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检索条件"任意字段=SPIE Conference on Algorithm for Synthetic Aperture Radar Imagery V"

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Self-training algorithms for ultra-wideband radar target detection

Self-training algorithms for ultra-wideband radar target det...

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conference on algorithms for synthetic aperture radar imagery X

作者： Mitra, AK Lewis, TL Paul, AS Shaw, AK AFRL SNRR Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819449555

An ultra-wideband (UWB) synthetic aperture radar (SAR) simulation technique that employs physical and statistical models is developed and presented. This joint physics/statistics based technique generates images that have many of the "blob-like" and "spiky" clutter characteristics of UWB radar data in forested regions while avoiding the intensive computations required for the implementation of low-frequency numerical electromagnetic simulation techniques. Approaches towards developing "self-training" algorithms for UWB radar target detection are investigated using the results of this simulation process. These adaptive approaches employ some form of modified singular value decomposition (SvD) algorithm where small blocks of data in the neighborhood of a sliding test window are processed in real-time in an effort to estimate localized clutter characteristics. These real-time local clutter models are then used to cancel clutter in the sliding test window. Comparative results from three SvD-based approaches to adaptive and "self-trained" target detection algorithms are reported. These approaches are denoted as "Energy-Normalized SvD", "Condition-Statistic SvD", and "Terrain-Filtered SvD". The results indicate that the "Terrain-Filtered SvD" approach, where a pre-filter is applied in an effort to eliminate severe clutter discretes that adversely effect performance, appears promising for the purposes of developing "self-traiming" algorithms for applications that may require localized "on-the-fly" training due to a lack of accurate off-line training data.

关键词： ultra-wideband radar synthetic aperture radar target detection signal simulation self-training algorithms

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Comparison of features from SAR and GMTI imagery of ground targets

Comparison of features from SAR and GMTI imagery of ground t...

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conference on algorithms for synthetic aperture radar imagery X

作者： Beckman, D Frame, S Toyon Res Corp Goleta CA 93117 USA

ISBN: (纸本)0819449555

We describe an algorithm for class-independent automated target recognition (ATR) and association using range-Doppler images of moving targets and SAR images of stationary targets. This algorithm can be used both for target identification (by comparison against a pre-existing database of measurements of all potential targets) and target association (not requiring a pre-existing database). The algorithm computes a one-dimensional signature for each received range-Doppler image;these signatures are stored in a database for comparison against other detections. The signatures used in our algorithm are range profiles, generated from the clutter-suppressed, filtered image by incoherently integrating the image energy across a number of Doppler bins centered on the target. The result is then normalized, to remove information about the overall cross-section from the profile, and range-aligned with other collected profiles by matching the profile centroids. Statistical models of the profiles are created as the targets are tracked, and newly-created profiles are compared against the existing models by computing the likelihood of the new profile given a particular model.

关键词： features signatures association identification

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ATR Workbench for automating image analysis

ATR Workbench for automating image analysis

引用

conference on algorithms for synthetic aperture radar imagery X

作者： English, RA Rawlinson, SJ Sandirasegaram, NM Def R&D Canada Ottawa ON K1A 0Z4 Canada

ISBN: (纸本)0819449555

The ATR Workbench is a software application to assist in the development of automation techniques for target recognition within SAR imagery. This will allow researchers and Image Analysts (IAs) to investigate the capabilities of various commercial and experimental applications, singly or in combination, as applied to the target recognition process. The platform will enable studies to determine which aspects improve IA performance when automated, which methods best improve classifier performance, as well as which methods work better for particular environments and target class definitions. Based largely on open-source tools, the Workbench was developed so as to provide an operating system independent bridge between automatic target detection (ATD) applications and target classifiers. It is capable of importing several kinds of ATD reports, of applying different feature extraction and preprocessing algorithms and of implementing various aspects of automatic target recognition (ATR) applications while importing, displaying and reporting their results. Each step may be automated or operated interactively, as required. Initially, this capability is demonstrated on imagery based upon the public MSTAR data set.

关键词： synthetic aperture radar SAR automatic target recognition ATR automatic target detection ATD classification preprocessing HNeT MLP Neural Network

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Migration based SAR imaging for ground penetrating radar systems

Migration based SAR imaging for ground penetrating radar sys...

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conference on algorithms for synthetic aperture radar imagery X

作者： Gu, KL Wang, G Li, J Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

ISBN: (纸本)0819449555

We consider migration based synthetic aperture radar (SAR) imaging of surfaced or shallowly buried objects using both down-looking and forward-looking ground penetrating radar (GPR). The well-known migration approaches devised to image the interior of the earth are based on wave equations and have been widely and successfully used in seismic signal processing for oil exploration for decades. They have exhibited great potentials and convenience to image the underground objects buried in complicated propagation medium. Compared to the ray-tracing based SAR imaging methods, the migration based SAR imaging approaches are more suited for the imaging of the underground objects due to their simple and direct treatment of the oblique incidence at the air-ground interface and the propagation velocity variation in the soil. In this paper, we apply the phase-shift migration approach to both the constant-offset and the common-shot experimental data collected by the PSI (Planning Systems Inc.) GPR systems. We will address the spatial aliasing problems related to the application of migration to the GPR data and the spatial zero-padding approach to circumvent the problem successfully.

关键词： SAR imaging migration spatial aliasing ground penetrating radar mine detection

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Model-based and data-based approaches for ATR performance prediction

Model-based and data-based approaches for ATR performance pr...

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conference on algorithms for synthetic aperture radar imagery X

作者： Lavely, EM Weichman, PB ALPHATECH Inc Burlington MA 01803 USA

ISBN: (纸本)0819449555

Performance of automatic target recognition (ATR) systems depends on numerous factors including the mission description, operating conditions, sensor modality, and ATR algorithm itself. Performance prediction models sensitive to these factors could be applied to ATR algorithm design, mission planning, sensor resource management, and data collection design for algorithm verification. Ideally, such a model would return measures of performance (MOPS) such as probability of detection (P-D), correct classification (P-C), and false alarm (P-FA), all as a function of the relevant predictor variables. Here we discuss the challenges of model-based and data-based approaches to performance prediction, concentrating especially on the synthetic aperture radar (SAR) modality. Our principal conclusion for model-based performance models (predictive models derived from fundamental physics- and statistics-based considerations) is that analytical progress can be made for performance of ATR system components, but that performance prediction for an entire ATR system under realistic conditions will likely require the combined use of Monte Carlo simulations, analytical development, and careful comparison to MOPS from real experiments. The latter are valuable for their high-fidelity, but have a limited range of applicability. Our principal conclusion for data-based performance models (that fit empirically derived MOPS) offer a potentially important means for extending the utility of empirical results. However, great care must be taken in their construction due to the necessarily sparse sampling of operating conditions, the high-dimensionality of the input space, and the diverse character of the predictor variables. Also the applicability of such models for extrapolation is an open question.

关键词： automatic target recognition performance prediction Monte Carlo simulation synthetic aperture radar probability of correct association global optimization feature selection and extraction

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Windowing functions for SAR data with spectral gaps

Windowing functions for SAR data with spectral gaps

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conference on algorithms for synthetic aperture radar imagery X

作者： Doerry, AW Dickey, FM Romero, LA Sandia Natl Labs Livermore CA 94550 USA

ISBN: (纸本)0819449555

synthetic aperture radar systems are being driven to provide images with ever-finer resolutions. This, of course, requires ever-wider bandwidths to support these resolutions in a number of frequency bands across the microwave (and lower) spectrum. The problem is that the spectrum is already quite crowded with a multitude of users, and a multitude of uses. For a radar system, this manifests itself as a number of 'stay-out' zones in the spectrum mandated by regulatory agencies;frequencies where the radar is not allowed to transmit. Even frequencies where the radar is allowed to transmit might be corrupted by interference from other legitimate (and/or illegitimate) users, rendering these frequencies useless to the radar system. In a SAR image, these spectral holes (by whatever source) degrade images, most notably by increasing objectionable sidelobe levels, most evident in the neighborhood of bright point-like objects. For contiguous spectrums, sidelobes in SAR images are controlled by employing window functions. However, those windows that work well for contiguous spectrums don't seem to work well for spectrums with significant gaps or holes. In this paper we address the question "Can some sorts of window functions be developed and employed to advantage when the spectrum is not contiguous, but contains significant holes or gaps?" A window function that minimizes sidelobe energy can be constructed based on prolate spheroidal wave functions. This approach is extended to accommodate spectral notches or holes, although the guaranteed minimum sidelobe energy can be quite high in this case.

关键词： SAR radar image window functions spectral gaps

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Signal processing techniques for forward imaging using ultra-wideband synthetic aperture radar

Signal processing techniques for forward imaging using ultra...

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conference on Unmanned Ground vehicle Technology v

作者： Nguyen, L Ton, T Wong, D Ressler, M USA Res Lab AMSRL SERU Adelphi MD 20783 USA

ISBN: (纸本)0819449423

The U.S. Army Research Laboratory (ARL), as part of a customer and mission-funded exploratory development program, has been developing a prototype of low-frequency, ultra-wideband (UWB) forward-imaging synthetic aperture radar (SAR) to support the U.S. Army's vision for increased mobility and survivability of unmanned ground vehicle missions. The ability of the UWB radar technology to detect objects under foliage could provide an important obstacle-avoidance capability for robotic vehicles, which could improve the speed and maneuverability of these vehicles and consequently increase the survivability of the U.S. forces. In a recent experiment at Aberdeen Proving Ground (APG), we exercised the UWB SAR radar in forward-looking mode and collected data to support the investigation. This paper discusses the signal processing algorithms and techniques that we developed and applied to the recent UWB SAR forward-looking data. The algorithms include motion data processing, self-interference signal (SIR) removal, radio frequency interference (RFI) signal removal, forward-looking image formation, and visualization techniques. We present forward-looking SAR imagery and also volumetric imagery of some targets.

关键词： ultra-wideband radar forward-imaging SAR automatic target detection SAR signal processing

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Registration of multiaspect InSAR images

Registration of multiaspect InSAR images

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conference on algorithms for synthetic aperture radar imagery X

作者： Middelmann, W Pepelka, v Thoennessen, U FGAN-Forschungsinstitut fuer Optronik und Mustererkennung (Germany) S.I. Vavilov State Optical Institute (Russia)

ISBN: (纸本)0819449555

The extensive knowledge of scenes is necessary for change detection or mission planning. Unfortunately, InSAR images have zones with full or partial loss of information, e.g. in shadow areas. We have developed an algorithm for registration and fusion of multi-aspect InSAR images to replace shadow zones in the image of the first aspect by corresponding data taken from another aspect. The investigations were carried out with using of X band images obtained for two aspects. The two aspect images were recorded from two contrary flight courses. The images were delivered as intensity and unwrapped phase of forest, rural and urban terrain. The registration is based on the consecutive application of three separate matching algorithms: matching straight lines, matching contour sequences, and matching based on the Fourier-Mellin transform. The different matching algorithms are optimized for working with the SAR images having different contents. The main peculiarities of the registration algorithm are the methods of structural matching brightness contours calculated by standard edge filters. The shadow borders are excluded from the gradient field by a heuristic algorithm. The contours are extracted by a watershed- or a maximum gradient tracking algorithm. The matching is very robust. It is rather computationally expensive, thus a hierarchical structural matching is used to decrease the computational complexity. The multi-stage contour matching provides a fast and reliable registration and fusion.

关键词： InSAR multi-aspect multi-resolution registration fusion

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Towards the Bayesian-regularization method for enhanced SAR imaging

Towards the Bayesian-regularization method for enhanced SAR ...

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conference on algorithms for synthetic aperture radar imagery X

作者： Shkvarko, Yv IPN CINVESTAV Guadalajara 45090 Jalisco Mexico

ISBN: (纸本)0819449555

In this paper, we propose to unify the Bayesian estimation strategy with the statistical regularization-based techniques for image reconstruction through developing the fused Bayesian-regularization (FBR) method for the high resolution estimation of the spatial spectrum pattern (SSP) of the wave field scattered from the probing surface. The problem is treated as it is required for enhanced radar imaging of the remotely sensed scenes via processing one sampled realization of the SAR trajectory signal. The derived optimal FBR estimator is a nonlinear solution-dependent (thus referred to as an adaptive) algorithm that also permits a concise robust simplification to the non-adaptive easy-to-implement imaging techniques. The optimal and robustified suboptimal SSP estimation algorithms imply formation of the second order sufficient statistics from the SAR trajectory data signals and their smoothing applying the window operators. The new formalism of such the sufficient statistics and windows explaining their adjustment to the metrics in a solution space, a priori nonparametric model of the desired SSP, its correlation properties and imposed regularization constraints is developed. The advantage in using the proposed method is demonstrated through simulations of enhancing the SAR images using a family of the robustified FBR-based imaging algorithms.

关键词： remote sensing spatial spectrum pattern regularization Bayesian estimation radar imaging

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Three dimensional fully polarimetric W-band ISAR imagery of scale-model tactical targets using a 1.56THz compact range.

Three dimensional fully polarimetric W-band ISAR imagery of ...

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conference on algorithms for synthetic aperture radar imagery X

作者： Goyette, TM Dickinson, JC Waldman, J Nixon, WE Univ Massachusetts Lowell Submillimeter Wave Technol Lab Lowell MA 01854 USA

ISBN: (纸本)0819449555

Using the high-frequency terahertz compact range developed recently for measurement of polarimetric return of scale models of tactical targets, we have developed several techniques to produce three-dimensional data sets. Fully polarimetric three-dimensional ISAR data has been collected on several 1/16(th) scale model tactical targets in free space at individual look angles. The three-dimensional scattering coordinates are calculated by viewing the target through a two-dimensional angular aperture in both azimuth and elevation while simultaneously performing a linear frequency chirp to measure the down-range coordinate. Due to the high frequency of W-band radar, this technique produces high-resolution cross-range images from relatively small (approximately 1 degree) angular integrations. Several techniques for calculation of the three-dimensional coordinates have been developed. In addition to the technique described above, a new method utilizing the phase change of the scattering centers due to differentially small changes in angle will be described. Data collected using this technique can be processed to produce three-dimensional scattering information similar to that obtained by monopulse systems. Results from this analysis will be shown.

关键词： sub-millimeter radar imagery modeling

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