In this paper, we present the results of a modeling study to examine the interference effect of microDopplers caused by offshore wind farms on airborne sensors operating in the synthetic aperture radar (SAR) and ground moving target indicator (GMTI) modes. The modeling is carried out by generating CAD instantiations of the dynamic wind turbine and using the high-frequency electromagnetic code Xpatch to perform the scattering calculations. Artifacts in the resulting SAR and GMTI signatures are evaluated for interference with tracking of boats in coastal waters. Results of signal filtering algorithms to reduce the dynamic turbine clutter in both SAR images and GMTI displays are presented.
KEYWORDS: 3D modeling, Solid modeling, 3D acquisition, Scattering, Computer aided design, Data modeling, Detection and tracking algorithms, Radar, Feature extraction, 3D metrology
In this paper we present an algorithm for target validation using 3-D scattering features. Building a high fidelity
3-D CAD model is a key step in the target validation process. 3-D scattering features were introduced previously [1] to
capture the spatial and angular scattering properties of a target. The 3-D scattering feature set for a target is obtained by
using the 3-D scattering centers predicted from the shooting and bouncing ray technique, and establishing a
correspondence between the scattering centers and their associated angular visibility. A 3-D scattering feature can be
interpreted to be a matched filter for a target, since the radar data projected onto the feature are matched to the spatial
and angular scattering behavior of the target. Furthermore, the 3-D scattering features can be tied back to the target
geometries using the trace-back information computed during the extraction process. By projecting the measured radar
data onto a set of 3-D scattering features and examining the associated correlations and trace-back information, the
quality of the 3-D target CAD model used for synthetic signature modeling can be quantified. The correlation and traceback
information can point to regions of a target that differ from the 3-D CAD model. Results for the canonical Slicy
target using the algorithm are presented.
The electromagnetic scattered field from an electrically large target can often be well modeled as if it is emanating
from a discrete set of scattering centers (see Fig. 1). In the scattering center extraction tool we developed previously based on the shooting and bouncing ray technique, no correspondence is maintained amongst the 3D scattering center extracted at adjacent
angles. In this paper we present a multi-dimensional clustering algorithm to track the angular and spatial behaviors of 3D
scattering centers and group them into features. The extracted features for the Slicy and backhoe targets are presented. We also
describe two metrics for measuring the angular persistence and spatial mobility of the 3D scattering centers that make up these
features in order to gather insights into target physics and feature stability. We find that features that are most persistent are also
the most mobile and discuss implications for optimal SAR imaging.
This paper describes the results of a multi-baseline IFSAR study using a shooting and bouncing ray (SBR) based IFSAR simulator. The SBR technique has been used in the past for 2-D SAR and IFSAR simulations. This paper extends on those approaches for modeling multi-baseline IFSAR images. IFSAR gives the height estimate for a target and hence leads to a 3-D image of the target. The 3-D reconstruction is dependent on the choice of IFSAR sensor parameters. We present a tradeoff study the sensor resolution versus the number of baselines using the SBR based simulator.
KEYWORDS: 3D acquisition, 3D image processing, Synthetic aperture radar, 3D modeling, Scattering, Detection and tracking algorithms, Image acquisition, 3D image reconstruction, Radar, Electromagnetic scattering
The performance of ATR systems can potentially be improved by using three-dimensional (3-D) SAR images instead of the traditional two-dimensional SAR images or one-dimensional range profiles. 3-D SAR image formation of targets from radar backscattered data collected on wide angle, sparse apertures has been identified by AFRL as fundamental to building an object detection and recognition capability. A set of data has been released as a challenge problem. This paper describes a technique based on the concept of 3-D target grids aimed at the formation of 3-D SAR images of targets from sparse aperture data. The 3-D target grids capture the 3-D spatial and angular scattering properties of the target and serve as matched filters for SAR formation. The results of 3-D SAR formation using the backhoe public release data are presented.
KEYWORDS: Doppler effect, Receivers, Radar, Transmitters, Antennas, Monte Carlo methods, Signal processing, Target detection, Error analysis, Signal generators
We investigate the use of a low-cost, two-element receiving array for tracking human movements in indoor surveillance applications. Conventional direction of arrival (DOA) detection requires the use of an antenna array with multiple elements. Here we investigate the use of only two elements in the receiver array. The concept entails simultaneously resolving the Doppler frequencies of the returned signals from the moving targets and the DOA of the targets. Simulation is performed to demonstrate the concept. Both the monostatic and the bistatic scenario where the transmitter and the receiving array are placed at different locations are investigated. DOA errors and tolerances are analyzed for each scenario. An experimental system is constructed to test the concept. The system consists of a two-element receiver array operating at 2.4 GHz. Measurement results of various collection scenarios are presented.
Based on the point scatterer model, the radar signal can be effectively analyzed using the joint time-frequency (JTF) method. The basis functions of a few primary point scatterers are believed to carry target motion information essential to the ISAR imaging process. One major problem with the JTF method is the computation load associated with the exhaustive search process for motion parameters. In this paper, genetic algorithms (GA) are used to for the parameterization process in the JTF method. Real and binary coded GA are investigated and their performance compared with the exhaustive search. It is shown that a significant amount of time can be saved while achieving almost the same image quality by using real-coded GA.
In this paper, ISAR images generated from measured data are compared to those from computer simulation in order to evaluate the effectiveness of ISAR-based target identification. Three sets of images are generated including: (1) motion compensated images from measured data using a joint time-frequency technique, (2) reference images from measured data and GPS-derived aircraft attitude data, and (3) synthetic images predicted by Xpatch. Visual examination and correlation analysis are undertaken to compare the three sets of images. In addition, two problem areas including JEM line corruption of the measured images and 3D rotation of the target are identified.
KEYWORDS: Scattering, 3D image processing, 3D modeling, 3D acquisition, Detection and tracking algorithms, Solid modeling, 3D image reconstruction, Image processing, Electromagnetic scattering, Electroluminescence
We present a technique to extract the three-dimensional (3-D) bistatic scattering center model of a target at microwave frequencies from its CAD model. The method is based on the shooting and bouncing ray (SBR) technique and is an extension of our previous work on extracting the monostatic 3-D scattering center model of complex targets. Using SBR, we first generate the bistatic 3-D radar image of the target based on a one-look inverse synthetic aperture radar (ISAR) algorithm. Next, we use the image processing algorithm CLEAN to extract the 3-D position and strength of the scattering centers from the bistatic radar image. We test the algorithm by extracting bistatic 3-D scattering centers from several test targets and reconstructing bistatic signatures (RCS, range profile, ISAR imagery) using the bistatic scattering centers.
This paper motivates the use of electromagnetic ray tracing for the study of smart antennas in Space Division Multiple Access (SDMA) systems. Whereas past ray tracing studies applied to the study of wireless communications systems have been conducted at low spatial resolution for cell-site design, this study makes use of high resolution data so that fast fading effects could be observed. Uplink diversity gain and downlink signal to interference ratio data is simulated for several mobile user environments to gain insight into the fundamental performance limiting criteria of SDMA systems. Mobile environments were varied from several simple artificial urban environments to a simulation of downtown Austin, Texas. When applicable, all simulation results compare favorably with measurement data taken using the smart antenna testbed at the University of Texas at Austin.
A new methodology based on adaptive joint time-frequency processing is proposed to separate the interference due to fast rotating parts from the original ISAR image of the target. The technique entails adaptively searching for the linear chirp bases which best represent the time-frequency behavior of the signal and fully parameterizing the signal with these basis functions. The signal components due to the fast rotating part are considered to be associated with those chirp bases having large displacement and slope parameters. While the signal components due to the target body motion are represented by those chirp bases having relatively small displacement and slope parameters. By sorting these chirp bases according to their slopes and displacements, the scattering due to the fast rotating part can be separated from that due to the target body. Consequently, the image artifacts overlapping with the original image of the target can be removed and a clean ISAR image can be produced. Furthermore, useful rotation rate information contained in the Doppler signal can be extracted. Successful applications of the algorithm to numerically simulated and measurement data show the robustness of the algorithm.
This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time-domain signature sand synthetic aperture radar (SAR) images of realistic 3D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, IGES curved surfaces, or solid geometries.The computer code, Xpatch, based on the shooting-and-bouncing-ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. Xpatch computers the first- bounce physical optics (PO) plus the physical theory of diffraction (PTD) contributions. Xpatch calculates the multi-bounce ray contributions by using geometric optics and PO for complex vehicles with materials. It has been found that the multi-bounce calculations, the radar return in typically 10 to 15 dB too low. Examples of predicted range profiles, SAR, imagery, and RCS for several different geometries are compared with measured data to demonstrate the quality of the predictions. Recent enhancements to Xpatch include improvements for millimeter wave applications and hybridization with finite element method for small geometric features and augmentation of additional IGES entities to support trimmed and untrimmed surfaces.
Based on the adaptive joint time-frequency processing techniques, a new methodology is proposed in this paper to separate the interference due to fast rotating parts from the original ISAR image of the target. The technique entails adaptively searching for the linear chirp bases which best represent the time-frequency behavior of the signal and fully parameterizing the signal with these basis functional. The signal components due to the fast rotating part are considered to be associated with those chirp bases having large displacement and slope parameters, while the signal components due to the target body motion are represented by those chirp bases which have relatively small displacement and slope parameters. By sorting these chirp bases according to their slopes and displacements, the scattering due to the fast rotating part can be separated form that due to the target body. Consequently, the image artifacts overlapping with the original image of the target can be well removed and a clean ISAR image can be produced. Successful applications of the algorithm to numerically simulated and measurement data show the robustness of the algorithm.
The application of joint time-frequency techniques for the analysis of electromagnetic backscattered data is reviewed. In the joint time-frequency features space, discrete time events such as scattering centers, discrete frequency events such as target resonances, and dispersive mechanisms due to surface waves and guided modes can be simultaneously displayed. We discuss the various joints time-frequency representations including the short-time Fourier transform, wavelet transform, Wigner-Ville distribution, windowed super-resolution algorithms and the adaptive spectrogram. Emphasis is placed on how these algorithms can be used to represent with good resolution the scattering phenomenology in electromagnetic data. We highlight and application of joint time-frequency processing for radar image enhancement and feature extraction. It is shown that by applying joint time-frequency processing to the conventional inverse synthetic aperture radar imagery, it is possible to remove non-point scattering features in the image, leading to a cleaned image containing only physically meaningful point scatterers. The extracted frequency-dependent mechanisms can be displaced in an alternative feature space to facilitate target identification.
We address two ISAR imaging problems by utilizing adaptive joint time-frequency (JTF) processing ideas. In the first application, the adaptive JTF processing is applied to extract non-point scattering resonant features from an ISAR image. By applying JTF processing to the down range dimension,w e show that it is possible to extract the strongly frequency-dependent components from the data that correspond to resonant features on the target.Our results show that non-point scattering mechanisms can be completely removed from the original ISAR image, leading to a cleaned image containing only physically meaningful point scatterers. The non-point scattering mechanisms, when displayed in the frequency-aspect plane, can be used to identify target resonances and cut-off phenomena. In the second application, we utilize adaptive JTF processing to address the motion compensation issue. By applying JTF processing to the cross range dimension, we track how the Doppler frequency varies as a function of imaging time. We then derive the target motion and remove this effect from the data. In both applications, the adaptive JTF engine preserves the phase information in the original data. Consequently, the two processing blocks can be cascaded to achieve both motion compensation and feature extraction.
This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time domain signatures, and synthetic aperture radar (SAR) images of realistic 3-D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, curved surfaces, or solid geometries. The computer code, XPATCH, based on the shooting and bouncing ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. XPATCH computes the first-bounce physical optics plus the physical theory of diffraction contributions and the multi-bounce ray contributions for complex vehicles with materials. It has been found that the multi-bounce contributions are crucial for many aspect angles of all classes of vehicles. Without the multi-bounce calculations, the radar return is typically 10 to 15 dB too low. Examples of predicted range profiles, SAR imagery, and radar cross sections (RCS) for several different geometries are compared with measured data to demonstrate the quality of the predictions. The comparisons are from the UHF through the Ka frequency ranges. Recent enhancements to XPATCH for MMW applications and target Doppler predictions are also presented.
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