RADARSAT ScanSAR Interferometry

R. Bamler, D. Geudtner, B. Schattler, P.W. Vachon’, U. Steinbrecher, J. Holzner, J. Mittermayer, H. Breit, and A. Moreira

German Aerospace Center (DLR) P.O. Box 11 16, D-82230 Wessling, Germany

Phone: +49-8153-28-2673 Fax: +49-8153-28-1420 e-mail: richard.bamler@dlr.de

ABSTRACT

ScanSAR interferometry is an efficient technique for topo- graphic mapping or surface change monitoring of large areas. The feasibility of ScanSAR interferometry has been demonstrated in theory and simulations before. In this paper we show the first ScanSAR interferogram from real RADARSAT data. In a first example, an interferogram derived from two ScanSAR data sets is presented. In a second example, an interferogram is formed from a Scan- SAR a one strip-map data set. In this case, the azimuth synchronization problem involved in the acquisition of ScanSAR interferometric pairs is circumvented. Different interferometric ScanSAR algorithms are discussed.

INTRODUCTION

The RADARSAT SAR instrument provides various im- aging modes, such as the strip-map mode with Standard (Sl-S7), Wide (Wl-W3) and Fine (Fl-F5) beams and various ScanSAR modes [l]. The ScanSAR mode of op- eration allows for an increase of swath width at the ex- pense of azimuth resolution by imaging several sub-swaths (beams) in a burst mode fashion quasi-simultaneously [2][3]. RADARSAT is the first space-borne system to operate in ScanSAR mode that is also able to provide suitable data for ScanSAR interferometry. There are dis- tinguished ScanSAR Narrow and Wide modes. The Scan- S A R Narrow modes combine beams W1 and W2 for the ‘ScanSAR Narrow Near’, or W2, S5, and S 6 for the ‘ScanSAR Narrow Far’ modes, respectively. Both narrow modes cover a swath width of about 300 km. The Scan- S A R Wide modes combine beams W1, W2, W3, and 57 or Wl , W2, S5, and S6 providing swath widths of 500 km and 450 km, respectively.

RADARS AT was not originally designed for repeat-pass InSAR. Both the orbit accuracy and the repeat cycle of 24 days are not favorable in this respect. On the other hand, RADARSAT’s 30 MHz fine-resolution mode combined with large incidence angles (= 49’) gives a critical baseline of as large as 6 km [4]. First results on interferometry using RADARSAT’s strip-map modes have been reported in [5][6]. Also ice sheet motion has been measured from RADARSAT InSAR data [7].

Although radiometric imaging of large areas was the original motivation for ScanSAR, its wide swath also supports efficient interferometric mapping. Some attrac- tive properties are the more economic use of ground con- trol points for calibration of the imaging geometry and the

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’Canada Centre for Remote Sensing (CCRS) 588 Booth St., Ottawa, Ont., K1A OY7, Canada Phone: 613 995-1575 Fax: 613 947-1385 e-mail: paris.vachon@ccrs.nrcan.gc.ca

reduced need for post-processing to mosaic large DEMs. ScanSAR data, however, have signal and spectral proper- ties that complicate interferometric processing compared to conventional strip-map data. This fact, together with the current lack of phase preserving complex ScanSAR products are the main reasons that ScanSAR interferome- try has never been demonstrated with actual ScanSAR data to date. Experiments using ScanSAR data simulated from ERS strip-map data have been reported in [SJ[9].

In this paper, we discuss the interferometric processing of RADARSAT ScanSAR data. We have processed and evaluated suitable InSAR image pairs over Bathurst Island, Northwest Territories, Canada. To our knowledge, in this paper we show the first ScanSAR interferograms produced from actual RADARSAT ScanSAR data.

INTERFEROMETRIC ScanSAR PROCESSING

The signal and spectral properties of ScanSAR burst-mode data are discussed elsewhere [S][9] [ 101. Interferometric processing of burst-mode data is different from strip-mode data processing in several respects.

Azimuth Scanning Pattern Synchronization

Each resolution element on the ground is ‘seen’ by the radar whenever a burst of its echoes is received. The se- quence of bursts (radar on) and pauses (radar off) is re- ferred to as the ‘azimuth scanning pattern’. For an inter- ferometric image pair to be coherent the azimuth scanning patterns of both acquisitions must be synchronous, i.e. the same point on ground must be imaged from the same along-track positions both times. Synchronization cannot be done during data acquisition for RADARSAT. There- fore, signal processing must take care of the synchroniza- tion. A post-processing filter operation has been proposed in [SI. We adopted the following pre-processing manipu- lation instead [lo]. In a first step, a small azimuth portion of each data set is processed to an image. The mutual azi- muth shift is then estimated from the two images. This allows for azimuth co-registration of the two burst-mode raw data sets (to an accuracy of one range line), i.e. along- track referencing of the two azimuth-scanning patterns. Finally, only the range lines that have companions in the other data set‘s on-cycle are kept for further processing; all the others are discarded. The more the burst cycles of the two data sets overlap, the fewer are the range lines that must be discarded and the better the final azimuth resolu- tion will be. If the two scanning patterns are mutually exclusive, i.e. bursts in one data set match pauses in the

other, the data sets cannot be used for interferometry. For this reason, the two-beam ‘ScanSAR Narrow Near’ mode of RADARSAT is preferred for interferometry; mutually exclusive scanning patterns are less likely.

Phase-Preserving Burst-Mode Processing

Several algorithms have been proposed for phase preserv- ing processing of burst-mode data [81[9][10][11][121. For a systematic overview of burst-mode processing strategies it is helpful to conceptually separate the processing chain into range and azimuth processing. The first step includes range compression, range cell migration (RMC) correc- tion, and secondary range compression (SRC), leaving the second step as a purely 1-D azimuth compression (AC).

R Range Processing

RI Azimuth Time Domain

The classical approach for burst-mode range processing attempts to correct for RCM in the azimuth time domain either by explicit range interpolation or by introducing an azimuth dependent linear phase term into the range com- pression filter. These algorithms can only correct for the linear part of the RCM.

R2 Use of Standard High Precision Strip-Mode

Standard SAR processing algorithms like range-Doppler, wavenumber domain, or Chirp Scaling can be used for range processing of burst-modes data [lo][ 121. Three approaches are possible:

R2. I

Each burst of range lines is processed separately by a stan- dard processor whose azimuth compression has been dis- abled. This method is computationally efficient and has been adopted by [8] and for use in the Extended Chirp Scaling (ECS) Algorithm [12]. However, often the bursts must be supplemented by a number of range lines con- taining zeroes to the next power of two.

R2.2

Since during range processing (almost) no energy leakage in azimuth occurs, several bursts can be concatenated and processed simultaneously by the standard S A R processor. After range processing the bursts can be easily separated. This method is more efficient than R2.1, since arbitrarily long FFTs can be used and zero padding to meet the power-of-two requirement is almost negligible.

R2.3 Coherent Multiple Burst Range Processing

A less efficient algorithm for range and azimuth process- ing has been proposed in [lo]: the inter-bursts pauses are filled with zeroes such that the burst train resembles a standard strip-map mode raw data set where some range lines (the pause lines) have been set to zero. The resulting

Processors

Single Burst Range Processing

Independent Multiple Burst Range Processing

coherent burst train is then processed in range and azimuth just like a standard strip-mode raw data set (see A5).

A Azimuth Compression (AC)

A1 SPECAN

The classical SPECAN algorithm is computationally effi- cient and can be made phase-preserving. The focussed burst image, however, exhibits a range dependent azimuth sample spacing, known as fan-shaped distortion, and, hence, requires an additional interpolation step.

A2 Azimuth Variant Filtering

After a burst has been range processed following the strat- egy of R2. I standard azimuth compression is applied. The result is a coherent superposition of several shifted replicas of the desired burst image. An azimuth band-pass filter whose center frequency varies with azimuth position is finally required to separate the correct result [8].

A3 Extended Chirp Scaling (ECS)

The high precision ECS algorithm [ 121 is a combination of Chirp Scaling for accurate range processing and SPECAN for azimuth processing. An azimuth scaling step is added to equalize the frequency rates of the azimuth chirps. Through this trick the fan-shaped distortion of the classical SPECAN is avoided, no interpolation is required, and the final azimuth sampling grid can be chosen arbitrarily. This allows also for mosaicking the processed sub-swaths to the complete ScanSAR image without further interpolation.

A4 Time Domain AC

Since the bursts are usually short (e.g. 100 range lines), a straightforward time domain azimuth correlation is an alternative to frequency domain methods. Although not as efficient, it is most easily implemented, and allows for a free choice of the output sample spacing.

A5 Coherent Multiple Burst Processing

If the bursts have been range processed according to R2.3, standard azimuth compression can be applied to the burst train. The result is equivalent to coherent superposition of the (correctly co-registered) individual burst images [lo]. As a consequence the azimuth impulse response function exhibits strong interference modulation (see below).

I ScanSAR Interferogram Formation

With the phase-preserved, burst mode images (complex looks) available, there are two options for further inter- ferometric processing:

I1 Single Burst Interferogram

Given the individual complex burst images of the master data set and the corresponding ones of the slave data, small interferograms are generated from each pair of companion burst images. These are referred to as ‘burst interfero-

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grams’ or ‘interferometric looks’. In a second step, the burst interferograms are properly shifted in azimuth and are concatenated or (in case of overlap) coherently added to form a full interferogram of the sub-swath under con- sideration. With the usual scanning scenarios several (NL) of these burst interferograms overlap at every point of the final interferogram. This leads to a phase noise reduction equivalent to an NL -look processing.

Note that processing such burst interferograms requires some care: in order to co-register a slave burst image to its master companion the time-variance of the burst image spectrum must be considered. Standard interferometric processing systems assume a constant azimuth center fre- quency (Doppler centroid), while in burst-mode data the look center frequency varies linearly with azimuth. To circumvent this problem either oversampling (as in 12) or an azimuth-variant interpolation kernel must be used.

12 Multiple Bursts Interferogram

The burst images from each beam are added coherently before interferogram formation. This is done automati- cally, if algorithms R2.3 and A5 have been used. The result is an image with a higher bandwidth but having a ‘nasty’ oscillating azimuth impulse response function [ 101 The interferogram from the two high bandwidth images is then formed. Subsequent azimuth averaging of adjacent inter- ferogram samples, i.e. low-pass filtering, reduces the bandwidth to that of a single burst and removes the oscil- lations in the impulse response. The intermediate increase in bandwidth requires redundant sampling of each burst image and increases the data volume input to the inter- ferometric processor. On the other hand, at the higher spectral resolution the spectrum of this data resembles strip-map spectra (except for periodic gaps) and, therefore, conventional co-registration and re-sampling techniques can be applied. However, the estimation of the mutual azimuth shift requires some care: due to the modulation of the impulse response function multiple local correlation maxima will occur. Also, coherence as a function of azi-

essed to an average of the actual Doppler centroid frequen- cies to avoid spectral decorrelation in azimuth.

ScanSAR Image

Figure 2 shows a full three-beam ScanSAR Narrow Far (W2, S5, S6) image with four looks in range and two looks in azimuth (due to the scanning strategy) processed by ECS. The final image resolution is about 80 m. Scalloping has been removed by estimating the azimuth antenna pat- tern from the data itself.

Burst-Mode Inter$erograms

We adopted option 12 to form the RADARSAT ScanSAR interferograms shown in this paper. Procedure 12 guaran- tees compatibility with standard interferometric processing systems, enabling us to use DLR’s InSAR processor GENESIS [ 141 without major ScanSAR-specific modifica- tions.

In all cases, we selected one sub-swath, focussed 40 of the more than 200 available bursts, and added them coher- ently. The azimuth sampling grid defined by the largest PRF lead to an azimuth oversampling factor of about 14 (with respect to the original azimuth resolution), allowing the use of a conventional co-registration method.

Interferometric Combination of RADARSAT ‘ScanSAR Narrow Near’ Data Sets

From a ScanSAR Narrow pair we selected sub-swath W1 for further processing. The bursts are 112 range lines long. The relative shift of the azimuth scanning pattern between corresponding bursts in each image was 45 lines, leaving 67 range lines for interferogram formation. Therefore, after synchronization of the azimuth scanning pattern, each burst has a bandwidth of about 100 Hz, giving an azimuth resolution of about 70 m. Figure 1 shows the inter- ferometric phase image after flat earth phase removal.

Interferometric Combination of RADARSAT ‘ScanSAR Narrow Far’ and Standard Beam Data Sets

muth misregistration exhibits multiple maxima.

RADARSAT ScanSAR INTERFEROMETRY RESULTS

In a second experiment, we combined Standard beam S5 of a conventional (strip-map) image with sub-swath S5 from the a ‘ScanSAR Narrow Far’ (W2, S5, S6) data set to

Two different ScanSAR processors have been developed at DLR and have been used for RADARSAT data: i) an ECS processor (using R2.1 and A3) [12] with full radio- metric correction both in elevation and in azimuth (scal- loping correction), ii) a time domain processor using DLR’s standard Chirp Scaling Processor BSAR [13] for ScanSAR interferometry (R2.2 and Ad). Standard Doppler centroid estimators have been used. The spectral distortion inherent in burst-type data averages out, if the estimation window is large enough in azimuth (e.g. 10.000 range lines). The interferometric image pairs have been proc-

form an interferogram. The strip-map raw data was syn- chronized to the azimuth scanning pattern of the ScanSAR sub-swath by removing non-overlapping (radar off) range lines and has been processed like the burst-mode data. Fig. 3 shows the interferometric phase image.

SUMMARY

In this paper, we have demonstrated the feasibility of ScanSAR interferometry using RADARSAT data. Scan- S A R interferometry is interesting for efficient inter- ferometric mapping. In addition, the interferometric com- bination of ScanSAR data with conventional strip-map

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data increases the number of suitable InSAR data sets, especially for long term monitoring.

ACKNOWLEDGEMENTS l%is work was carried out in the context of RADARSAT ADRO Project #500. The original RADARSAT data are copyright CSA 1996, 1997, and 1998. DLRs research and development activities on RADARSAT ScanSAR interfe- rometry were partially funded by the former DARA in the framework of the GEMSAR project. B. S.’s work was partially supported by the German-Canadian Scientific- Technical Cooperation Programme.

REFERENCES [l] R. K. Raney, A. P. Luscambe, E. J. Langham, S. Ah- med, “RADARSAT”, Proc. IEEE, vol. 79,839-849,1991. [2] R. K. Moore, J. P. Claassen, Y. H. Lin, “Scanning spaceborne synthetic aperture radar with integrated radi- ometer”, IEEE Trans. AES, vol. 17,410-420, 1981. [3] K. Tomiyasu, “Conceptual performance of a satellite borne, wide swath synthetic aperture radar”, IEEE TGaRS,

[4] P. W. Vachon, D. Geudtner, A. L. Gray, R. Touzi, “ERS-1 Synthetic Aperture Radar repeat-pass interfe- rometry studies: Implications for RADARSAT”, Can. J. Rem. Sens. vol. 21,441-445, 1995. [5] Vachon, P. W. Geudtner, D., “RADARSAT SAR interferometry”, h t ~ : / / W W W . ~ S . N c a n . g C . ~ ~ ~ t ~ ~ r ~ andinter fer/interfre.html [6] D. Geudmer, P. W. Vachon, K. E. Mattar, A. L. Gray, “RADARS AT Repeat-pass SAR Interferometry”, Roc. IGARSS’98, 1635-1637, Seattle, USA, 1998. [7] A. L. Gray, K. E. Mattar, P. W. Vachon, “RADARSAT interferometric SAR results obtained over Antarctic ter- rain”, CEOS workshop, ESA-ESTEC, Noordwijk, 1998. [8] A. Monti Guamieri, C. Prati, “ScanSAR focusing and interferometry”, IEEE TGaRS, vol. 34,1029-1038,1996. [9] A. Monti Guarnieri, C. Prati, and F. Rocca, “Interfe- rometry with ScanSAR”, EARSeL Newsletter, Dec. 1994. [lo] R. Bamler, M. Eineder, “ScanSAR processing using standard high precision SAR algorithms”, IEEE TGaRS.,

[ l l ] I. G. Cumming, Y. Guo, I;. Wong, “A comparison of phase-preserving algorithms for burst-mode S A R data processing”, Roc. IGARSS97, Singapore, 73 1-733, 1997. [12] A. Moreira, J. Mittermayer, R. Scheiber, “Extended Chirp Scaling algorithm for air- and spaceborne S A R data processing in stripmap and S m S A R image modes”, IEEE

[13] H. Breit, B. Schittler, U. Steinbrecher, “A High- Precision Workstation-Based Chirp Scaling SAR Proces- sor”, Proc. IGARSS’97, Singapore, 46547,1997. [14] M. Eineder, N. Adam, “A Flexible System for the Generation of Interferometric S A R Products”, IGARSS’97, Singapore, 1341 - 1343,1997.

vol. GE-19, 108-116, 1981.

vol. 34,212-218, 1996.

TGaRS, vol. 34, 1123-1 136, 1996.

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L ds Figure 1: ScanSAlUScanSAR (‘Narrow Near’: Wl,W2) interferogram. Interferometric phase of beam W1.

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baa s6

bea s5

bea

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Figure 2: Full ‘ScanSAR Narrow Far’ (W2,S5,S6)- amplitude image (green and red firames correspond to figures 1 and 3, respectively)

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