The Synchronous Impulse Reconstruction (SIRE) forward-looking radar, developed by the U.S. Army Research Laboratory
(ARL), can detect concealed targets using ultra-wideband synthetic aperture technology. The SIRE radar has been mounted
on a Ford Expedition and combined with other sensors, including a pan/tilt/zoom camera, to test its capabilities of concealed
target detection in a realistic environment. Augmented Reality (AR) can be used to combine the SIRE radar image with
the live camera stream into one view, which provides the user with information that is quicker to assess and easier to
understand than each separated.
In this paper we present an AR system which utilizes a global positioning system (GPS) and inertial measurement
unit (IMU) to overlay a SIRE radar image onto a live video stream. We describe a method for transforming 3D world
points in the UTM coordinate system onto the video stream by calibrating for the intrinsic parameters of the camera. This
calibration is performed offline to save computation time and achieve real time performance. Since the intrinsic parameters
are affected by the zoom of the camera, we calibrate at eleven different zooms and interpolate. We show the results of a
real time transformation of the SAR imagery onto the video stream. Finally, we quantify both the 2D error and 3D residue
associated with our transformation and show that the amount of error is reasonable for our application.
We present a modification of the standard time-frequency (t-f) analysis for landmine detection. The modification is adapted to synthetic aperture radar (SAR) images that may or may not exhibit near-circular symmetry. Each prospective SAR image is here sliced along several directions to generate t-f plots along those chosen cuts, and the resulting 2-D plots are correlated in pairs to obtain a relevant metric, which is defined as their ratio. This metric has served to distinguish targets from clutter objects in the various cases examined here. The procedure was validated using a dataset obtained in a recent field test, and the results are shown.
The U.S. Army Research Laboratory (ARL) has recently evaluated a commercially available borehole radar to detect
targets hidden underground. The goal of the experiment is to demonstrate the feasibility of the borehole radar coupled
with ARL's signal and image processing techniques to penetrate various geophysical media for target detection.
In this paper, we briefly describe the commercial ultra-wideband borehole radar used in the experiment. A conventional
technique to provide the attenuation and velocity maps of the underground area between two holes is called tomography.
It requires separate probes for the transmitter and the receiver for the measurement, and generally is more time
consuming and laborious. Another technique known as reflection is also widely used. In this mode, the transmitter and
receiver travel together as one single unit in one hole to measure the reflection data from surrounding clutter and
underground targets. Although this mode is much simpler to operate than tomography, the resulting image has inferior
resolution in the cross-range (depth) direction. In our experiment we employ this reflection mode, where a small
cylindrical metal target is placed in one hole while the radar (both transmitter and receiver) travels in another hole to
measure the target return. To improve the poor cross-range resolution associated with the reflection raw data image, we
apply the backprojection image formation algorithm that is commonly used in synthetic aperture radar to form high
resolution 2D images. We present the resulting images of background (without target) and with target, and show that the
underground target can be easily detected using change detection technique. This paper also compares the measured data
with the electromagnetic model prediction of the same target.
The Microwave Sensors Branch of the Army Research Laboratory (ARL) recently evaluated the potential of a commercially available borehole radar system for an underground target detection application. We used this ground-penetrating system, which is capable of operation at either 100 or 250 MHz, to conduct experiments at a locally constructed test site. Since the site's soil characteristics would severely impact conclusions drawn from the collected data, we also obtained and analyzed soil samples in order to determine the electrical properties of the earth in the vicinity of the boreholes. In addition, we modeled and then built a canonical target, using this canonical target as an input to electromagnetic simulations. The outputs from these simulations guided us in the analysis and interpretation of the collected radar data.
In this paper, we present a description of both the data collection itself and the results of a posteriori analysis of the collected data. We begin by describing the test site along with the procedures that we followed when conducting the experiments. Next, we present a soil analysis and the expected target radar cross section (RCS) obtained from the electromagnetic modeling simulations. We then discuss the implications of these results for system performance. Finally, we present an analysis of real data from the collection and compare it to what we expect based on the soil analysis and the output of the electromagnetic models. Collectively, these analyses provide an indication of the borehole radar's true potential for detecting underground targets.
A known target buried underground and illuminated from the air on its top flat surface by a ground-penetrating radar (GPR) is used to verify the results of a polarization approach that uses the Huynen parameters. The target is a dielectric cylinder of diameter d and height h that simulates a land mine buried in soil, flat top surface looking up. A method-of-moments (MoM) approach (and codes) is used to generate the complex elements of the scattering matrix of the present target. These elements are obtained in modulus and phase as functions of frequency in the wide band; 0f5 GHz, for various angles of incidence of the radar beam on the air-ground interface. That matrix is then used to generate the elements of the traditional Mueller matrix by several methods, which are described. The Huynen parameters are then extracted from and the pertinent nonvanishing ones are plotted versus frequency in the same band. This extraction is done with care because Huynen defined his differently than in the traditional fashion—a great source of confusion. After several appropriate changes the results agree with those of earlier works. As confirmation, the values of the Huynen parameters revert and recover the original elements of they are extracted from. The plots of the Huynen parameters for this target indeed give a general phenomenological description of the buried, symmetric object with differences in local curvatures and somewhat irregular structure that was originally conceived. The displayed plots of various nonvanishing elements of and of the Huynen parameters, at normal and oblique incidences verify our conclusions and the method.
KEYWORDS: Synthetic aperture radar, Detection and tracking algorithms, Data modeling, Mining, Land mines, Target detection, X band, Bandpass filters, Magnetism, Analytical research
The Army Research Laboratory has recently collaborated with Raytheon to determine the effects of various target signature phenomena on the performance of a detection pre-screening processing chain. These signature phenomena for plastic mines were predicted by ARL's high fidelity electromagnetic models and then observed in airborne X-band synthetic aperture radar (SAR) data. The agreement of the modeled results with experimental data was then used to guide pre-screener design.
In this paper we present predicted plastic mine signatures generated by ARL and compare the results with actual target samples extracted from X-Band SAR data. We then briefly describe the new prescreener algorithm and examine modeling results for other frequency bands in an effort to determine if similar notions can be exploited in these bands as well.
Target signatures extracted by ultra-wideband ground penetrating radar (GPR) will substantially depend on the target's burial depth, and on the soil’s moisture content. Using a Method-of-Moments (MoM) code, we earlier simulated such returned echoes from two targets for several moisture contents and burial depths in a soil with known electric properties. We also showed that they could then be all translated to equivalent echoes from the target at some selected
standardized depth and soil moisture with adequate accuracy. The signature template of each target is here computed using a time-frequency distribution of the returned echo when the target is buried at a selected depth in the soil with selected moisture content. For any returned echo the relative difference can be computed between the target signature and a selected template signature. Using our target translation method (TTM) that signature difference can then be used
as a cost function to be minimized. This is done by adjusting the depth and moisture content, now taken to be unknown parameters, using the differential evolution method (DEM). The template that gives the smallest value of the minimized cost function for a chosen returned echo is here taken to signify the classification. As it turns out, any choice of returned waveform results in correct classification of the two targets used here. Moreover, when the proper template is used, the values of the depth and moisture parameters that give the minimum cost function are good predictions of the actual target depth and soil moisture content.
Ultra-wideband (UWB) ground penetrating radar (GPR) systems are useful for extracting and displaying information for target recognition purposes. The frequency content of projected signals is
designed to match the size and type of prospective targets and environments. The soil medium is generally dispersive and, if moist, dissipative as well. Hence, target signatures whether in the
time, frequency or joint time-frequency domains, will substantially depend on the target's burial depth, and on the soil's moisture content. To be useful for target recognition purposes the signatures
of a given target must be known for several typical burial depths and soil moisture contents. These signatures are then used as templates in the classification process. In an attempt at reducing
the number of needed templates, we focus here on the propagation of the pulses in the dissipative soil medium. Disregarding for the moment the scattering interaction with the target, we examine the distortion of the emitted interrogating pulses as they propagate through the soil and are backscattered to the receiver. We simulated such returned target echoes earlier for several burial depths using a Method-of-Moments (MoM) code. They could then be all translated
to equivalent echoes from the target at some selected standardized depth and soil moisture, and vice-versa. A sufficiently accurate signal processing method for depth conversion could be employed to reduce the number of templates required for the correct classification of subsurface targets with a GPR.
Single-polarity, synthetic aperture radar (SAR) data collected in spotlight mode is examined as part of an effort to identify surface land mines in high-frequency radar imagery. A measurements program was recently conducted using a Ku-band (16 GHz) radar. In this experiment, metal and plastic mines were placed on smooth dirt lanes and in tall and short grass areas adjacent to these lanes. The collected data set consisted of magnitude-only data for several different passes over a common target area that included various reference reflectors as well as the landmines. The metal and plastic mines on the dirt lanes were clearly visible in the processed radar imager, while the mines in the grass areas were not observable - even after applying multi-look averaging. (Multi-look averaging exploits the circular symmetry of the mines to enhance the contrast between the mines and the background clutter). To investigate these effects, we used rigorous moment method-based electromagnetic solvers to compute the backscatter from the metal and plastic mines in a variety of backgrounds. The model results were shown to be consistent with the measurement data for metal mines on the dirt lanes. The plastic mines were not consistent with the data, however. We believe that the difference is due to uncertainty in the mine dielectric constant. The model results also showed that a significant focusing effect (or “glory wave”) could be seen in the plastic mines at low depression angles. Finally, the model demonstrated the highly absorptive nature of the grass, as shown by the significantly reduced radar cross section of mines placed in a three-layer grass model.
The utility of ultra-wideband (UWB) synthetic aperture radar (SAR) for detecting surface and flush buried unexploded ordnance (UXO) is examined using a layered-medium moment method analysis. Clutter models of a subsurface root system have been created using a set of discrete clutter objects. Given the size of the targets and the wideband frequencies of interest, it is shown that the problem size quickly grows beyond the capabilities of even supercomputers. As a result, an approximate linear superposition technique is developed to model the response from a large number of targets (UXO plus clutter objects). The root system clutter model is used in conjunction with the buried UXO targets. Results show that sufficient signal to clutter ratios are achieved to make such a scenario amenable to target detection. The scattering from multiple, randomly oriented, surface-laid UXO is examined next. Results show that targets oriented broadside to the radar aperture have the largest signatures in the SAR image. This suggests a multi-pass strategy over the potential UXO test area for airborne SAR systems.
The utility of low frequency synthetic aperture radar (SAR) for detecting foliage-concealed targets is examined. A forest simulation has been created using a large set of randomly placed and oriented tree models over a lossy dielectric half-space. Given the size of the targets and the wideband frequencies of interest, it is shown that the problem size quickly grows beyond the capabilities of even supercomputers. As a result, an approximate linear superposition technique is developed to model the response from a large number of targets (T-72 tank plus forest model). Results in the SAR image domain show that the clutter response produced by the collection of trees is higher than the response from the T-72 in all cases except when the tank orientation is broadside to the radar aperture. Examination of the backscattered signature of the T-72 shows that there is a direct correlation between the target response and the physical layout of the vehicle. This connection between shape and response holds promise for future exploitation in ATR algorithm development.
The capability of ultra-wideband (UWB) radar systems for extracting and displaying signature information useful for target recognition purposes has been already demonstrated. The frequency content of the projected signals is designed to match the size and kind of prospective targets and environments. Low frequencies are required for deep penetration into the ground, and high frequencies for detailed target information. Such conflicting requirements cannot always be satisfied. The complex permittivity of a soil varies substantially with its moisture content. Dry soils have a relative permittivity close to that of most dielectric mines, with low contrast and detection difficulties as consequences. Moist soils have high complex-valued dielectric constant, which may prevent sufficient penetration of the high frequencies. Moisture content of the soil and target burial depth will alter the returned echo. Moreover, moisture content of the soil and target burial depth will distort the returned echo and hence also the target signature. In the present work we investigate the backscattered radar echoes of a metal target and a dielectric target under illumination by the waveform from an aboveground radar when they are buried at a few representative depths in Yuma soil of a few different moisture contents. These echoes are simulated by the Method- of-Moments (MoM) and then used to determine the targets' signatures as generated by a signal-adaptive time-frequency distribution. These time-frequency distributions can then be used as templates for actual target classification purposes using measured data.
Wideband (approximately 0-2000 MHz) electromagnetic scattering from mines and unexploded ordnance (UXO) is considered using a method of moments (MoM) analysis for general targets in a layered medium, with the lossy, dispersive layers representing the typical layered character of many soils. We examine wave phenomenology to identify target features that may be exploited in target detection algorithms. Accordingly, we examine the target signature in both the frequency and time domain, as well as in the SAR image domain. For this study, we restrict ourselves to a single UXO target, i.e., a 155 mm shell, an arbitrary cylindrical metal mine, and a cylindrical plastic mine (TM- 62P3 anti-tank mine). Results show that for the UXO, a strong correlation exists between the target signature in the frequency domain and the target orientation. For the rotationally symmetric mines, despite their small size, results show that these targets contain isolated scattering centers due to the wide bandwidth of the incident pulse. Further, these scattering centers can be used to deconstruct the backscattered time waveform into closely spaced simple wave objects that leads to an observable interference pattern in the frequency domain. This relatively simple scattering deconstruction lends itself well to target detection and discrimination.
There has been considerable interest in evaluating the use of a low frequency, ultra-wideband (UWB) imaging radar to detect tactical vehicles concealed by foliage. This interest stems from the fact that while high-frequency imagery has shown near-literal imaging capability for targets positioned in open areas, it cannot penetrate tree canopy effectively. However, at low frequencies, the tree canopy is effectively transparent. We examine the issues related to foliage penetrating (FOPEN) radar by first considering VHF scattering from a T-72 tank over soil using a method of moments (MoM) analysis. The MoM analysis considers arbitrary dielectric and perfectly conducting targets in a layered medium, with the lossy, dispersive layers representing the typical layered character of many soils. The solution obtained via the MoM is based on a full-wave formulation of Maxwell's equations. For the clutter, we model both tree trunks as well as a full tree model (trunk and branch structure). The tree trunk is modeled as a dielectric body of revolution (BoR), again using a MoM half-space analysis, while the 'tree' is modeled as an arbitrary dielectric target.
The Army Research Laboratory (ARL) has been developing ultra wideband (UWB), ultra wide angle radar technology to meet warfighter requirements to detect concealed targets (such as tactical vehicles under foliage). Experiments undertaken by ARL and others using testbed radar's (such as ARL's BoomSAR) have shown significant potential for detecting hidden targets. Initial evaluations have concentrated on identifying the 'contrast' ratios for desired targets versus average background. In more recent work, we have begun to evaluate specific angle, frequency, and/or polarization-based scattering properties of targets and clutter to isolate discrimination features for use in automatic target detection and cuing (ATD/C) algorithms (see reference 1). Though promising, much of this work has been ad hoc and based on small data sets that have only recently become available. To complement the measurements and analysis effort under way at ARL, our team is also developing high-fidelity electromagnetic models of targets and certain classes of clutter to gain a physics-based insight into robust discrimination techniques. We discuss recent analysis of both EM model results as well as a unique inverse synthetic aperture radar (ISAR) collection undertaken at Aberdeen Proving Ground (APG). By creating a phenomenological framework for explaining and/or describing target and/or clutter backscatter behavior and comparing it with measured field data, we can develop detection strategies inspired by the unique physics of low-frequency radar. Finally, we suggest one such detection paradigm.
Recent development of wideband, high-resolution SAR technology has shown that detecting buried targets over large open areas may be possible. Ground clutter and soil type are tow limiting factor influencing the practicality of using wideband SAR for wide-area target detection. In particular, the presence of strong ground clutter because of the unevenness, roughness or inconsistency of the soil itself may limit the radar's capability to resolve the target from the clutter. Likewise, the soil material properties can also play a major tole. The incident wave may experience significant attenuation as the wave penetrates lossy soil. In an attempt to more fully characterize this problem, fully polarimetric ultra-wideband measurements have been taken by the US Army Research Laboratory's SAR at test sites in Yuma, Arizona, and Elgin Air Force Base, Florida. SAR images have been generated for above-ground and subsurface unexploded ordnance targets, including 155-mm shells. Additionally, a full-wave method of moments (MoM) model has been developed for the electromagnetic scattering from these same targets, accounting for the lossy nature and frequency dependency of the various soils. An approximate model based on phys9cal optics (PO) has also been developed. The efficacy of using PO in lieu of the MoM to generate the electromagnetic scattering data is examined. We compare SAR images from the measured data with images produced by the MoM and PO simulations by using a standard back-projection technique.
We present results of an unexploded ordnance (UXO) detection algorithm based on template matching in ultra-wideband (130 MHz to 1.2 GHz) synthetic aperture radar (SAR) data. We compute scattered fields of UXOs in different orientations, both on the surface and buried at different depths, using a physical optics (PO) approximation for perfectly conducting targets in a half space via the half-space Green's function. The PO code that we developed computes the scattered fields in a lossy and dispersive material. This permits simulation of targets in real soil. The frequency-domain scattered fields are transformed into time-domain. SAR images of the UXOs at different aspect angles are generated by a standard backprojection technique, with the same resolution as the ground-penetrating ultra-wideband SAR. These SAR images form the templates for detection of the UXOs.
The multi-level fast multipole algorithm (MLFMA) is applied to the problem of scattering from surface and subsurface targets. In this paper we demonstrate how the MLFMA is modified to handle the half-space problem, and present example results for several scattering problems of interest. In particular, we present results for scattering from buried unexploded ordnance.
A method of moment (MoM) analysis is developed for electromagnetic scattering from a generalized perfectly conducting target in the near field of a tree trunk in a layered medium environment. In this analysis, the tree trunk is modeled as a dielectric body of revolution and the layered medium electrical properties can be lossy and dispersive, of interest for simulating real soil. The MoM analysis employs the layered medium Green's function, which is evaluated efficiently via the method of complex images. To simplify the analysis, the conducting target is considered to be a flat plate. To rigorously account for the interaction between these disparate targets, the conducting target and tree trunk are modeled separately, with interactions handled via an efficient iterative procedure. In addition to yielding accurate results, this procedure has memory and run-time requirements that are significantly less than required of a straightforward brute force MoM approach. This latter issue is particularly important for the problem of interest here, since the tree trunk and conducting target are generally electrically large and because this work is ultimately directed towards modeling conducting targets in the near field of multiple tree trunks (that is, simulating targets concealed in tree foliage).
A method of moments (MoM) analysis is developed for electromagnetic scattering from a dielectric body of revolution (BoR) embedded in a layered medium (the half-space problem constituting a special case). The layered-medium parameters can be lossy and dispersive, of interest for simulating the ground. To make such an analysis tractable for wideband applications, we have employed the method of complex images to evaluate the Sommerfeld integrals characteristic of the dyadic layered-medium Green's function. Scattering results from tree trunks are presented, where tree trunks are well represented as BoRs sitting atop a dielectric half-space. In addition, we use our rigorous MoM algorithm to examine scattering from multiple bodies. In this second study, the MoM matrix equations are derived for a BoR and two flat plate conducting targets. To simplify the analysis, the targets are situated in free space. An electric field integral equation (EFIE) formulation is employed in which the submatrices of the MoM matrix are uncoupled, and the current on each body is solved directly. The currents on each body are then recalculated within an outer iterative loop. This iterative solution procedure is shown to preserve the simplicity and attractiveness of an isolated BoR.
A full-wave model is developed for electromagnetic scattering from buried and surface land mines, taking rigorous account of the lossy, dispersive and potentially layered properties of soil. The theoretical results are confirmed via synthetic aperture radar (SAR) measurements, performed using the US Army Research Laboratory's BoomSAR, with which fully polarimetric ultra-wideband SAR imagery is produced. The theoretical model is used to predict wave phenomenology in various environments. Since the efficacy of radar-based subsurface sensing depends strongly on the soil properties, we perform a parametric study of the dependence of such on the target RCS and on possible land-mine resonances.
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