Video-SAR systems that employ backprojection to generate frames offer efficient re-use of processed data in the image domain, minimal distortion due to wavefront curvature, a fixed frame viewing angle, and several other advantages over Doppler-based methods such as polar formatting. However, one challenge that persists is real-time autofocusing SAR imagery at high frame rates on small airborne radars with limited computational capacity. The work herein describes a method to condition the I & Q data before backprojecting onto the image grid so that blurring due to errors on the motion measurement system is minimized. The method takes advantage of the extremely efficient FFTs on Graphical Processing Units (GPU) to transform a select number of ranges lines to the Doppler domain so that phase gradient autofocus can be performed. The subsequent autofocus vector is fedback to the most recent portion of the aperture where phases of the I & Q samples are adjusted to mimic a correction in motion measurements. The data are then processed as usual with backprojection to ensure well-focused video frames, even during periods of severe turbulence, changes in GPS satellite sequencing or IMU errors.
General Atomics, ASI has emerged as a leading purveyor of size limited airborne radars for remotely piloted vehicles (RPV). The Lynx B20A is a multi-modal system that includes SAR, video SAR, dismount MTI, and Maritime Wide Area Search (MWAS). GA-ASI is also developing the Due Regard Radar (DRR) for the Predator® B that provides the remote pilot with situational awareness of approaching aircraft over a field of view similar to that of an onboard pilot. GA-ASI hopes to significantly expand the role of RPVs for military and civilian use in the coming decades. Radar will be the lynchpin to achieving this goal.
This paper describes the impact of ground target motion in Synthetic Aperture Radar (SAR) and video SAR mode imagery. The observations provide an approach for optimizing algorithms that detect moving targets by using only the magnitude of a SAR image. A slowly moving target at a constant velocity in the along-track direction or accelerating in the cross-track direction often generates a ridge of intensity that is distinguishable from the background clutter. The direction and location of a detected ridge provide information about the motion of the associated target. The ridge can be approximated as a linear feature and detected using the Hough transform. This approach acts as a complement to detecting the radar shadow of a moving target, improving detection probability. The method is robust enough to discriminate between a ridge associated with a moving target and false alarms due to vegetation, boulders, or stationary manmade objects. Simulated and flight test data collected by General Atomics Aeronautical Systems, Inc. (GA-ASI) validate the method.
In June 2012, General Atomics Aeronautical Systems, Inc. (GA-ASI) Reconnaissance Systems Group participated in the
NATO Unified Vision 2012 (UV12) Joint ISR (JISR) Trial at Orland Main Air Station in Brekstad, Norway. GA-ASI
supplied a modified King Air 200 as a Predator B/MQ-9 Reaper Remotely Piloted Aircraft (RPA) surrogate outfitted
with a Lynx Block 30 Multi-mode Synthetic Aperture Radar/Ground Moving Target Indicator (SAR/GMTI), a FLIR
Star SAFIRE 3800HD Electro-optical/Infrared (EO/IR) sensor, and a L-3 Tactical Common Data Link. This airborne
platform was combined with GA-ASI’s new System for Tactical Archival, Retrieval, and Exploitation (STARE) for full
integration into the NATO ISR exploitation community.
UV12 was an event sponsored by the NATO Joint Capability Group on Intelligence, Surveillance, and Reconnaissance
(ISR) to focus on the interoperability of national ISR assets and improving JISR concept of operations. The Predator B
RPA surrogate flew alongside multiple NATO ISR assets in nine missions that showcased the platform’s all-weather
ISR capabilities focusing on the Lynx SAR/GMTI and Maritime Wide Area Search (MWAS) modes.
The inclusion of the STARE technology allowed GA-ASI’s radar and Full Motion Video (FMV) data to be seamlessly
processed and passed to joint networks where the data was fused with other NATO ISR products, resulting in a full
battlefield reconnaissance picture.
General Atomics Aeronautical Systems, Inc. (GA-ASI) is designing a real-time, video-SAR (synthetic aperture radar) mode for a test bed radar system. Typically, the flight path for video-SAR is circular with the sensor directed inward and broadside relative to the platform heading, providing continuous surveillance over a region of interest. The SAR frames are processed using the backprojection algorithm onto a Cartesian coordinate system at the nominal ground level and oriented in a fixed direction. Standard autofocus techniques are ineffective since the azimuth dimension will be oblique through the images when the synthetic apertures are not centered at a multiple of π/ 2 along the flight path. We have developed an algorithm that estimates the phase gradient from pseudo point-scatterers, regardless of the platform position, and focuses the images before they are compiled into a SAR video. Thus the efficiency and utility of fixed frame video-SAR processing is retained, while image sharpness and quality are not compromised due to antenna motion error measurements and / or severe atmospheric effects during propagation.
Synthetic aperture radar (SAR) images processed using the polar format algorithm (PFA) may exhibit distortion
if the curvature of the spherical wavefronts are not accounted for. The distortion manifests in geometric shifts
and defocusing of targets, and intensifies as distances between pixels and the scene reference position increase.
In this work, we demonstrate a method to mitigate the effects of wavefront curvature by applying localized
(space-variant) phase corrections to sub-regions selected from the polar format processed image. The modified
sub-images are then reassembled into a full image. To minimize discontinuities in the reconstructed image, the
spatially variant phase adjustments are made to regions larger than the sub-images, and pared down before
being reinserted into the complete image. The result is a SAR process that retains the efficiency of the PFA,
yet avoids scene size limitations due to wavefront curvature distortions. The method is illustrated and validated
using simulations and real data collected by the General Atomics Aeronautical Systems, Inc. (GA-ASI) Lynx®
Multi-mode Radar System.
KEYWORDS: Target detection, Data modeling, Synthetic aperture radar, Detection and tracking algorithms, Model-based design, Logic, Simulation of CCA and DLA aggregates, Doppler effect, Radar, Image processing
Ground moving target indication (GMTI) radars can detect slow-moving targets if their velocities are high enough to produce distinguishable Doppler frequencies. However, no reliable technique is currently available to detect targets that fall below the minimum detectable velocity (MDV) of GMTI radars. In synthetic aperture radar (SAR) images, detection of moving targets is difficult because of target smear due to motion, which could make low-RCS targets fall below stationary ground clutter. Several techniques for SAR imaging of moving targets have been discussed in the literature. These techniques require sufficient signal-to-clutter ratio (SCR) and adequate MDV for pre-detection. Other techniques require complex changes in hardware. Extracting the maximum information from SAR image data is possible using adaptive, model-based approaches. However, these approaches lead to computational complexity, which exceeds current processing power for more than a single object in an image. This combinatorial complexity is due to the need for having to consider a large number of combinations between multiple target models and the data, while estimating unknown parameters of the target models. We are developing a technique for detecting slow-moving targets in SAR images with low signal-to-clutter ratio, without minimal velocity requirements, and without combinatorial complexity. This paper briefly summarizes the difficulties related to current model-based detection algorithms. A new concept, dynamic logic, is introduced along with an algorithm suitable for the detection of very slow-moving targets in SAR images. This new mathematical technique is inspired by the analysis of biological systems, like the human brain, which combines conceptual understanding with emotional evaluation and overcomes the combinatorial complexity of model-based techniques.
Ground surface roughness is problematic when using a radar impulse to detect and locate land mines. Waves scatter from a random rough ground surface in unpredictable ways, contributing to clutter that is particularly hard to suppress. This clutter has proven experimentally and computationally to distort and obscure the desired scattered field from a buried target. To overcome this effect we have developed a lightweight, artificial dielectric that can be placed over a chosen area that will mimic flat ground and mitigate clutter effects. An artificial dielectric of close-packed array of small insulated metal-coated plastic spheres and lossless uniform plastic spheres can be formulated to match the dielectric properties soil. The ratio of these two spheres in the collection is adjusted to match a particular soil type and the moisture content. Placing them in a conformable bag and ensuring a flat upper interface with the air, ground reflections from an impulse radar can effectively be removed to reveal a target scattering signature. Furthermore, a matched filter can be used to distinguish between a landmine and a false alarm (such as a rock) The artificial dielectric was matched by running experiments in the frequency and time domains. A 1 GHz center frequency impulse ground penetrating radar was used to collect time signals and compare different cases: flat ground, rough ground and rough ground with artificial dielectric. Results indicate excellent rough surface reflection removal and target signal enhancement.
The problem of scattered and transmitted electromagnetic wave distortion by random rough ground surfaces can be reduced by using a lightweight dielectric matching layer. For mine detection applications, it is essential for this layer to be lightweight, low loss, readily conformable, and adaptable to different soil types. Arrays of metal-coated plastic spheres act as lossless artificial dielectrics with impedance determined by the volume packing fraction. By controlling the thickness of insulator surrounding each sphere, a close-packed array with the dielectric properties of soil can be created inside a compliant rolling bag that will conform to the rough surface of the ground. Since this artificial dielectric is matched to the soil, the ground surface interface is 'softened', without an abrupt transition from soil to air. Signals transmitted and received by GPR antennas immersed in the artificial dielectric within the bag will not be corrupted by ground surface clutter. Alternatively, an artificial dielectric layer on the ground with a planar air interface could be used to ensure that the surface reflection is a constant, well-calibrated signal. Computational models indicate complete removal of the ground clutter, even with occasional gaps between the artificial dielectric and the ground. Experimental studies with swept-frequency measurements and impulse GPR indicate that using this dielectric layer matching to a rough loamy soil ground surface is results in signals that are practically indistinguishable from those of an equivalent layer of the same type of soil.
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