IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 3, NO. 3, JULY 2006 377

Interferometry With ENVISAT WideSwath ScanSAR Data

Pietro Guccione

Abstract—The possibility to get efficient topographic mappingand monitoring of large-scale motions with ScanSAR interferom-etry has been demonstrated with the Shuttle Radar TopographyMission and RADARSAT mission. The Environmental SatelliteAdvanced Synthetic Aperture Radar (ASAR) sensor has beendesigned to provide enhanced capabilities for interferometricapplications. Different types of interferometric products can beobtained by combining the various ASAR modes as stripmapsynthetic aperture radar [image mode (IM)] and ScanSAR [wideswath (WS) mode]. This letter deals with the possibility to useWS data to get either mixed-mode (IM/WS) or ScanSAR mode(WS/WS) differential interferograms. The impact of digital ele-vation model localization errors on IM/WS interferograms andof scan pattern synchronization on WS/WS interferograms isinvestigated. Experimental results are encouraging and show thatASAR ScanSAR data can be routinely used for interferometricapplications in both cases.

Index Terms—Interferometry, scanning antennas, syntheticaperture radar (SAR).

I. INTRODUCTION

S canSAR mode achieves a large swath coverage by peri-odically switching the antenna pointing. This allows to

image a large swath at the expense of azimuth resolution. Theincreased range swath can produce large-area interferometricimages and a more frequent coverage for differential applica-tions, like surface deformation measurement, change detection,and monitoring of natural hazards [2].

The Environmental Satellite (ENVISAT) Advanced Syn-thetic Aperture Radar (ASAR) wide swath (WS) complexproduct recently released by the European Space Agency (ESA)makes the exploitation of ScanSAR data for interferometricapplications more attractive.

ScanSAR interferometry depends heavily on the availabil-ity of precise timing and localization of the sensor. DopplerOrbitography and Radiopositioning Integrated by Satellite(DORIS)-derived orbits and ENVISAT onboard clock guaran-tee [5] a root-mean-square (rms) positioning error of 1 m alongtrack and 0.5 m cross track, adequate to obtain interferogramswithout the need to refine image registration. Experimentalresults confirm such expectations.

Interferometric applications using WS data are the object ofthis letter. Section II briefly revises the properties of ScanSARsystems. Section III shows that good differential mixed-modeinterferograms can be achieved even in areas with significant

Manuscript received October 27, 2005; revised February 16, 2006.The author is with the Dipartimento di Elettrotecnica ed Elettronica, Politec-

nico di Bari, Bari 70125, Italy (e-mail: guccione@poliba.it).Digital Object Identifier 10.1109/LGRS.2006.873876

Fig. 1. Acquisition geometry and time-frequency spectral support ofScanSAR data. The slope of the spectrum is kR.

relief, but digital elevation model (DEM) localization errors arean issue. Section IV considers pure ScanSAR interferometryand how the need to guarantee a proper spectral overlap of thestereo pair requires the synchronization of the scanning patternsof the two acquisitions which, with WS data (five subswathsand three looks), is far from being assured. A simple methodto verify pattern synchronization for candidate stereo pairs isdescribed. Conclusions are in Section V.

II. PROPERTIES OF SCANSAR SYSTEM

ScanSAR acquisition geometry and spectral properties of the“focused” data are well known [1], [6]; thus, just the basics arerecalled here.

A ScanSAR sensor is basically a SAR with a discontinuousdata acquisition. It acquires short bursts of time extent TD(“dwell” time) and cyclically changes the elevation pointingof the antenna, scanning all the subswaths (SS). The timethe antenna takes to complete the scanning pattern is calledcycle time TR and must be less than the time a scatterer stayswithin the antenna footprint TF to assure azimuth continuityof the imaged scene. The azimuth response of the acquisitionsystem is time variant; scatterers at different azimuth positionscontribute different segments of a same chirp with a Dopplerrate that depends on the acquisition geometry (see Fig. 1).

Focusing of ScanSAR data is basically a correlation of the re-ceived echoes with the azimuth Doppler history (just as for stripmode, see [7]–[9]); it performs an azimuth redistribution of theechoes along the antenna footprint, according to their spectralcontent, but leaves their spectral support unchanged. The time-frequency support of the processed data is a strip � |kR|TDwide, which sweeps the whole Doppler bandwidth (∼ |kR|TF ,with kR as the Doppler rate).

1545-598X/$20.00 © 2006 IEEE

378 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 3, NO. 3, JULY 2006

III. MIXED-MODE INTERFEROMETRY

To get meaningful interferograms, the images in a stereo pairmust share a common spectral domain [3], [4], [10]. If one ofthe images is derived from ScanSAR data, its spectral supportis as described above. The first proposed interferometric appli-cation [4] for ScanSAR data was in mixed-mode interferometrythat mixes ScanSAR and strip map (image mode for ENVISAT)data. This is because the image mode (IM) data have a spectralsupport that fills the whole azimuth bandwidth. If the stereo pairis geometrically paired, it is always possible to cut the ScanSARspectral support out of the full bandwidth spectrum of theIM data.

To “cut” a slice like that shown in Fig. 1 out of the “full”spectral domain of IM data, IM data are multiplied by a com-plex exponential exp(−πkR(t− to)2), low-pass filtered in aband � ±kRTD/2 and remultiplied by another complex expo-nential exp(πkR(t− to)2). The first multiplication centers thespectral strip over the time axis, whereas the second one placesit back over the line with slope kR in the slow-time/Dopplerfrequency plane.

The geometric resolution of the resulting interferogram is,at most, equal to that of the coarser resolution image in thestereo pair (the ScanSAR one). Large-resolution cell meansmore decorrelation noise, which is due to the interfering phasesof returns from scatterers at different altitudes within the cell.Interferograms coming from coarse-resolution images are thenlimited to smooth or nearly flat surfaces [4].

However, the use of a DEM with a resolution comparablewith that of the full-resolution image (ASAR IM, 30 m inground range) can remove the average local slope of the in-terferogram [4], preventing further decorrelation noise fromarising. In this context, the DEM localization errors (simplerigid shifts are here taken into account) must compare with thefull-resolution cell size (30 m), which is much smaller than theScanSAR resolution cell azimuth size.

Let I1 = A1 exp(ϕ1) and I2 = A2 exp(ϕ2) be the first andsecond complex images in the stereo pair, after registrationand common band filtering. The phase of each image canbe decomposed into two terms: 1) the topographic phase de-ducible from the DEM ψi and 2) the residual φi: ϕi = φi +ψi (i = 1, 2). The differential interferogram results from thecombination of the images after subtraction of the DEM-derived topographic phase. Let suppose that the DEM is mis-located and let ψSi be the corresponding topographic phase.

Coherence is used as a measure of the final quality of theinterferogram

|γ| =

∣∣E [I1I

∗2e

−(ψS1−ψS2)]∣∣

√E [|I1|2] · E [|I2|2]

. (1)

After some manipulations and assuming statistical indepen-dence between the residual interferogram and the DEM topo-graphic phase

|γ| =

∣∣E [A1A2e

∆φ]∣∣

√E [A2

1] · E [A22]

· ∣∣E[e∆ψe−∆ψS ]∣∣ (2)

TABLE IASAR IM/WS DATASET PARAMETERS

where ∆φ = φ1 − φ2 is the residual interferometric phase af-ter optimal removal of the DEM topographic phase, ∆ψ =ψ1 − ψ2 represents the DEM topographic phase, and ∆ψS =ψS1 − ψS2 is the phase from a mislocated DEM.

The result equals the one obtainable with a perfectly locatedDEM times a factor ≤ 1, which is the cross correlation betweenthe topographic phases from a correctly located DEM and amislocated DEM, i.e.,

|γdispl| = |γopt| ·∣∣E[e∆ψe−∆ψS ]

∣∣ . (3)

Small DEM displacements approximately result in a similarlydisplaced phase, i.e.,

∆ψS(l,m) � ∆ψ(l + l1,m+m1).

Therefore, the factor in (3) can be approximated with thetopographic phase autocorrelation. Obviously, mountainous re-gions will exhibit a narrower autocorrelation function than flatregions because topographic phase properties depend on thelocal terrain slope and roughness described by the DEM [4].

The area around the city of Las Vegas has been selectedbecause of its temporal stability and because of the availabilityof a high-resolution (1 arcsec, � 30 m × 30 m of groundsampling) Shuttle Radar Topography Mission (SRTM) DEM.Topographic phase has been generated using the DEM and,through geometrical considerations, from DORIS-derived or-bits and the time stamps of the ENVISAT data. Table I sum-marizes the parameters of the two missions. The amplitudeimage of the whole area is shown in Fig. 2. Three differentregions are marked: two on relatively flat areas (on a valleyand on the city) and the other one on mountains. The slantrange cuts of the topographic phase autocorrelation function,computed on these three different regions, are sketched inFig. 3. As expected, topographic phase autocorrelation functionis narrower on mountainous area, wider on smoother areas.

ASAR IM and ScanSAR WS complex images have beenused to generate interferograms, but when mixed with the topo-graphic phase to get the differential interferogram, the DEMhas been shifted with respect to the master image. The in-terferogram quality was assessed using coherence, as in (1).The most peaked coherence histogram has been consideredthe indicator of the best match. No procedure to correct theregistration of the two images in the stereo pair has been used.

We focused on the DEM displacement errors as the SRTMDEM was the best available for testing. Elevation errors alsocontribute to decorrelation noise but, using results in [4], acoherence value ≥ 0.7 can be expected for the most part of theselected area as, with the available SRTM DEM (which has a

GUCCIONE: INTERFEROMETRY WITH ENVISAT WIDE SWATH SCANSAR DATA 379

Fig. 2. Amplitude image of the whole area (about 100 km × 100 km).Highlighted regions mark where the topographic phase autocorrelation functionestimates of Fig. 3 have been computed. The area to which the interferogramsof Fig. 5 refer has been marked, too.

Fig. 3. Range cut of the topographic phase autocorrelation function.

σq � 6 m [11]), this should be possible as long as local slopesare ≤ 15◦.

The optimal positioning of the DEM required the adoptionof an automatic procedure to search for the displacement thatgives the highest coherence. Fig. 4 shows estimated coherencehistograms corresponding to a few slant range shifts of theDEM w.r.t. the master image reference; the best shift is the onethat moves the greatest number of pixels toward high coherence(higher signal-to-noise (S/N) ratio), i.e., the one (in Fig. 4:+5 pixel) corresponding to the histogram with the highest peaknear unity coherence. Fig. 5(a) shows the differential interfero-gram with the DEM optimally repositioned, whereas Fig. 5(b)shows the differential interferogram when the DEM is movedfrom its optimal positioning. The effect on SNR is evident,mainly over the mountainous areas, whereas no appreciablechanges on the area of the city are evident, as expected fromwhat is sketched in Fig. 3.

Fig. 4. Histograms of the interferometric coherence for the selected slice ofthe Las Vegas site. The plots refer to shifts of the DEM-derived phase w.r.t. themaster image by −10, −5, 0, 5, and 10 IM pixels in the slant range direction(one pixel corresponds to the IM range sampling step: � 7.9 m). Positive valuescorrespond to shifts toward the far range.

These results were obtained within the context of an ESAEuropean Space Research and Technology Centre (ESTEC)contract (#15609/01/NL/SF); the DEM-derived phase was gen-erated with a software developed by RSL (Zurich), and co-herence maps with a software were developed by SARMAP(Switzerland).

IV. WS/WS INTERFEROMETRY

The generation of a WS/WS interferogram is performed ona look-by-look basis. Each interferometric look is obtainedby multiplying one look of the first image by the complexconjugate of the corresponding look in the second image,after common band filtering and DEM-derived topographicphase removal. Multiplication by topographic phase warps thespectral support to get the best match and reduce the phasenoise. Differently from IM/WS interferometry, in WS/WSinterferometry, both images have a narrow spectral domain(see Fig. 1); thus, there is scarcely room to increase S/N ratioin mountainous areas.

The sampling grid is that of the master image and, as inthe ESA WSS format all the looks are sampled on a coherentgrid, it is a straightforward matter to average the interferometriccomplex looks. Mosaicking is no problem also when differentSS are considered; even if multilook interferogram will resultwith an azimuth amplitude modulation effect (scalloping [7]),interferogram phase experiences only a slight modulation inS/N ratio. Because of the partial look overlap, due to nonper-fect timing pattern synchronization, it can be very difficult orimpossible to remove such scalloping effects.

Requisites for good-quality interferograms are usually geo-metric correspondence of the stereo pair, small baseline, andsmall time separation between the two acquisitions, althoughthis last condition depends strongly on the target variability.

ScanSAR/ScanSAR interferometry requires one more, verystringent, condition to be met: the scanning patterns of the two

380 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 3, NO. 3, JULY 2006

Fig. 5. ASAR WS-IM differential interferograms of the area around LasVegas, obtained with (a) the optimal DEM positioning and (b) a DEM displace-ment of � 25 m in azimuth, � 24 m in range.

acquisitions must be “synchronous.” If acquisitions from thesame relative orbit are used, the Doppler rates will be verysimilar, and the spectral support will have the same slope in thet− f plane. However, the time localization of the “lozenge” inFig. 1 will depend on the timing of the burst.

Even supposing it is possible, at present, no attempt hasbeen made to plan interferometric (with synchronous scanningpatterns) WS acquisitions. This means that random timing hasto be assumed; the probability that the scanning patterns in ahypothetical stereo pair overlap by more than αTD is

P (overlap > α) = (1 − α) · 2TDTR

, 0 < α < 1. (4)

A lower limit for the exploitable bandwidth cannot be fixedin a general case, as baseline and temporal decorrelations arealso involved. Obviously, the azimuth resolution of the resultinginterferogram is 1/α times coarser than that of the contributingWS images. Experimental results on many sites have shownthat α ≥ 0.1 is the minimum required to allow the appearanceof interferometric fringes.

Thus, if we use the previous limit and the typical valuesfor TD and TR in a WS mission (TD/TR � 0.155−0.183),28%–34% of success (depending on the SS) is expected.

Pattern synchronization is much less of a problem [1] forRADARSAT ScanSAR Narrow Mode, which has only two SS.

Verifying that the scanning patterns of two WS acquisitionsoverlap enough to allow meaningful interferometric processingis very simple for ENVISAT ASAR, as its DORIS-derivedorbits and its data timing have proved precise enough. Giventhe start time t1 of one burst in the first data set and, through theprecise orbit, the corresponding sensor position, it is a simpletask [12, Ch. 6] to compute the location on the ellipsoidalearth of a target (P ) at an assigned slant range. Then, usingthe precise orbit for the second acquisition, it is possible tocompute the time t12 at which the same ground point is imagedin the second acquisition. As focused data are usually referredto their zero Doppler position, zero Doppler is assumed both inthe forward and in the reverse computations [see Fig. 6(a)]. Ift2 is the start time of the last burst in the second data set beforet12, the scanning cycles are mispositioned by t12 − t2 (“cycle

Fig. 6. (a) Identification of temporal overlap of the two scanning patterns.(b) Relation between the cycle overlap of three acquisitions.

overlap”). TR and TD’s are assumed constant throughout all theacquisitions.

A usual problem in selecting candidate WS stereo pairs (formultiple baseline application, for example) is to screen allavailable acquisitions with the same relative orbit over the samearea. If the cycle time overlap is computed between one data setand all the others, it is simple to compute the cycle time overlapbetween any couple in the set.

If t12 − t2 is the cycle overlap between acquisitions 1 and2, and t13 − t3 is the overlap between acquisitions 1 and 3, itis evident [see Fig. 6(b)] that the overlap between 2 and 3 ist23 − t3 = t13 − t3 − (t12 − t2). If the result is negative, it isenough to add TR. Table II shows normal baselines and cycleoverlaps measured with real data sets; cycle overlap is writtenas a fraction of cycle time: ρcyc = (t12 − t2)/TR. What reallymatters, however, is the overlap between the active parts of thecycle, i.e., the dwell times. The dwell time overlap ρD can beobtained simply from ρcyc

ρD =(1 − TR

TDρcyc

), if 0 < ρcyc <

TD

TR

ρD =(1 − TR

TD(1 − ρcyc)

), if

(1 − TD

TR

)< ρcyc < 1

ρD = 0, elsewhere.(5)

In case of multiple missions, it is not possible to combine ρD’s,but it is always possible to combine ρcyc’s and then computethe required ρD’s.

GUCCIONE: INTERFEROMETRY WITH ENVISAT WIDE SWATH SCANSAR DATA 381

TABLE IICYCLE OVERLAPS AND NORMAL BASELINES FOR FIVE WS ACQUISITIONS OVER BAM, IRAN (RELATIVE ORBIT 306).

THE REFERENCE MISSION IS THAT OF FEBRUARY 4, 2003

Fig. 7. ASAR WS-WS differential interferogram (low-resolution SRTMDEM used) of the area around Bam, obtained with the missions of September 2,2003 and June 8, 2004 (before and after the earthquake). The normal baselineis � 100 m, the spectral overlap � 85%. Image has been geocoded, and theabsolute position is 27◦/31◦N, 57◦/61◦E. Sampling steps are 90 m in latitudeand longitude.

Some tests have been carried out over desert areas, wherethe target small variability assures high coherence over longtime intervals. DEM derived from the SRTM missions wereused, and meaningful fringes were obtained even with highbaseline. Here, results obtained with five acquisitions over thearea of Bam, Iran are shown. Fig. 7 shows the differentialinterferogram. The unfortunate cause for so much interest wasthe earthquake of December 26, 2003.

V. CONCLUSION

ASAR wide swath complex data can be used for interfer-ometric applications even if the synchronization of the scan-ning pattern is, at present, the major limit in generating goodScanSAR interferograms. However, even considering purelyrandom timing, a fair percentage of success is expected. Ex-perimental results agree with theory or, sometimes, are better,suggesting that it is possible for the mission control to im-

prove the percentage of WS acquisitions with interferometriccapabilities.

The accuracy of ENVISAT orbit and timing information hasproved good enough to support both mixed-mode and WS/WSmode interferometry without autofocusing procedures, even ifa precise DEM (with small enough altitude and positioningerrors) is required to reduce noise decorrelation.

ACKNOWLEDGMENT

This work is the offspring of several ESA contracts un-dertaken in collaboration with the Politecnico di Milano. Theauthor wishes to thank C. Cafforio and M. Guarnieri for theirhelpful discussions.

REFERENCES

[1] J. Holzer and R. Bamler, “Burst-mode and ScanSAR interferometry,”IEEE Trans. Geosci. Remote Sens., vol. 40, no. 9, pp. 1917–1934,Sep. 2002.

[2] A. K. Gabriel and R. M. Goldstein, “Crossed orbit interferometry—Theory and experimental results from SIR-B,” Int. J. Remote Sens., vol. 9,pp. 857–872, May 1988.

[3] F. Gatelli, A. M. Guarnieri et al., “The wavenumber shift in SAR infer-ometry,” IEEE Trans. Geosci. Remote Sens., vol. 32, no. 4, pp. 855–865,Jul. 1994.

[4] A. M. Guarnieri and F. Rocca, “Combination of low- and high-resolutionSAR images for differential interferometry,” IEEE Trans. Geosci. RemoteSens., vol. 37, no. 4, pp. 2035–2049, Jul. 1999.

[5] J. Tavernier, J. P. Granier, C. Jayles, P. Sengenes, and F. Rozo, “Thecurrent evolutions of the DORIS system,” presented at the COSPAR02,A-02654.

[6] A. M. Guarnieri and C. Prati, “ScanSAR focusing and interferome-try,” IEEE Trans. Geosci. Remote Sens., vol. 34, no. 4, pp. 1029–1038,Jul. 1996.

[7] A. M. Guarnieri and P. Guccione, “Optimal ‘focusing’ for low reso-lution ScanSAR,” IEEE Trans. Geosci. Remote Sens., vol. 39, no. 3,pp. 479–491, Mar. 2001.

[8] R. Lanari, S. Hensley, and P. A. Rosen, “Chirp z-transform basedSPECAN approach for phase-preserving ScanSAR image generation,”Proc. Inst. Elect. Eng., vol. 145, no. 5, pp. 254–261, Oct. 1998.

[9] F. Wong, D. Stevens, and I. Cumming, Phase Preserving Focusing ofScanSAR Data With a Modified Range Doppler Algorithm, pp. 559–560,Jul. 1999.

[10] A. M. Guarnieri, P. Guccione, P. Pasquali, and Y. Desnos, “Multi-mode ENVISAT ASAR interferometry: Techniques and preliminaryresults,” Proc. Inst. Elect. Eng.—Radar, Sonar, Navigat., vol. 150, no. 3,pp. 193–200, Jun. 2003.

[11] B. Rabus, M. Eineder, A. Roth, and R. Bamler, “The shuttle radar topo-graphic mission—A new class of digital elevation models acquired byspaceborne radar,” ISPRS J. Photogramm. Remote Sens., vol. 57, no. 4,pp. 241–262, Feb. 2003.

[12] G. Schreier, SAR Geocoding Data and Systems. Karlsruhe, Germany:Wichmann, 1993.