Detecting Moving Targets in Clutter in Airborne SAR via Keystoning and Multiple Phase Center Interferometry

Transcription

1 Deteting Moving Targets in Clutter in Airborne SAR via Keystoning and Multiple Phase Center Interferometry D. M. Zasada, P. K. Sanyal The MITRE Corp., 6 Eletroni Parkway, Rome, NY 134 (dmzasada, psanyal)@mitre.org R. P. Perry The MITRE Corp., Burlington Road, Rte. 6, Bedford, MA , rpp@mitre.org Without motion ompensation, Syntheti Aperture Radar (SAR) images of the ground are generally blurred. In 1997, MITRE reported the development tehnique alled the Keystone Proess for removing the range migration aused by the radial veloity omponent of eah pixel s movement within the sene, whether moving or stationary with respet to the ground. When applied to multiple phase enter phased array radar data, this first pass proess allows for automated detetion of moving targets via phase thresholding. One deteted in phase spae, the moving targets an be individually and automatially foused using the proedures previously reported. Automated positioning of the deteted target within the formed image is then aomplished (georegistration) We an easily detet and aurately georegister bright (large radar ross-setions) moving targets using a phase threshold tehnique reported herein. However, we have found that, for smaller targets, the phase differenes between the ells ontaining the moving target an be greatly distorted by the presene of strong ground lutter. Only after the ground lutter is anelled will the phase differene be suffiiently dominated by the target response to allow aurate geopositioning. Herein we desribe one tehnique whereby the lutter may be anelled by using multiple phase enters. I. INTRODUCTION Without motion ompensation, Syntheti Aperture Radar (SAR) images of the ground are generally blurred. In 1997, MITRE reported development of the Keystone Proess [1]. This proess removes range migration aused by the radial veloity omponent of eah pixel s movement within the sene, independent of whether the illuminated objet is moving or stationary with respet to the ground. This first pass proess allows for automated detetion of moving targets via phase thresholding, as we have reported previously in [, 3, 4]. be derived by noting that the spetrum of a single reeived pulse is given by, f ) exp[ i ) R( t)], (1) where P( f ) = spetrum of transmitted pulse, B B f = baseband frequeny ( f < ), f arrier frequeny. = Expanding R(t) in a Taylor series, we get: 1 R ( t) = R( t ) + R& ( t ) t + R&& ( t ) t + L. () Substituting () into (1) and dropping ubi and higher order terms, f )exp[ i ) R i ( f f ) Rt & π + i ) Rt && ]. The seond term in the brakets ontains the produt f Rt & that gives rise to range walk. This term beomes zero when we use the temporal transformation f t = ( ) t. f + f (3) II. KEYSTONE FORMATTING Keystone Formatting simultaneously ompensates for multiple target motion at multiple radial veloities... It an

2 With the above substitution, (3) an be written as, f )exp[ i ) R (4) f t i f Rt & π i ) R&& ( ) ]. f + f Sine the Keystone formatting does not solve the quadrati (or higher order) motion problem we also drop the quadrati term in (4) and simplify to: f ) * (5) exp[ i ) R i f R & t ]. Notie that the substitution of t for t has removed the phase term that varied with both time and frequeny and this removes the range-walk. Thus no matter what radial veloity the target is moving at, it will remain in a given range ell determined by its position at the enter (t=) of the oherent proessing interval. Figure 1 shows the keystone nature of the transformation. Figure shows the effet of Keystoning on the range walk. Coherent proessing of the data without any ompensation for target motion results in an integration loss and smearing of the target over multiple range ells. Standard motion ompensation will only orret the range walk for one target at a time. The Keystone proess ompensates for the motion of all the targets simultaneously. In a SAR image that has been foused with the Keystone Proess and the appropriate ground aeleration orretion, moving objets may still appear unfoussed, sine they eah may have a different aeleration relative to the radar platform as ompared to the point on the ground where the target is loated at any instant. One deteted, the moving targets an be individually and automatially foused using the proedures previously reported in [1]. A seond effet that the motion of the target has is that it auses the moving targets to appear at loations different from their true instantaneous loations on the ground. This is due to the oupling of the ross-range position to the target radial veloity and the fat that the moving target and the ground under it have different radial veloities relative to the platform. The result is the well known train off the trak phenomenon. III. SIMULTANEOUSLY DETECTING AND POSITIONING MOVING TARGETS IN SAR Complimentary to the Keystone Range-Doppler-Intensity (RTI) image, we also form a phase interferometry image. In the interpherometri phase image, all points on the ground nominally appear as a ontinuum of phase differenes while the moving targets appear as disontinuities. By threshold omparisons within the intensity and the phase images, we [3] and others [] have shown that it is possible to detet and georegister moving targets in the SAR. An example is shown in Figure 5. In partiular, using a QuikSAR tehnique [3] omparing sequential short-duration, elliptially pixelleted SAR images, we have obtained exellent results deteting moving targets against bakground senes and orretly georegistering them in omposite images. Figure 1. Keystone Formatting Performs Motion Compensation for Targets Moving at Different Veloities However, even a linear, onstant veloity motion of the olletion platform results in a pseudo-aeleration of the platform relative to individual points on the ground. Thus, the SAR data has to be further ompensated for this pseudoaeleration to produe foused images. Figure 3 shows an example wherein the appropriate aeleration orretion has foused the image. Figure 4 shows a Google Earth image of the same geographial area; the orrespondene is quite lear. IV. CLUTTER CANCELLATION Although we an easily detet and aurately georegister bright (large radar ross-setions) moving targets using these tehniques, we have found that, for smaller targets, the phase differenes between the ells ontaining the moving target are greatly distorted by the presene of strong ground lutter in those ells. Only after the ground lutter is anelled will the phase differene be suffiiently dominated by the target response to allow orret georegistration. Our urrent Keystone QuikSAR proessing hain is shown below in figure 6. The pale yellow proess bloks indiate the additional steps required for lutter anellation. Two pairs of phase enters are used to form two new phase enters with redued bakground lutter (figure 7). This is aomplished using a linear least squares planar best fit to the differential phase surfae for eah pair to obtain the omplex weights to redue their lutter. A new redued lutter interferometer pair is then formed and proessed to detet (figure 8) and position the moving targets (figure 9). Interferometri phase disontinuities are automatially deteted via a threshold proess. This series of steps result in far more onsistent automati detetion and trak initiation

3 on small, slow moving, targets than via phase thresholding without prior lutter anellation. REFERENCES [1] Rihard P. Perry, Robert C. DiPietro and Ronald L. Fante, The MITRE Corporation, SAR Imaging of Moving Targets. IEEE Transations on Aerospae and Eletroni Systems, Vol. 35, No. 1, pp [] Stokburger, E. F., Held, D. N., Interferometri Moving Target Imaging, IEEE International Radar Conferene, 1995 [3] Sanyal, P. K., Perry, R. P., Zasada, D. M., Deteting Moving Targets in SAR via Keystoning and Multiple Phase Center Interferometry, IRSI-5, Bangalore, India, Deember 5 [4] Sanyal, P. K., Perry, R. P., Zasada, D. M., Deteting Moving Targets in SAR via Keystoning and Multiple Phase Center Interferometry, IEEE Radar6, Oneida NY, April 6. Figure. Keystone Formatting Performs Motion Compensation for Targets Moving at Different Veloities

4 Figure 3. SAR Images of Ft. Huahua reated from LiMIT Data Colleted by Linoln Laboratory Figure 4. Google Earth image of geographial area orresponding to the SAR Images of Ft. Huahua in figure 1

5 Figure 5. Automatially Deteting Moving Targets in the Ft. Huahua Phase Image Figure 6. Blok Diagram of Moving Target Detetion and Traking Using Multiple Phase Centers

6 CLUTTER CANCELLED 5 GROUND IMAGE Figure 7. Canellation of Ground Clutter. Right panel is lutter bakground, Left panel is lutter residue after anellation. PHASES OF TARGET1 3 CALCULATED PHASE PLANE, SUM5-SUM Figure 8. Improvement in Contrast in the Phase Image (left panel) due to Clutter Canellation (Target Auto-deteted) Geopositioning aomplished via fitting smoothed target phase to phase referene plane (right panel) mathing