstract: Wall Attenuation and Dispersion, A. Hussein Muqaibel, M.A. Alsunaidi, Nuruddeen M. Iya, and A. Safaai-Jazi Antenna Elements, Arrays, and Systems for Through-the-Wall Radar Imaging, A. Hoorfar and A. Fathy Beamforming for Through-the-Wall Radar Imaging, G. Alli and D. DiFilippo Image and Localization of Behind-the-Wall Targets Using Collocated and Distributed Apertures, Y.D. Zhang and A. Hunt Conventional and Emerging Waveforms for Detection and Imaging of Targets behind Walls, F. Ahmad and R.M. Narayanan Inverse Scattering Approaches in Through-the-Wall Imaging, K. Sarabandi, M. Thiel, M. Dehmollaian, R. Solimene, and F. Soldovieri Through-the-Wall Microwave Building Tomography, P.B. Weichman, E.M. Lavely, E.H. Hill III, and P. Zemany Analytical Ray Methods for Through-the-Wall Radar Imaging, R.J. Burkholder, R.J. Marhefka, and J.L. Volakis Synthetic Aperture Radar Techniques for Through-the-Wall Imaging, T. Dogaru and C. Le Impulse SAR and Its Application for Through-the-Wall Detection and Identification of People and Weapons, J.Z. Tatoian Through-the-Wall SAR for Characterization of Building Interior Structure Using Attributed Scattering Center Features, E. Ertin and R.L. Moses Detection Approaches in Through-the-Wall Radar Imaging, C. Debes and A.M. Zoubir Detection of Concealed Targets in Through-the-Wall Imaging, L. Crocco Fast Acquisition and Compressive Sensing Techniques for Through-the-Wall Radar Imaging, M. Amin, Y-S. Yoon, and S. Kassam Radar Micro-Doppler Signatures for Characterization of Human Motion, V.C. Chen, G.E. Smith, K. Woodbridge, and C.J. Baker Index
391 citations
TL;DR: The ASAR & PALSAR sensors provide state vectors and timing with higher absolute accuracy than was previously available, allowing them to directly support accurate tie-point-free geolocation and radiometric normalization of their imagery.
Abstract: Enabling intercomparison of synthetic aperture radar (SAR) imagery acquired from different sensors or acquisition modes requires accurate modeling of not only the geometry of each scene, but also of systematic influences on the radiometry of individual scenes. Terrain variations affect not only the position of a given point on the Earth's surface but also the brightness of the radar return as expressed in radar geometry. Without treatment, the hill-slope modulations of the radiometry threaten to overwhelm weaker thematic land cover induced backscatter differences, and comparison of backscatter from multiple satellites, modes, or tracks loses meaning. The ASAR & PALSAR sensors provide state vectors and timing with higher absolute accuracy than was previously available, allowing them to directly support accurate tie-point-free geolocation and radiometric normalization of their imagery. Given accurate knowledge of the acquisition geometry of a SAR image together with a digital height model (DHM) of the area imaged, radiometric image simulation is applied to estimate the local illuminated area for each point in the image. Ellipsoid-based or sigma naught (σ0) based incident angle approximations that fail to reproduce the effect of topographic variation in their sensor model are contrasted with a new method that integrates terrain variations with the concept of gamma naught (γ0) backscatter, converting directly from beta naught (β0) to a newly introduced terrain-flattened γ0 normalization convention. The interpretability of imagery treated in this manner is improved in comparison to processing based on conventional ellipsoid or local incident angle based σ0 normalization.
344 citations
TL;DR: Results indicate that the algorithm has the potential to obtain better soil-moisture accuracy at a high resolution and show an improvement in root-mean-square error of 0.015-0.02-cm3/cm3 volumetric soil moisture over the minimum performance taken to be retrievals based on radiometer measurements resampled to a finer scale.
Abstract: A robust and simple algorithm is developed to merge L-band radiometer retrievals and L-band radar observations to obtain high-resolution (9-km) soil-moisture estimates from data of the NASA Soil Moisture Active and Passive (SMAP) mission. The algorithm exploits the established accuracy of coarse-scale radiometer soil-moisture retrievals and blends this with the fine-scale spatial heterogeneity detectable by radar observations to produce a high-resolution optimal soil-moisture estimate at 9 km. The capability of the algorithm is demonstrated by implementing the approach using the airborne Passive and Active L-band System (PALS) instrument data set from Soil Moisture Experiments 2002 (SMEX02) and a four-month synthetic data set in an Observation System Simulation Experiment (OSSE) framework. The results indicate that the algorithm has the potential to obtain better soil-moisture accuracy at a high resolution and show an improvement in root-mean-square error of 0.015-0.02-cm3/cm3 volumetric soil moisture over the minimum performance taken to be retrievals based on radiometer measurements resampled to a finer scale. These results are based on PALS data from SMEX02 and a four-month OSSE data set and need to be further confirmed for different hydroclimatic regions using airborne data sets from prelaunch calibration/validation field campaigns of the SMAP mission.
270 citations
TL;DR: The software, called GMTSAR, is an open-source (GNU General Public License) InSAR processing system designed for users familiar with Generic Mapping Tools and requires installation of GMT and Network Common Data Format and supports several fast Fourier transform libraries.
Abstract: [1] Over the past 15 years, software for processing interferometric synthetic aperture radar (InSAR) data into maps of surface deformation has been developed and refined. The InSAR technique is commonly used to investigate deformation associated with earthquakes, volcanoes, withdrawal of crustal fluids, and coherent ice motions [Massonnet and Feigl, 1998]. The software, called Generic Mapping Tools Synthetic Aperture Radar (GMTSAR), is an open-source (GNU General Public License) InSAR processing system designed for users familiar with Generic Mapping Tools (GMT) [Wessel and Smith, 1998]. The GMTSAR code is written in the C programing language and will run on any UNIX® computer. It requires installation of GMT and Network Common Data Format (NetCDF) and supports several fast Fourier transform libraries.
269 citations
TL;DR: This paper compares SLIM, through imaging examples and examination of computational complexity, to several well-known sparse methods, including the widely used CoSaMP approach, and shows that SLIM provides superior performance for sparse MIMO radar imaging applications at a low computational cost.
Abstract: Through waveform diversity, multiple-input multiple-output (MIMO) radar can provide higher resolution, improved sensitivity, and increased parameter identifiability compared to more traditional phased-array radar schemes. Existing methods for target estimation, however, often fail to provide accurate MIMO angle-range-Doppler images when there are only a few data snapshots available. Sparse signal recovery algorithms, including many l1-norm based approaches, can offer improved estimation in that case. In this paper, we present a regularized minimization approach to sparse signal recovery. Sparse learning via iterative minimization (SLIM) follows an lq-norm constraint (for 0 <; q ≤ 1), and can thus be used to provide more accurate estimates compared to the l1-norm based approaches. We herein compare SLIM, through imaging examples and examination of computational complexity, to several well-known sparse methods, including the widely used CoSaMP approach. We show that SLIM provides superior performance for sparse MIMO radar imaging applications at a low computational cost. Furthermore, we will show that the user parameter q can be automatically determined by incorporating the Bayesian information criterion.
259 citations
TL;DR: Migrant moths have been shown to employ sophisticated orientation and height-selection strategies that maximize displacements in seasonally appropriate directions; they appear to have an internal compass and to respond to turbulence features in the airflow.
Abstract: Radar has been used to study insects in flight for over 40 years and has helped to establish the ubiquity of several migration phenomena: dawn, morning, and dusk takeoffs; approximate downwind transport; concentration at wind convergences; layers in stable nighttime atmospheres; and nocturnal common orientation. Two novel radar designs introduced in the late 1990s have significantly enhanced observing capabilities. Radar-based research now encompasses foraging as well as migration and is increasingly focused on flight behavior and the environmental cues influencing it. Migrant moths have been shown to employ sophisticated orientation and height-selection strategies that maximize displacements in seasonally appropriate directions; they appear to have an internal compass and to respond to turbulence features in the airflow. Tracks of foraging insects demonstrate compensation for wind drift and use of optimal search paths to locate resources. Further improvements to observing capabilities, and employment in operational as well as research roles, appear feasible.
257 citations
TL;DR: The experimental evidence that radio techniques can be used for synthesizing and analyzing non-integer electromagnetic (EM) orbital angular momentum (OAM) of radiation is presented in this article.
Abstract: The experimental evidence that radio techniques can be used for synthesizing and analyzing non-integer electromagnetic (EM) orbital angular momentum (OAM) of radiation is presented. The technique used amounts to sample, in space and time, the EM field vectors and digitally processing the data to calculate the vortex structure, the spatial phase distribution, and the OAM spectrum of the radiation. The experimental verification that OAM-carrying beams can be readily generated and exploited by using radio techniques paves the way to an entirely new paradigm of radar and radio communication protocols.
TL;DR: It is shown that uniform or equal power allocation is not necessarily optimal and that the proposed power allocation algorithms result in local optima that provide either better localization MSE for the same power budget, or require less power to establish the same performance in terms of estimation MSE.
Abstract: Widely distributed multiple radar architectures offer parameter estimation improvement for target localization. For a large number of radars, the achievable localization minimum estimation mean-square error (MSE), with full resource allocation, may extend beyond the predetermined system performance goals. In this paper, performance driven resource allocation schemes for multiple radar systems are proposed. All available antennas are used in the localization process. For a predefined estimation MSE threshold, the total transmitted energy is minimized such that the performance objective is met, while keeping the transmitted power at each station within an acceptable range. For a given total power budget, the attainable localization MSE is minimized by optimizing power allocation among the transmit radars. The Cramer-Rao bound (CRB) is used as an optimization metric for the estimation MSE. The resulting nonconvex optimization problems are solved through relaxation and domain decomposition methods, supporting both central processing at the fusion center and distributed processing. It is shown that uniform or equal power allocation is not necessarily optimal and that the proposed power allocation algorithms result in local optima that provide either better localization MSE for the same power budget, or require less power to establish the same performance in terms of estimation MSE. A physical interpretation of these conclusions is offered.
TL;DR: Unlike previously reported MIMO radar ESPRIT/PARAFAC-based direction finding techniques, this method achieves the rotational invariance property in a different manner combined also with the transmit energy focusing and achieves better estimation performance at lower computational cost.
Abstract: In this paper, we propose a transmit beamspace energy focusing technique for multiple-input multiple-output (MIMO) radar with application to direction finding for multiple targets. The general angular directions of the targets are assumed to be located within a certain spatial sector. We focus the energy of multiple (two or more) transmitted orthogonal waveforms within that spatial sector using transmit beamformers which are designed to improve the signal-to-noise ratio (SNR) gain at each receive antenna. The subspace decomposition-based techniques such as MUSIC can then be used for direction finding for multiple targets. Moreover, the transmit beamformers can be designed so that matched-filtering the received data to the waveforms yields multiple (two or more) data sets with rotational invariance property that allows applying search-free direction finding techniques such as ESPRIT or parallel factor analysis (PARAFAC). Unlike previously reported MIMO radar ESPRIT/PARAFAC-based direction finding techniques, our method achieves the rotational invariance property in a different manner combined also with the transmit energy focusing. As a result, it achieves better estimation performance at lower computational cost. The corresponding Cramer-Rao bound is derived and its dependence on the number of waveforms used is discussed. Simulation results also show the superiority of the proposed technique over the existing techniques.
BMW1
TL;DR: In this paper, the authors provide an overview on the different physical principles responsible for laser radar signal disturbance and theoretical investigations for estimation of their influence, which are applied for signal generation in a newly developed laser radar target simulator providing the worldwide first HIL test capability for automotive laser radar systems.
Abstract: . Laser radar (lidar) sensors provide outstanding angular resolution along with highly accurate range measurements and thus they were proposed as a part of a high performance perception system for advanced driver assistant functions. Based on optical signal transmission and reception, laser radar systems are influenced by weather phenomena. This work provides an overview on the different physical principles responsible for laser radar signal disturbance and theoretical investigations for estimation of their influence. Finally, the transmission models are applied for signal generation in a newly developed laser radar target simulator providing – to our knowledge – worldwide first HIL test capability for automotive laser radar systems.
TL;DR: In this article, the authors used forest inventory plots in old growth, secondary succession, and forest plantations at the La Selva Biological Station in Costa Rica to examine the spatial variability of tropical forest structure and its impact on the L-band and P-band polarimetric radar estimation of AGB at multiple spatial scales.
TL;DR: This investigation demonstrates the feasibility and the utility of a combined use of an electromagnetic scattering model and an advanced image processing technique for inundation monitoring.
09 May 2011
TL;DR: Methods for automatically mapping the three dimensional positions of traffic lights and robustly detecting traffic light state onboard cars with cameras are presented.
Abstract: The outdoor perception problem is a major challenge for driver-assistance and autonomous vehicle systems. While these systems can often employ active sensors such as sonar, radar, and lidar to perceive their surroundings, the state of standard traffic lights can only be perceived visually. By using a prior map, a perception system can anticipate and predict the locations of traffic lights and improve detection of the light state. The prior map also encodes the control semantics of the individual lights. This paper presents methods for automatically mapping the three dimensional positions of traffic lights and robustly detecting traffic light state onboard cars with cameras. We have used these methods to map more than four thousand traffic lights, and to perform onboard traffic light detection for thousands of drives through intersections.
TL;DR: An algorithm developed to map flooded areas from synthetic aperture radar imagery is presented and is conceived to be inserted in the operational flood management system of the Italian Civil Protection and can be used in an almost automatic mode or in an interactive mode, depending on the user's needs.
Abstract: . An algorithm developed to map flooded areas from synthetic aperture radar imagery is presented in this paper. It is conceived to be inserted in the operational flood management system of the Italian Civil Protection and can be used in an almost automatic mode or in an interactive mode, depending on the user's needs. The approach is based on the fuzzy logic that is used to integrate theoretical knowledge about the radar return from inundated areas taken into account by means of three electromagnetic scattering models, with simple hydraulic considerations and contextual information. This integration aims at allowing a user to cope with situations, such as the presence of vegetation in the flooded area, in which inundation mapping from satellite radars represents a difficult task. The algorithm is designed to work with radar data at L, C, and X frequency bands and employs also ancillary data, such as a land cover map and a digital elevation model. The flood mapping procedure is tested on an inundation that occurred in Albania on January 2010 using COSMO-SkyMed very high resolution X-band SAR data.
TL;DR: This paper reports on experiments to measure large-scale Earth surface displacements, such as those caused by solid Earth tides, with centimeter-level accuracy using TerraSAR-X radar images and shows the best ranging accuracies so far reported for spaceborne radar amplitude images.
Abstract: In this paper, we report on experiments to measure large-scale Earth surface displacements, such as those caused by solid Earth tides, with centimeter-level accuracy using TerraSAR-X radar images. With two totally different approaches, corner reflectors and image correlation techniques, we show the clear interrelation between the radar range measurements and the projection of the solid Earth tide motion vector onto the radar line of sight. Pixel location accuracies of up to 2.6-cm standard deviation can be achieved after a single calibration. We further demonstrate that solid Earth tides and tropospheric water vapor variations are the largest sources of ranging error if not compensated for. Alternatively, tropospheric water vapor can be estimated with centimeter accuracy using our proposed technique of synthetic aperture radar (SAR) image correlation and solid Earth motion compensation by the existing models. We also consider ionospheric delays which improve the results marginally in the X-band. Our results show the best ranging accuracies so far reported for spaceborne radar amplitude images and make TerraSAR-X-together with our simple compensation methodology-suitable for the imaging of centimeter-level Earth displacements. Absolute measurements of volcanoes or glaciers are possible without the use of ground equipment and without the use of SAR interferometry, thus avoiding the associated problems of phase ambiguity, phase unwrapping, and reference points.
TL;DR: An in-orbit demonstration mission that would prove the expected altimetric accuracy suited for mesoscale ocean science is proposed, and an instrument specially conceived to fully exploit the GNSS signals for best altIMetric performance and to provide multifrequency observations to correct for the ionospheric delay is described.
Abstract: Mesoscale ocean altimetry remains a challenge in satellite remote sensing. Conventional nadir-looking radar altimeters can make observations only along the satellite ground track, and many of them are needed to sample the sea surface at the required spatial and temporal resolutions. The Passive Reflectometry and Interferometry System (PARIS) using Global Navigation Satellite Systems (GNSS) reflected signals was proposed as a means to perform ocean altimetry along several tracks simultaneously spread over a wide swath. The bandwidth limitation of the GNSS signals and the large ionospheric delay at L-band are however issues which deserve careful attention in the design and performance of a PARIS ocean altimeter. This paper describes such an instrument specially conceived to fully exploit the GNSS signals for best altimetric performance and to provide multifrequency observations to correct for the ionospheric delay. Furthermore, an in-orbit demonstration mission that would prove the expected altimetric accuracy suited for mesoscale ocean science is proposed.
TL;DR: This paper presents a GNSS-R technique, based on Global Positioning System measurements, that allows the retrieval of several geophysical parameters from land surfaces, and presents the results obtained after applying the Interference Pattern Technique (IPT).
Abstract: In the past years, the scientific community has placed a special interest in remotely sensing soil moisture and vegetation parameters. Radiometry and radar techniques have been widely used for years. Global Navigation Satellite Systems opportunity signals Reflected (GNSS-R) over the earth's surface are younger, but they have already shown their potential to perform these observations. This paper presents a GNSS-R technique, based on Global Positioning System (GPS) measurements, that allows the retrieval of several geophysical parameters from land surfaces. This technique measures the power of the interference signal between the direct GPS signal and the reflected one after scattering over the land, so it is called Interference Pattern Technique (IPT). This paper presents the results obtained after applying the IPT for topography, soil moisture, and vegetation height retrievals over vegetation-covered soils.
TL;DR: In this article, a 50-member ensemble was produced by randomly perturbing base-state wind profiles and by regularly adding random local perturbations to the horizontal wind, temperature, and water vapor fields in and near observed precipitation.
Abstract: Ensemble Kalman filter (EnKF) techniques have been proposed for obtaining atmospheric state estimates on the scale of individual convective storms from radar and other observations, but tests of these methods with observations of real convective storms are still very limited. In the current study, radar observations of the 8 May 2003 Oklahoma City tornadic supercell thunderstorm were assimilated into the National Severe Storms Laboratory (NSSL) Collaborative Model for Multiscale Atmospheric Simulation (NCOMMAS) with an EnKF method. The cloud model employed 1-km horizontal grid spacing, a single-moment bulk precipitation-microphysics scheme, and a base state initialized with sounding data. A 50-member ensemble was produced by randomly perturbing base-state wind profiles and by regularly adding random local perturbations to the horizontal wind, temperature, and water vapor fields in and near observed precipitation. In a reference experiment, only Doppler-velocity observations were assimilated into ...
TL;DR: This work develops methods for detecting a moving target in the presence of multipath reflections, which exist, for example, in urban environments, and proposes an algorithm to optimally design the parameters of the OFDM transmitting waveform for the next coherent processing interval.
Abstract: We develop methods for detecting a moving target in the presence of multipath reflections, which exist, for example, in urban environments. We take advantage of the multipath propagation that increases the spatial diversity of the radar system and provides different Doppler shifts over different paths. We employ a broadband orthogonal frequency division multiplexing (OFDM) signal to increase the frequency diversity of the system as different scattering centers of a target resonate variably at different frequencies. To overcome the peak-to-average power ratio (PAPR) problem of the conventional OFDM, we also use constant-envelope OFDM (CE-OFDM) signaling scheme. First, we consider a simple scenario in which the radar receives only a finite number of specularly reflected multipath signals. We develop parametric measurement models, for both the OFDM and CE-OFDM signaling methods, under the generalized multivariate analysis of variance (GMANOVA) framework and employ the generalized likelihood ratio (GLR) tests to decide about the presence of a target in a particular range cell. Then, we propose an algorithm to optimally design the parameters of the OFDM transmitting waveform for the next coherent processing interval. In addition, we extend our models to study the aspects of temporal correlations in the measurement noise. We provide a few numerical examples to illustrate the performance characteristics of the proposed detectors and demonstrate the achieved performance improvement due to adaptive OFDM waveform design.
TL;DR: In this paper, the authors present an approach that combines sparse ice thickness data collected by airborne radar sounding profilers with high resolution swath mapping of ice velocity derived from satellite synthetic-aperture interferometry to obtain a high resolution map of ice thickness that conserves mass and minimizes the departure from observations.
Abstract: The traditional method for interpolating ice thickness data from airborne radar sounding surveys onto regular grids is to employ geostatistical techniques such as kriging. While this approach provides continuous maps of ice thickness, it generates products that are not consistent with ice flow dynamics and are impractical for high resolution ice flow simulations. Here, we present a novel approach that combines sparse ice thickness data collected by airborne radar sounding profilers with high resolution swath mapping of ice velocity derived from satellite synthetic-aperture interferometry to obtain a high resolution map of ice thickness that conserves mass and minimizes the departure from observations. We apply this approach to the case of Nioghalvfjerdsfjorden (79North) Glacier, a major outlet glacier in northeast Greenland that has been relatively stable in recent decades. The results show that our mass conserving method removes the anomalies in mass flux divergence, yields interpolated data that are within about 5% of the original data, and produces thickness maps that are directly usable in high spatial-resolution, high-order ice flow models. We discuss the application of this method to the broad and detailed radar surveys of ice sheet and glacier thickness. Copyright 2011 by the American Geophysical Union.
TL;DR: It is shown that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar, and can be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which enables the mapping and continuous monitoring of bird migration flyways.
Abstract: A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which—when extended to multiple radars—enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe.
TL;DR: In this paper, a new rainfall algorithm is developed using hydrometeor identification (HID) to guide the choice of the particular rainfall estimation algorithm, which can better account for the presence of ice in the sampling volume.
Abstract: The efficacy of dual-polarization radar for quantitative precipitation estimation (QPE) has been demonstrated in a number of previous studies. Specifically, rainfall retrievals using combinations of reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) have advantages over traditional Z‐R methods because more information about the drop size distribution (DSD) and hydrometeor type are available. In addition, dual-polarization-based rain-rate estimators can better account for the presence of ice in the sampling volume. An important issue in dual-polarization rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? AtColoradoStateUniversity(CSU),anoptimizationalgorithmhasbeendevelopedandusedforanumberof years to estimate rainfall based on thresholds of Zh, Zdr, and Kdp. Although the algorithm has demonstrated robust performance in both tropical and midlatitude environments, results have shown that the retrieval is sensitive to the selection of the fixed thresholds. In this study, a new rainfall algorithm is developed using hydrometeor identification (HID) to guide the choice of the particular rainfall estimation algorithm. A separate HID algorithm has been developed primarily to guide the rainfall application with the hydrometeor classes, namely, all rain, mixed precipitation, and all ice. Both the data collected from the S-band Colorado State University‐University of Chicago‐Illinois State Water Survey (CSU‐CHILL) radar and a network of rain gauges are used to evaluate the performance of the new algorithm in mixed rain and hail in Colorado. The evaluation is also performed using an algorithm similar to the one developed for the Joint Polarization Experiment (JPOLE). Results show that the new CSU HID-based algorithm provides good performance for the Colorado case studies presented here.
Book•
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08 Nov 2011
TL;DR: This book offers a concise review of quantum radar theory, making emphasis on the physics behind the operation of a hypothetical quantum radar, and focuses on the two major models proposed to date: interferometric quantum radar and quantum illumination.
Abstract: This book offers a concise review of quantum radar theory. Our approach is pedagogical, making emphasis on the physics behind the operation of a hypothetical quantum radar. We concentrate our discussion on the two major models proposed to date: interferometric quantum radar and quantum illumination. In addition, this book offers some new results, including an analytical study of quantum interferometry in the X-band radar region with a variety of atmospheric conditions, a derivation of a quantum radar equation, and a discussion of quantum radar jamming. This book assumes the reader is familiar with the basic principles of non-relativistic quantum mechanics, special relativity, and classical electrodynamics. Our discussion of quantum electrodynamics and its application to quantum radar is brief, but all the relevant equations are presented in the text. In addition, the reader is not required to have any specialized knowledge on classical radar theory. Table of Contents: Introduction / The Photon / Photon Scattering / Classical Radar Theory / Quantum Radar Theory / Quantum Radar Cross Section / Conclusions
TL;DR: The field operational tests demonstrate that the UWB radar sensor detects the respiratory rate of person under test associated with sub-centimeter chest movements, allowing the continuous-time non-invasive monitoring of hospital patients and other people at risk of obstructive apneas such as babies in cot beds, or other respiratory diseases.
Abstract: An ultra wideband (UWB) system-on-chip radar sensor for respiratory rate monitoring has been realized in 90 nm CMOS technology and characterized experimentally. The radar testchip has been applied to the contactless detection of the respiration activity of adult and baby. The field operational tests demonstrate that the UWB radar sensor detects the respiratory rate of person under test (adult and baby) associated with sub-centimeter chest movements, allowing the continuous-time non-invasive monitoring of hospital patients and other people at risk of obstructive apneas such as babies in cot beds, or other respiratory diseases.
TL;DR: In this article, a stepwise regression was used to select the height indices rh50 and rh75 of the LVIS data for predicting field measured biomass with a R(exp 2) of 0.63-0.71 and RMSE of 31.33 Mg/ha.
TL;DR: A generalized-likelihood ratio test (GLRT) for moving target detection in distributed MIMO radar is developed and shown to be a constant false alarm rate (CFAR) detector and the test statistic is a central and noncentral Beta variable under the null and alternative hypotheses, respectively.
Abstract: In this paper, we consider moving target detection using a distributed multiple-input multiple-output (MIMO) radar on stationary platforms in nonhomogeneous clutter environments. Our study is motivated by the fact that the multistatic transmit-receive configuration in a distributed MIMO radar causes nonstationary clutter. Specifically, the clutter power for the same test cell may vary significantly from one transmit-receive pair to another, due to azimuth-selective backscattering of the clutter. To account for these issues, a new nonhomogeneous clutter model, where the clutter resides in a low-rank subspace with different subspace coefficients (and hence different clutter power) for different transmit-receive pair, is introduced and the relation to a general clutter model is discussed. Following the proposed clutter model, we develop a generalized-likelihood ratio test (GLRT) for moving target detection in distributed MIMO radar. The GLRT is shown to be a constant false alarm rate (CFAR) detector, and the test statistic is a central and noncentral Beta variable under the null and alternative hypotheses, respectively. Simulations are provided to demonstrate the performance of the proposed GLRT in comparison with several existing techniques.