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Drones and drone swarms, characterized by their low price and ease of deployment, are being utilized to launch assaults, and presenting a great threat to the public and homeland security in recent years. Countering drones or drone swarms is thus of great significance. Some effective counter approaches for a small group of drones have been studied. However, these approaches may be insufficient to counter a large-scale drone swarm due to the lack of efficient time-saving detecting technologies. Towards this end, this paper proposes a fast counter approach to deprive the drone swarm of its coordination and clustering capabilities in a short time by splitting the drone swarm into several unconnected components. To achieve efficient splitting, two efficient algorithms for searching critical nodes are proposed, namely, the genetic algorithm and the particle swarm optimization algorithm. Extensive simulation results are presented to validate the superior performances of the proposed two algorithms for splitting the drone swarms in different formations. The results show that the drone swarms lose their coordination ability as they are forced to split into multiple components with a constraint of group size. The high accuracy and efficiency of the proposed algorithms are also verified by a series of comparative experiments. [ABSTRACT FROM AUTHOR]

This article presents detailed geometric analyses of ground clutter in bistatic passive airborne radars. Analytic closed-form solutions are derived for finding the intersection of iso-ranges and iso-velocities. This allows clutter bistatic coordinates to be easily converted to its Cartesian coordinates. Based on those solutions, a theoretical clutter map in the bistatic coordinates can be calculated assuming uniform clutter distribution on the Earth’s surface. This is done by first converting a resolution cell in the bistatic coordinates into a corresponding cell in the Cartesian coordinates. Next, the power distribution in the bistatic coordinates is calculated taking into account range dependency, incident angles, and the radiation patterns of the transmitter and the receiver. The aim of this analysis is to characterize clutter in terms of expected mean power map rather than in terms of statistical distribution. The obtained results provide insights into the expected characteristics of clutter, which can be helpful in designing signal processing algorithms for ground moving target indication (GMTI) and synthetic aperture radar (SAR). The theoretical clutter distribution on the range-velocity map is compared with real-life data acquired with a Digital Video Broadcasting–Terrestrial (DVB-T)-based passive radar and good agreement between theory and measurement is presented. [ABSTRACT FROM AUTHOR]

Ambiguity clutter for airborne radar systems is usually caused by a uniform pulse repetition interval (UPRI) waveform, which significantly degrades target detection and location performance. To address this issue, this article proposes an ambiguity clutter suppression method resorting to a pseudorandom pulse repetition interval (PrPRI) waveform. First, an airborne radar clutter model accounting for multiple range rings with PrPRI waveform is developed. Next, a nonuniform coherent processing framework is introduced to eliminate the clutter folded in the range and Doppler domain. In particular, the reasons for the enlargement of the area free of clutter corresponding to PrPRI mode are analyzed, as well as the maximum unambiguous Doppler frequency, maximum unambiguous range, and design principles for PRI are derived. Finally, numerical examples are designed to verify that the nonuniform coherent processing framework can enlarge the clutter-free area and achieve unambiguity target detection and location. [ABSTRACT FROM AUTHOR]

The signal coherence on target is vulnerable toconfiguration perturbationsof an airborne distributed radar system where radar nominal positions are disturbed by unknown position errors to radar actual positions in three-dimensional space. This article copes with the configuration calibration problem of an airborne distributed radar system using several auxiliary devices in known locations, e.g., ground auxiliary receivers. To warrant parameter identifiability, for given transmitted signals from radars, two types of echoes are exploited, including the internal ones received by radars and external ones received by auxiliary receivers. The range measurements can be extracted from these echoes subsequently. The theoretical analysis claims that an identifiability condition for configuration calibration, precluding pathological configurations, is to have at least two auxiliary receivers when the location of one radar is known. Besides, configuration calibration is a highly nonlinear problem due to the coupling of position errors between two different radars and to the existence of second-order position error terms in the range measurement equations. We introduce the novel idea of auxiliary ranges to eliminate the second-order position error terms and the iterative fashion to handle the coupling in the methodology to enable the formulation of pseudolinear equations, thereby leading to the establishment of an algebraic solution for radar position estimation. Numerical simulations are included to corroborate the theoretical results and to demonstrate the superiority of the devised method in comparison with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Airborne multichannel high-resolution radar (HRR)-ground moving target indication (GMTI) is of great significance to wide-area surveillance, traffic monitoring, and target recognition. The Aerospace Information Research Institute, Chinese Academy of Sciences, produced an advanced airborne digital array radar with high resolution and conducted an experiment with slow and weak cooperative moving targets in 2021. In this article, an overall processing framework for target detection, parameter estimation, and target tracking using this system is introduced. For HRR detection, the echo energy of targets is spread into multiple range units, so-called range-spread targets; thus, using detectors designed for pointlike targets will severely degrade the detection performance, especially for slow and weak targets. To address the adaptive detection of such range-spread targets embedded in Gaussian clutter with an unknown covariance matrix, a novel two-step generalized space–time adaptive processing (GSTAP) algorithm is proposed, which offers an enhanced clutter suppression capability compared with natural competitors. Moreover, a tracking method is implemented in the range-Doppler domain to avoid track loss caused by azimuth relocation error and reject discrete false alarms. Both simulation and experimental results are presented to demonstrate the effectiveness of the proposed method and provide a paradigm for further research. [ABSTRACT FROM AUTHOR]

Frequency diverse array (FDA), which employs a small frequency increment across its array elements to generate controllable degrees-of-freedom (DOFs) in range dimension, has attracted extensive attentions in recent years. In order to extract and exploit the DOFs in range and angle dimensions, FDA has been combined with multiple-input multiple-output (MIMO) technique, which shows sufficient performance improvement in clutter suppression in scenarios with range ambiguities. Therefore, clutter rank evaluation is an important issue for FDA-MIMO radar mounted on a moving platform. In this article, a clutter rank evaluation criterion is developed with respect to different transmit/receive array configurations and different number of range ambiguities. It is based on a subspace transformation matrix that decouples the clutter subspace and allows a direct determination of clutter rank. With the proposed clutter rank evaluation criterion, the maximum resolvable number of range ambiguities can be determined, which is bounded by the system's DOFs. Three cases according to different relationships between uniform array element spacings are studied. Then, the aforementioned clutter rank evaluation method is extended to nonuniform array configurations. Moreover, the robustness of the method is studied in the presence of gain-phase errors. Several simulation results are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Range-dependent clutter suppression is a challenging problem in nonsidelooking, bistatic, and conformal antenna array airborne radar, especially in the presence of range ambiguity. Superimposed stepped frequency (SSF) radar employs a small frequency increment across the stepped signals in each pulse, which introduces a dimension related to slant range. In this article, an airborne radar framework is established, which takes SSF signal as the transmit waveform. Thus, a two-stage adaptive clutter suppression method is proposed, which utilizes the degrees of freedom in range, space, and time domains provided by airborne SSF radar. In the first stage, the secondary range dependence compensation approach is adopted to distinguish the clutter of each range region in the carrier frequency domain. Then, a target-free covariance matrix is estimated by the compensated data, and the covariance matrix is used for the range-ambiguous clutter separation in the carrier frequency domain. Thus, the space-time snapshot of each range region can be extracted. In the second stage, a clutter segmentation processing method is devised for residual clutter suppression. For the near-range unambiguous clutter, the traditional clutter compensation approach is applied to further align the spectrum distribution of clutter, while the conventional space-time adaptive processing is utilized to suppress far-range clutter directly. Since the proposed method takes full advantage of the range dimension and the two stages of adaptive processing are data-dependent, excellent clutter suppression performance can be obtained. The proposed method can also extract the real range of the target since each range region is processed separately. Simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Observations and analysis from the first airborne deployment of a G-band atmospheric radar, the Jet Propulsion Laboratory’s vapor in-cloud profiling radar (VIPR), are presented with a focus on ocean surface scatterometry and water vapor retrievals using the differential absorption radar (DAR) technique. We assess transceiver cross-calibration stability between the two DAR frequency channels using a combination of ground-based calibration measurements and airborne cloud observations that are validated by independent sensors. By comparing calibrated, unattenuated ocean surface backscatter measurements with existing models, we demonstrate the need for improvements in treating ocean surface scattering at G-band frequencies for future in-flight radar calibration applications. During science-oriented flights off the coast of California, we demonstrate partial column integrated water vapor (IWV) measurement capabilities with 0.3-mm precision in clear sky by performing a descent maneuver over an operational radiosonde (RS) launching site and comparing with the coincident in situ profiles to find a root mean square error (RMSE) of 0.5 mm. Furthermore, we present water vapor profiling and IWV measurements in the presence of clouds and precipitation when flying through a frontal weather system in the vicinity of Bodega Bay. By comparing with coincident RS profiles, we find an RMSE for in-cloud humidity profile retrievals of 1.1 ${\rm gm}^{-3}$ and precision of 0.6 ${\rm gm}^{-3}$ while the IWV retrievals reveal a bias from differential hydrometeor extinction of 5 mm. We provide a critical assessment of cloud-scattering-induced biases in the water vapor retrievals, as well as discuss a potential method for eliminating systematic error from the DAR measurements. [ABSTRACT FROM AUTHOR]

Passive operation is an important operational concept for future airborne radar platforms. Successful target detection requires an understanding of the underlying clutter statistics in order to set the detection threshold accurately. In addition, clutter statistics are important for modeling of passive radar performance and simulation of passive bistatic radar to aid in the development of new target detection algorithms. In this article, the clutter statistics of data from an airborne platform are studied over a range of bistatic geometries and receive polarizations. The illuminator is a digital video broadcast-terrestrial (DVB-T) station and the collected data spans both ground and maritime regions. The key contributions include a study of amplitude statistics using a number of common distributions and understanding the impact of the reference signal quality in terms of the clutter statistics. [ABSTRACT FROM AUTHOR]

Ship tracking facilitates a comprehensive insight into maritime traffic situations and ensures its safety and security. However, with the current operational surveillance systems, detecting several maritime threats is still a major challenge. In this article, we propose a supportive ship tracking concept using an airborne-based radar sensor. The proposed tracking algorithm is suitable for dense multitarget scenarios. Tracking is performed in the range-Doppler domain. The primary advantage of using the range-Doppler domain is that ships even with low radar cross section moving with certain line-of-sight velocity appear out of the clutter region, thus improving their detectability. In addition, a powerful track management system is also developed to handle false targets. The simulated and real experimental results from the DLR’s airborne radar sensors, F-SAR and DBFSAR, are presented to prove the concept. [ABSTRACT FROM AUTHOR]

We present new high-resolution snow depth data on Arctic sea ice derived from airborne microwave radar measurements from the IceBird campaigns of the Alfred Wegener Institute (AWI) together with a new retrieval method using signal peakiness based on an intercomparison exercise of colocated data at different altitudes. We aim to demonstrate the capabilities and potential improvements of radar data, which were acquired at a lower altitude (200 ft) and slower speed (110 kn) and had a smaller radar footprint size (2-m diameter) than previous airborne snow radar data. So far, AWI Snow Radar data have been derived using a 2–18-GHz ultrawideband frequency-modulated continuous-wave (FMCW) radar in 2017–2019. Our results show that our method in combination with thorough calibration through coherent noise removal and system response deconvolution significantly improves the quality of the radar-derived snow depth data. The validation against a 2-D grid of in situ snow depth measurements on level landfast first-year ice indicates a mean bias of only 0.86 cm between radar and ground truth. Comparison between the radar-derived snow depth estimates from different altitudes shows good consistency. We conclude that the AWI Snow Radar aboard the IceBird campaigns is able to measure the snow depth on Arctic sea ice accurately at higher spatial resolution than but consistent with the existing airborne snow radar data of NASA Operation IceBridge. Together with the simultaneous measurements of the total ice thickness and surface freeboard, the IceBird campaign data will be able to describe the whole sea-ice column on regional scales. [ABSTRACT FROM AUTHOR]

Radar specific emitter identification (SEI) is the process of uniquely identifying an individual emitter from the same class of radars by their individual properties that arise from hardware imperfections. However, it is challenging or perhaps impossible to generate globally unique emitter identifiers by using SEI techniques alone, due to the increasing number of radars and the subtle differences in their signal properties. We therefore introduce a multitier radar emitter identification concept that includes radar function identification, model identification, and SEI. The combination of function identifiers, model identifiers, and specific emitter identifiers could generate globally unique radar emitter identifiers. In this article, we propose to use the radio frequency (RF) features extracted from time domain transient signals for radar model identification. The RF features include the duration, maximum derivative, skewness, kurtosis, mean, variance, fractal dimension, Shannon entropy, and polynomial coefficients of the normalized energy trajectory of a transient signal, as well as the area under the trajectory curve. We propose three RF fingerprints for radar model identification, each consisting of a predetermined subset of the features. The performance of the RF fingerprints was evaluated by using five classification algorithms with two radar datasets. Our results show attractive performance with respect to hetero-model radar identification. In particular, for the hetero-model radar dataset, the pair of the all-features (AF) fingerprint and gradient boosting algorithm achieved 91.9, 90.25, and 91.1% classification accuracy for three, four, and five emitters, respectively. On this basis, we conclude that the proposed AF fingerprint could be applied directly to radar model identification by training the gradient boosting algorithm using a dataset with many radars per model. [ABSTRACT FROM AUTHOR]

Generally ground clutter has serious range dependence and range ambiguity in the forward-looking array airborne radar system under a high pulse repetition frequency (PRF) system. In this work, a range ambiguous clutter suppression method based on transmitting beam main lobe correction for the FDA MIMO radar is proposed. Firstly, this method uses the designed transmission pulse weights to compensate for the initial phases formed by the accumulation of frequency increments between pulses, so as to solve the problem that the main lobe high gain illuminated angle is inconsistent between the MIMO equivalent transmitting beampattern pulses synthesized at the receiving in the traditional FDA MIMO system. Secondly, by restoring and compensating received echoes, the influence of the main lobe correction weights of the transmitting signal is eliminated. Finally, through the characteristics of transmitter correction compensation to distinguish different range ambiguous clutters, the echoes from the range ambiguous areas can be discretely distributed in the power spectrum while preserving the signal echoes in the observation area. Thus range ambiguous clutter suppression is realized. The simulation results show that the proposed method can improve the clutter suppression performance compared with the MIMO and linear frequency increment FDA radar. [ABSTRACT FROM AUTHOR]

We propose a lightweight radar that autonomously measures snow depth over sea ice from an unmanned aerial vehicle (UAV). Development of this snow radar and its integration with an octocopter UAV is presented. Field trials of the UAV-mounted snow radar, conducted in Antarctica during the summer season of 2017/2018, are also described. The radar allows measurements of snow depths on sea ice between 10 and 100 cm. Additional reflections due to internal layers within the snow are evident at a few measurement points. The snow radar is evaluated for various flight parameters: stationary; flying at speeds between 1 and 3 m/s, and at heights from 5 to 15 m. Evaluation of snow-depth results indicates that a depth accuracy of ±3.2 cm is achieved with stationary measurements, and of ±9.1 cm with measurements at the various flight speeds. [ABSTRACT FROM AUTHOR]

VIPR (vapor in-cloud profiling radar) is a tunable G-band radar designed for humidity and cloud remote sensing. VIPR uses all-solid-state components and operates in a frequency-modulated continuous-wave (FMCW) radar mode, offering a transmit power of 200–300 mW. Its typical chirp bandwidth of 10 MHz over a center-frequency tuning span of 167–174.8 GHz results in a nominal range resolution of 15 m. The radar’s measured noise figure over the transmit band is between 7.4 and 10.4 dB, depending on its frequency and hardware configuration, and its calculated antenna gain is 58 dB. These parameters mean that with typical 1 ms chirp times, single-pulse cloud reflectivities as low as −26 dBZ are detectable with unity signal-to-noise at 5 km. Experimentally, radar returns from ice clouds above 10 km in height have been observed from the ground. VIPR’s absolute sensitivity was validated using a spherical metal target in the radar antenna’s far-field, and a G-band switch has been implemented in an RF calibration loop for periodic recalibration. The radar achieves high sensitivity with thermal noise limited detection both by virtue of its low-noise RF architecture and by using a quasioptical duplexing method that preserves ultrahigh transmit/receive isolation despite operation in an FMCW mode with a single primary antenna shared by the transmitter and receiver. [ABSTRACT FROM AUTHOR]

We report the analysis of opposite-side ambiguities in single-pass radar sounding interferometry. Nadir pointing radar sounders suffer inherent cross track ambiguities that cannot be separated with the power image alone. Interferometry can be used to interpret these ambiguities when data are collected with multichannel receivers. However, opposite-side surface clutter, volume scattering, and cross track range misalignment create unique interferometric phase and correlation signatures. Such signatures are observed experimentally in data collected by the Polarimetric Airborne Radar Ice Sounder (POLARIS) P-band multichannel radar sounder. We derive analytic expressions to predict the observations and validate them with simulation. In addition, we observe and explain a correlation dropout feature that is due to volume scattering competing with surface clutter in the null of the cross track antenna pattern. The purpose of this article is to explain opposite-side ambiguity signatures in radar sounder interferometry and provide models and techniques for scientific interpretation of interferograms. [ABSTRACT FROM AUTHOR]

For an unmanned aerial vehicle (UAV) carrying out a maritime radar surveillance mission, there is a tradeoff between maximizing information obtained from the search area and minimizing fuel consumption. This article presents an approach for the optimization of a UAV's trajectory for maritime radar wide area persistent surveillance to simultaneously minimize fuel consumption, maximize mean probability of detection, and minimize mean revisit time. Quintic polynomials are used to generate UAV trajectories due to their ability to provide complete and complex solutions while requiring few inputs. Furthermore, the UAV dynamics and surveillance mission requirements are used to ensure that a trajectory is realistic and mission compatible. A wide area search radar model is used within this article in conjunction with a discretized grid in order to determine the search area's mean probability of detection and mean revisit time. The trajectory generation method is then used in conjunction with a multiobjective particle swarm optimization algorithm to obtain a global optimum in terms of path, airspeed (and thus time), and altitude. The performance of the approach is then tested over two common maritime surveillance scenarios and compared to an industry recommended baseline. [ABSTRACT FROM AUTHOR]

Space–time adaptive processing (STAP) of multichannel radar data is an established and powerful method for detecting ground moving targets, as well as for estimating their geographical positions and line-of-sight velocities. Crucial steps for practical applications are: 1) the appropriate and automatic selection of the training data and 2) the periodic update of these data to take into account the change of the clutter statistics over space and time. Improper training data and contamination by moving target signals may result in a decreased clutter suppression performance, an incorrect constant false alarm rate threshold, and target cancelation by self-whitening. In this paper, two conventional and two novel methods for training data selection are evaluated and compared using real four-channel X-band radar data acquired with DLR’s airborne sensor F-SAR. In addition, a module for rejecting potential moving target signals and strong scatterers from the training data is proposed and discussed. All methods are evaluated for a conventional post-Doppler (PD) STAP processor and for a particular PD STAP that uses an a priori known road map. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the direction-of-arrival (DOA) of the ice-sheet data collected over Jakobshavn Glacier with the airborne Multichannel Radar Depth Sounder (MRDS) during the 2006 field season. We extracted weak ice–bed echoes buried in signals scattered by the rough surface of the fast-flowing Jakobshavn Glacier by analyzing the DOA of signals received with a five-element receive-antenna array. This allowed us to obtain ice thickness information, which is a key parameter when generating bed topography of glaciers. We also estimated ice–bed roughness and bed slope from the combined analysis of the DOA and radar waveforms. The bed slope is about 8° and the roughness in terms of rms slope is about 16°. [ABSTRACT FROM PUBLISHER]

Airborne co-polarization and cross-polarization observations of ocean surface normalized radar cross section (NRCS) were conducted over the North Atlantic during January and February 2015. Observations were made using the University of Massachusetts' Imaging Wind and Rain Airborne Profiler (IWRAP) radar system and a prototype antenna for the next-generation European scatterometer aboard MetOp-SG. Both were installed on a National Oceanic and Atmospheric Administration (NOAA) WP-3D research aircraft to characterize the wind response of the ocean-surface cross-polarization NRCS. During the flights, numerous constant-roll-angle circle maneuvers were performed at several different angles to collect NRCS measurements over a range of incidence angles. Surface winds at speeds between 8 and 34 ms−1 were observed at incidence angles from 20° to 60° at all polarization combinations. The majority of measurements fell between 8 and 20 ms−1. Wind-direction dependence similar to copolarized NRCS was observed in the cross-polarized (VH) NRCS. The amplitude of the VH NRCS with respect to direction is less than that of copolarized NRCS at all wind speeds. Incidence angle dependence was also observed in the VH NRCS at all wind speeds. As a function of wind speed, the mean VH NRCS (A0) has a similar shape to the VV NRCS. The VH NRCS appears to not saturate at most incidence angles, unlike the VV and HH NRCS. VH and HH geophysical model functions (GMFs) were developed as functions of wind speed, incidence angle, and wind-relative azimuth for the wind speeds and incidence angles observed. [ABSTRACT FROM AUTHOR]

Radiometric correction of radar images is essential to produce accurate estimates of biophysical parameters related to forest structure and biomass. We present a new algorithm to correct radiometry for 1) terrain topography and 2) variations of canopy reflectivity with viewing and tree-terrain geometry. This algorithm is applicable to radar images spanning a wide range of incidence angles over terrain with significant topography and can also take into account aircraft attitude, antenna steering angle, and target geometry. The approach includes elements of both homomorphic and heteromorphic terrain corrections to correct for topographic effects and is followed by an additional radiometric correction to compensate for variations of canopy reflectivity with viewing and tree-terrain geometry. The latter correction is based on lookup tables and enables derivation of biophysical parameters irrespective of viewing geometry and terrain topography. We evaluate the performance of the new algorithm with airborne radar data and show that it performs better than classical homomorphic methods followed by cosine-based corrections. [ABSTRACT FROM PUBLISHER]

This communication presents the experimental results of a ultrawideband 2–18-GHz dual-polarized Vivaldi antenna array for airborne radar measurements of snow. The antenna design is based on the previously reported all-metal flared-notch array by Kindt and Pickles for operation over the frequency range 0.7–9 GHz. An antenna array prototype consisting of $8 \times 8$ active dual-polarized elements was fabricated with precise aluminum machining and tested in the anechoic chamber. Beamsteering upto 30° was experimental demonstrated from 2 to 18 GHz. The measurement results are in a good agreement with the full-wave simulation results in both polarization configurations. Preliminary sample results from data collected using the Vivaldi array are also presented. The antenna array enables full polarimetric measurements of snow-over-sea-ice for estimating the snow-water-equivalent (SWE), as well as fine-resolution mapping of snow-air and snow-ice interfaces for estimating thickness. [ABSTRACT FROM PUBLISHER]

A polarization-reconfigurable low-profile ultra-wideband VHF/UHF antenna array is presented in this paper. The design is based on resistively loaded planar dipole antenna elements backed with a ground plane. The antenna array has two mechanically field-switchable polarization configurations which are designed to measure the crystal orientation of ice sheets. The nominal operating mode of the array is in the vertically polarized configuration with operating frequency ranges from 150 to 550 MHz. The planar dimension of the array is 3.6\;\textm \times 0.8\;\textm with a ground plane height of 16 cm (0.08\lambda low,{{\text f}low} = 150\,\text{MHz}). Anechoic chamber measurements show that the array performance is in very good agreement with simulated results, for both VSWR and array radiation pattern. It is also shown that the array is capable of handling 1-kW peak power per transmit channel. The antenna array is housed within a flight-qualified composite S2-glass/epoxy fairing and can readily be mounted on airborne platforms, such as Basler BT-67 and Twin Otter, for radar sounding of polar ice sheets and glaciers. [ABSTRACT FROM PUBLISHER]

We describe a lightweight wideband C-band radar sounder, which is designed for use in a small unmanned aerial vehicle, primarily for measuring snow and ice. The waveform used is a gated frequency modulated continuous wave, which enables transmission at low power with relatively high energy in the compressed pulse. Gating allows use of a single antenna, reducing the influence of the direct wave on the systems' dynamic range. The radar operates at 5.3-GHz center frequency and has a bandwidth of 1 GHz, for a nominal range resolution of 15 cm in air or 12 cm in snow. Laboratory testing and airborne acquisition of data over the glacier Hardangerjøkulen show that the radar appears to work well for the intended purpose of measuring snow layer thickness. [ABSTRACT FROM PUBLISHER]

A comparison of model predictions with measurements of near-nadir normalized radar cross sections (NRCSs) of the sea surface at Ku- and Ka-bands is reported. Measurements of Airborne Precipitation Radar Second Generation (APR-2) from near nadir to 25 ° incidence angle, along with simultaneous wind truth from dropsonde observations, are compared with predictions of the “cutoff-invariant” two-scale model of sea scattering with the overall goal of assessing the model for possible future use in the APR-2 calibration process. The performance of the model as a function of wind speed and incidence angle is therefore emphasized. The measured data set, acquired primarily during the 2010 “Genesis and Rapid Intensification Processes” (GRIP) experiment, includes wind speeds from approximately 5 to 45 m/s. Model comparisons are limited by uncertainties in the wind fields due to limited dropsonde coverage; the data set is separated into “more reliable” (containing wind speeds of 5-20 m/s) and “less reliable” (wind speeds of 5-45 m/s) wind truth categories accordingly. Because a model of the sea spectrum is required for cutoff-invariant model predictions, comparisons with measured data are performed for three differing sea spectrum descriptions. It is found that a bias of less than ~ 1 dB over the wind speed range 5-40 m/s and a standard deviation less than 1 dB over the wind speed range 10-40 m/s can be achieved when using the “unified” sea spectrum description of Elfouhaily The model also provides error levels that are near uniform with respect to both incidence angle and wind speed. [ABSTRACT FROM PUBLISHER]

Highly crevassed ice surfaces at ice-sheet margins and fast-flowing glaciers significantly scatter radar signals. The scattered signals, often known as surface clutter, mask weak echoes from the ice-bed interface. Large wing-mounted antenna arrays are essential to synthesizing low-sidelobe patterns to reduce surface clutter. However, wing-mounted arrays are susceptible to structural flexure, which causes amplitude and phase errors that result in shifting and filling of desired array pattern nulls. In this communication, we characterize the effects of wing flexure on array beamformation using a scaled array model, and we present a compensation method to mitigate phase center errors caused by wing flexure. The compensation greatly improves clutter suppression through improved null formation. Experimental results show that we obtain an average of 7.5 dB improvement in the signal-to-interference noise ratio. [ABSTRACT FROM PUBLISHER]

Antenna arrays with low sidelobes in the cross-track direction are needed for sounding and imaging ice-sheets margins including outlet glaciers. Weak radar signals from the ice-bed interface are often masked by off-vertical surface clutter from extremely rough crevassed surfaces in ice-sheet margins. Synthetic aperture radar (SAR) processing can be used to synthesize a large array for reducing clutter in the along-track direction. Low-sidelobe transmit- and receive-antenna patterns must be generated from a limited size array in the cross-track direction. Airborne antenna pattern measurements are critical to verifying pattern characteristics in the presence of a non-ideal ground plane and neighboring aircraft structures, as well as in-flight operational dynamics. In this paper, we describe a set of airborne measurements performed to determine and optimize antenna patterns for the very high frequency (VHF) array used to sound and image polar ice sheets. We measured antenna patterns by flying over a relatively smooth ice surface at an altitude of about 2700 m. The pattern data were obtained by processing the surface echoes with aircraft rolled from left to right over more than five cycles. We also simulated antenna patterns using a three-dimensional computer model of the entire airborne platform and compared with experimental results. The discrepancies between the measured and simulated results are less than 2.7 dB for 85% of the data samples. The measured pattern data will be used to optimize our array processing algorithms. [ABSTRACT FROM PUBLISHER]

This paper describes a physical model of the temporal changes that occur in vegetated land surfaces observed by a repeat-pass radar interferometer. We assume the temporal changes to be caused by a Gaussian-statistic motion of the vegetation elements, with motion variance changing along the vertical direction. We show that the temporal correlation between two interferometric radar signals is affected by the structural parameters of the vegetation, such as canopy height, and varies with the wave polarization. We validate the model using L-band data acquired by the Jet Propulsion Laboratory with the Uninhabited Aerial Vehicle Synthetic Aperture Radar airborne radar. This work provides new insights into the role of temporal decorrelation in interferometric radar applications. [ABSTRACT FROM AUTHOR]

In this paper, we propose novel l_1-regularized space-time adaptive processing (STAP) algorithms with a generalized sidelobe canceler architecture for airborne radar applications. The proposed methods suppose that a number of samples at the output of the blocking process are not needed for sidelobe canceling, which leads to the sparsity of the STAP filter weight vector. The core idea is to impose a sparse regularization (l_1-norm type) to the minimum variance criterion. By solving this optimization problem, an l_1-regularized recursive least squares (l_1-based RLS) adaptive algorithm is developed. We also discuss the SINR steady-state performance and the penalty parameter setting of the proposed algorithm. To adaptively set the penalty parameter, two switched schemes are proposed for l_1-based RLS algorithms. The computational complexity analysis shows that the proposed algorithms have the same complexity level as the conventional RLS algorithm (O((NM)^2)), where NM is the filter weight vector length), but a significantly lower complexity level than the loaded sample covariance matrix inversion algorithm (O((NM)^3)) and the compressive sensing STAP algorithm (O((N_sN_d)^3), where N_sN_d > NM is the angle-Doppler plane size). The simulation results show that the proposed STAP algorithms converge rapidly and provide a SINR improvement using a small number of snapshots. [ABSTRACT FROM PUBLISHER]

In this paper, a novel method is proposed for retrieving 3-D topography of the ground surface by using a single-antenna squint-mode airborne synthetic aperture radar (SAR). The main idea of the method is based on the fact that the spatial 3-D location of a target can be found as the intersection of the range sphere, the Doppler cone, and the elevation plane of the antenna pattern. An accurate estimation of the Doppler centroid for each resolution cell is required to realize this method. Experimental results obtained with a Ku-band airborne SAR are presented. The method calls for using a precise calibrated attitude determination unit. [ABSTRACT FROM AUTHOR]

Recent analysis of a polarimetric synthetic aperture radar (PolSAR) velocity experiment has shown that azimuth ambiguities can provide useful information for the detection of moving targets with an across-track velocity component in PolSAR images using cross-polarization clutter cancellation. This paper examines this phenomenon using theoretical analysis and simulations and illustrates its application with experimental results. It is shown that, for reciprocal scatterers, the phase difference between HV and VH images is zero, whereas for HV and VH ambiguities, the phase difference is π. For land applications, clutter cancellation is essential for the detection of moving targets in PolSAR images. For maritime applications, it can be used to distinguish images from ambiguities. However, it is important to note that the underlying physical reasons for the performance of clutter cancellation are entirely different from ground moving target indication along-track interferometric SAR. It is also shown that cross-pol clutter cancellation is related to filtering of a double-rate-sampled single-channel SAR signal. [ABSTRACT FROM AUTHOR]

This paper is concerned with the simultaneous measurement of terrain heights and currents using an airborne interferometric synthetic aperture radar (INSAR). For the first time, a hybrid two-antenna INSAR system with both along- and across-track baseline components is used to measure high-resolution digital elevation maps (DEMs) and current fields in a Wadden sea area. Coastal applications like the monitoring of sediment transport or the numerical modeling of morphodynamic processes require measurements of topography and currents. Classical in situ measurements of these parameters are both expensive and time consuming, or even impossible if higher spatial resolution is required. Pure along-track interferometers (ATIs) have demonstrated their ability to provide information on ocean currents, while across-track interferometric systems (XTIs) have been successfully used to measure DEMs. In this paper, a hybrid system with both ATI and XTI components is used to acquire synoptic measurement for the first time. An experiment with an airborne system taking data over a Wadden sea area is presented demonstrating the potential of the technique. A geometrical model is developed for the interferometric phase of hybrid INSAR systems. This model combines ATI and XTI techniques using a baseline that spans between two antennas consisting of along-track and across-track components. In this model, both the effect of topography and the radial velocity of the water surface enter into the resulting interferometric phase. To separate both components, the system takes data of the respective scene flying two or more tracks with different flight directions, e.g., antiparallel tracks. This approach leads to a set of linear equations that has a unique solution for the along- and cross-track phase. Finally, an additional phase bias has to be considered due to the radial velocity and the influence of squint. [ABSTRACT FROM AUTHOR]

Snow accumulation rate is an important parameter in determining the mass balance of polar ice sheets. Accumulation rate is currently determined by analyzing ice cores and snow pits. Inadequate sampling of the spatial variations in the ice sheet accumulation has resulted in accumulation rate uncertainties as large as 24%. We designed and developed a 600-900-MHz airborne radar system for high-resolution mapping of the near-surface internal layers for estimating the accumulation rate of polar ice sheets. Our radar system can provide improved spatial and temporal coverage by mapping a continuous profile of the isochronous layers in the ice sheet. During the 2002 field season in Greenland, we successfully mapped the near-surface layers to a depth of 200 m in the dry-snow zone, 120 m in the percolation zone, and 20 m in the melt zone. We determined the water equivalent accumulation rate at the NASA-U_1 site to be 34.9 ± 5.1 cm/year from 1964 to 1992. This is in close agreement with the ice-core derived accumulation rate of 34.6 cm/year for the same period. [ABSTRACT FROM AUTHOR]