A new methodology for geolocating slow moving targets using SAR images at multiple phase centers is shown here along with methods to minimize false targets. In an effort to isolate the true movers from the false targets, a new approach exploiting spatio-temporal connectivity in addition to signal processing algorithms involving imaging and interferometry is proposed here to geolocate the movers in a measured data set.
Along-Track Interferometry (ATI) has been widely used for ground moving target indication (GMTI) in airborne synthetic aperture radar (SAR) systems. In ideal cases, the ATI phase obtained using two phase centers that are aligned in the along-track dimension yield clutter-only pixels with zero phase. However, the platform's motion may create a cross-track displacement between the two phase centers and in turn offset the phase centers' baseline from the along track dimension. This cross-track offset leads to non-zero phase for clutter-only pixels, necessitating calibration for accurate GMTI. This paper proposes a blind calibration method to correct the along-track baseline error in ATI-SAR systems. The success of the proposed method is shown on a set of measured data from the Gotcha sensor.
Proc. SPIE. 9093, Algorithms for Synthetic Aperture Radar Imagery XXI
KEYWORDS: Target detection, Radar, Signal to noise ratio, Detection and tracking algorithms, Doppler effect, Synthetic aperture radar, Digital filtering, Antennas, Global Positioning System, Device simulation
We describe techniques for improving ground moving target indication (GMTI) performance in multi-channel synthetic aperture radar (SAR) systems. Our approach employs a combination of moving reference processing (MRP) to compensate for defocus of moving target SAR responses and space-time adaptive processing (STAP) to mitigate the effects of strong clutter interference. Using simulated moving target and clutter returns, we demonstrate focusing of the target return using MRP, and discuss the effect of MRP on the clutter response. We also describe formation of adaptive degrees of freedom (DOFs) for STAP filtering of MRP processed data. For the simulated moving target in clutter example, we demonstrate improvement in the signal to interference plus noise (SINR) loss compared to more standard algorithm configurations. In addition to MRP and STAP, the use of tracker feedback, false alarm mitigation, and parameter estimation techniques are also described. A change detection approach for reducing false alarms from clutter discretes is outlined, and processing of a measured data coherent processing interval (CPI) from a continuously orbiting platform is described. The results demonstrate detection and geolocation of a high-value target under track. The endoclutter target is not clearly visible in single-channel SAR chips centered on the GMTI track prediction. Detections are compared to truth data before and after geolocation using measured angle of arrival (AOA).
A small and lightweight dual-channel radar has been developed for SAR data collections. Using
standard Displaced Phase Center Antenna (DPCA) radar digital signal processing, SAR GMTI images have
been obtained. The prototype radar weighs 5-lbs and has demonstrated the extraction of ground moving
targets (GMTs) embedded in high-resolution SAR imagery data. Heretofore this type of capability has been
reserved for much larger systems such as the JSTARS. Previously, small lightweight SARs featured only a
single channel and only displayed SAR imagery. Now, with the advent of this new capability, SAR GMTI
performance is now possible for small UAV class radars.
An airborne circular synthetic aperture radar system captured data for a 5 km diameter area over 31 orbits.
For this challenge problem, the phase history for 56 targets was extracted from the larger data set and placed
on a DVD for public release. The targets include 33 civilian vehicles of which many are repeated models,
facilitating training and classification experiments. The remaining targets include an open area and 22 reflectors
for scattering and calibration research. The circular synthetic aperture radar provides 360 degrees of azimuth
around each target. For increased elevation content, the collection contains two nine-orbit volumetric series,
where the sensor reduces altitude between each orbit. Researchers are challenged to further the art of focusing,
3D imaging, and target discrimination for circular synthetic aperture radar.
This document describes a challenge problem whose scope is two-fold. The first aspect is to develop SAR CCD
algorithms that are applicable for X-band SAR imagery collected in an urban environment. The second aspect relates to
effective data compression of these complex SAR images, where quality SAR CCD is the metric of performance.
A set of X-band SAR imagery is being provided to support this development. To focus research onto specific areas of
interest to AFRL, a number of challenge problems are defined.
The data provided is complex SAR imagery from an AFRL airborne X-band SAR sensor. Some key features of this data
set are: 10 repeat passes, single phase center, and single polarization (HH). In the scene observed, there are multiple
buildings, vehicles, and trees. Note that the imagery has been coherently aligned to a single reference.
This document describes a challenge problem whose scope is the detection, geolocation, tracking
and ID of moving vehicles from a set of X-band SAR data collected in an urban environment. The
purpose of releasing this Gotcha GMTI Data Set is to provide the community with X-band SAR data
that supports the development of new algorithms for SAR-based GMTI. To focus research onto
specific areas of interest to AFRL, a number of challenge problems are defined.
The data set provided is phase history from an AFRL airborne X-band SAR sensor. Some key
features of this data set are two-pass, three phase center, one-foot range resolution, and one
polarization (HH). In the scene observed, multiple vehicles are driving on roads near buildings.
Ground truth is provided for one of the vehicles.
This paper describes a challenge problem whose scope is the 2D/3D imaging of stationary targets from a volumetric data
set of X-band Synthetic Aperture Radar (SAR) data collected in an urban environment. The data for this problem was
collected at a scene consisting of numerous civilian vehicles and calibration targets. The radar operated in circular SAR
mode and completed 8 circular flight paths around the scene with varying altitudes. Data consists of phase history data,
auxiliary data, processing algorithms, processed images, as well as ground truth data. Interest is focused on mitigating
the large side lobes in the point spread function. Due to the sparse nature of the elevation aperture, traditional imaging
techniques introduce excessive artifacts in the processed images. Further interests include the formation of highresolution
3D SAR images with single pass data and feature extraction for 3D SAR automatic target recognition
applications. The purpose of releasing the Gotcha Volumetric SAR Data Set is to provide the community with X-band
SAR data that supports the development of new algorithms for high-resolution 2D/3D imaging.
This paper examines the theory, application, and results of using single-channel synthetic aperture radar (SAR) data with Moving Reference Processing (MRP) to focus and geolocate moving targets. Moving targets within a standard SAR imaging scene are defocused, displaced, or completely missing in the final image. Building on previous research at AFRL, the SAR-MRP method focuses and geolocates moving targets by reprocessing the SAR data to focus the movers rather than the stationary clutter. SAR change detection is used so that target detection and focusing is performed more robustly. In the cases where moving target returns possess the same range versus slow-time histories, a geolocation ambiguity results. This ambiguity can be resolved in a number of ways. This paper concludes by applying the SAR-MRP method to high-frequency radar measurements from persistent continuous-dwell SAR observations of a moving target.
The Lincoln Laboratory ground-based UWB Rail SAR was used to collect UHF and L-band data on a variety of mine-like targets. The target set consisted of metal pipes, bomb fragments, and M-20 metallic anti-tank mines, above and below ground. Mostly co-polarized data was collected for depression angles between 10 and 30 degrees. Imagery of the targets in different frequency sub-bands are shown and RCS characteristics are quantified.
The Lincoln Laboratory ground-based rail SAR was used to collect UHF band data on buried and partially buried trihedral corner reflectors in Yuma soil. The frequency range was 0.25 to 1 GHz in discrete steps. Both HH and VV polarization data were collected in the vicinity of the pseudo-Brewster angle. The partially buried trihedrals revealed two principal components for the returned signals: (1) a surface reflected component, and (2) a ground penetrated component. A model is described for partially buried trihedrals that accounts for these two components and the model is used in estimating ground penetration parameters.