I-PAF SRTM X-SAR Processing Chain: Algorithms and Analysis of First Results

Transcription

1 I-PAF SRTM X-SAR Processing Chain: Algorithms and Analysis of First Results P. AMMENDOLA(*), E. LOPINTO(**),C. MARZO (***), G. MILILLO (***), G. RICCOBONO (***), G. R. VERDONE (**), R. VIGGIANO (**) (*)ASI Viale Liegi 26 Rome - ITALY Tel: , Fax : , ammendola@asi.it ** Telespazio S.p.A. Centro Spaziale Matera- Contrada Terlecchia Matera - ITALY Tel , Telefax ettore_lopinto@telespazio.it, gianrocco_verdone@telespazio.it, renata_viggiano@telespazio.it * **ASI - Centro di Geodesia Spaziale - Contrada Terlecchia Matera - ITALY Tel , Telefax Telex marzo@asi.it, milillo@asi.it *** Telespazio S.p.A. - Via Tiburtina Rome - ITALY Tel , Telefax Telex gianni_riccobono@telespazio.it INTRODUCTION From 11th to 22nd February 2000, the Shuttle Radar Topography Mission (SRTM) carried out two SAR interferometers (C and X band) to acquire data and generate a new complete and more accurate map of Earth's surface. The Endeavour Space Shuttle was equipped by radar sensors developed by ASI (Italian Space Agency, Italy), NASA (United States) and DARA (Germany). All land areas between approximately +/-60 will be processed in order to obtain a Digital Elevation Model (DEM) with a quality never previously obtained on a global data set: absolute (relative) vertical accuracy better than 16 (6) m, and absolute (relative) horizontal accuracy better than 20 (15) m. The data will also be vital to environmental research, geology, glaciology, agriculture and many other fields. Telespazio, under contract award by the Italian Space Agency, has developed the SRTM X-SAR Processing Chain completely integrated in the Italian Processing and Archiving Facility (IPAF). This work gives a description of the Standard and Interferometric products generated by the SRTM System, describes in details the algorithmical steps of the interferometric processing chain and gives some example of DEM generated during the mission (Donw-link data) and the DEM of Gargano, South Italy generated using post-flight PADR data XSAR-SRTM PRODUCT DESCRIPTION The SRTM system is able to produce two categories of products: X-SAR Standard Products, including those from the SRL-1 and SRL-2 mission, that are fully focussed, single band SAR image X-SAR Interferometric Products, that are Altitude and Elevation Products derived starting form a pair of focused images already coregistered X-SAR Standard Products Annotated Raw Data (X-SAR.SAR.RAW) This product contains the X-SAR raw data and the ancillary data transcribed from D1 tape and reformatted in a computer readable format (8 bits per sample). Single-Look Slant range Complex (X-SAR.SAR.SSC) This product contains the complex image obtained by SAR processing the raw data without any ground projection and amplitude detection. The SSC (Single- Look Slant-Range Complex) processing foresees the following steps: raw data preprocessing (data unpacking, missing lines padding, data window position correction, raw data bias, gain unbalance and quadrature correction) corners localization (using orbit and sensor parameters) doppler parameters estimation including centroid ambiguity. RAW data are range focused and then segmented along both directions in small and slightly overlapping blocks which are azimuth focused with a ω-k class algorithm and then exactly joined together, avoiding the introduction of any phase discontinuity. During the frequency domain processing the image is also geometrically deskewed to put data in a zero doppler axis. Multilook Ground range Detected Image (X- SAR.SAR.MGD). This product contains a detected image. The generation of MGD products requires additional computation mainly for slant to ground projection, range and azimuth

2 multilooking and data detection with associated oversampling by a factor 2. Geocoded Ellipsoid Corrected (X-SAR.SAR.GEC). This product contains ellipsoid corrected image data related to a full scene of the input MGD product. The product is obtained by resampling the input image onto output coordinated axes defined by a selected cartographic projection. Geocoded Terrain Corrected (X-SAR.SAR.GTC). This product contains terrain corrected image data related to a full scene of the input MGD product. With respect to the GEC product, in the GTC product generation the SAR inherent geometric terrain distortion is restored to the best X-SAR Interferometric products SSC registered Interferometric couple processing is based on the generation of two SSCs simply followed by data coregistration. The slave channel is focused with the same parameters of the master while the couple coregistration is based on segmentation in azimuth direction and application of a first degree warping function on each segment. The warp coefficients are obtained via master/slave patches oversampled cross correlation and the warp application (i.e. slave interpolation) uses a couple of weighted truncated sinc, with the azimuth one placed on actual doppler centroid frequency. Mosaicked ITHD-2 (Interferometric Terrain Height Data, Level 2) The ITHD-2 product contains interferometric derived altitudes, vertically referred to an ellipsoidal surface and horizontally referred to a latitude, longitude grid. Both the horizontal and vertical references are defined in the WGS84 ellipsoid so the ITHD-2 will contain ellipsoidal geodetic heights in a geodetic lat,lon grid. The Mosaicked ITHD-2 is derived starting from the X band interferometric ITHD-2 heights, mosaicked with external height data and, in the zones where exists a overlap in the X band swaths, with ITHD-2 data coming from different orbits. Mosaicked HEM (Height Error Map) The Mosaicked HEM (Height Error Map) contains the errors of the Mosaicked ITHD-2 heights product, coregistered with the ITHD-2 and hence expressed in the same reference (WGS84) used for such data. It will be derived starting from the X band interferometric height error map, mosaicked with same rules as the Mosaicked ITHD-2. DEM (Digital Elevation Mode The DEM (Digital Elevation Mode contains elevations, vertically referred to a surface very close to the MSL (Mean Sea Leve, i.e. the WGS84 geoid and horizontally referred to a latitude, longitude grid. The horizontal reference is defined in the WGS84 ellipsoid so the DEM will contain elevations above the geoid in a geodetic lat,lon grid, with elevations measured along the local gravity direction. Mosaicked DEM The Mosaicked DEM is derived starting from the X band interferometric ITHD-2 heights converted into elevations, mosaicked with external elevation data and, in the zones where exists a overlap in the X band swaths, with interferometric data coming from different orbits. The main specifications of height data products are summarized in this table. Parameter Value Accuracy(*) Horizontal Datum Vertical Datum Posting Absolute Horiz Accuracy 90%Circular Error 20m Relative Horiz Accuracy 90% Circular Error 15m Absolute Vert Accuracy 90% Linear Error 16m Relative Vert Accuracy 90% Linear Error 6m Geodetic latitude, longitude expressed in WGS84 ellipsoid Latitude value belong to [-60, 60 ] Longitude values belong to [-180, 180 ] Geodetic Ellipsoidal elevations referred to WGS84 ellipsoid (ITHD2, HEM) or geoid surface (DEM) Latitude: 1 arcsec Longitude: 1 arcsec when longitude is in [-50,50 ] 2 arcsec outside (*) Specifications applicable only in areas, which are not affected by the layover or shadowing, effect. It does not apply to HEM. AODA DATA PROCESSING The X-SAR radar has been operated as a fixed-baseline interferometer. The two antennas are mounted on a 60m deployable mast structure. It is possible that dynamics (due to manoeuvres, gravitational or temperature variation effects) changed length and orientation of the baseline during Shuttle fly. Since the great sensibility of the height determination respect the baseline knowledge (in a very rough approximation they share the same relative error, so to obtain a 1000 meter height with ±5m accuracy, you have to measure the nominal 60 meter baseline with ±0.3m accuracy, i.e. few centimetres) a component of the SRTM system, the Attitude and Orbit Determination Avionics (AODA), has been devoted to provides accurate measurement of baseline parameters.

3 By the processing of PADR files (Position Attitude Data Record) generated from the AODA system, very accurate measurements of baseline length and tilt angle are computed. Since PADR data is referred on Shuttle local coordinate systems, the processing is mainly based on coordinates conversions using repeated application of rotation matrices and translation vectors, until the master electric antenna center and baseline are all expressed into WGS84 rectangular coordinates. INTERFEROGRAM/COHERENCE GENERATION AND FILTERING The two coregistrated SSC images (named Master m and Slave s images) are multiplied in order to obtain the complex interferogram I. The interferometric phase is defined as Φ(r,c) = Tan -1 ( Imaginary ( I (r,c) ) / Real ( I (r,c) ) ) The following interferometric filters are applied to the focused images and to the complex interferogram. Common band filtering. The master and slave images could be filtered before multiplication, to eliminate the contribution coming from the spatial decorrelated spectrum part [R1]. The processor operates convolving each one of the two images with two non-recursive (FIR), complex, digital filters tuned on the fringe frequency that cut from the spectra the non common part, hence resulting in a coherence increase. Caltone removal. The two images have been filtered in order to eliminate the contribution of the caltone that produces a fringe frequency clearly visible in the phase of the interferogram. The caltone removal is done via a notch FIR filter that eliminates the caltone frequency on the master and slave focused images before the interferogram formation, avoiding the introduction of artefacts on the interferometric phase. The caltone effect, clearly shown in the Fig. 1, produces fringe frequency which the unwrap try to reconstruct as a phase ramp with a very dangerous effect. Fig. 1: an example of a piece of coherence image before and after the caltone removal (Data Take ) Layover filtering. Another source of noise for the interferometric phase is the contribution coming from the layover zones [R1]. The complex interferogram could be filtered in order to eliminate from its spectrum the portions corresponding to the layover zones, so improving the phase in such zones. However, layover affects only the very mountainous areas acquired at low incidence angles (which is quite far from the SRTM case). Interferogram demodulation. The interferometric phase coming from known sources (earth ellipsoid or a DEM) could be subtracted from the interferogram in order to flatten it and hence simplify the unwrapping processing. The complex interferogram is demodulated in such a way that: I demod (r,c) = I (r,c) e -Φ T (r,c). Coherence image generation. The coherence image is evaluated for each interferometric couple. The coherence is an image of correlation defined as [R1]: ρ( r, c) = r + N / 2 r r + N / 2 r c+ N / 2 a k = r N r / 2 l = c N a / 2 c+ N / 2 a k = r N r / 2 l = c N a / 2 + m( s( e m( 2 r + N / 2 r Φ T ( k, l ) c+ N / 2 a k = r N r / 2 l = c N a / 2 s( where the exponential that demodulates the numerator interferogram takes into account the so called topographic factor, which avoids any coherence loss coming from the terrain geometry and allows a more accurate estimation of the true coherence. If a DEM is allowable (for interferometric phase demodulation and for the topographic factor computation, as we have seen above), it s also used to evaluate a mask identifying in the coherence image the layover and the shadowing areas. Multilook. The last operation is the multilooking done for reducing the noise and for resampling the data from natural spacing to one closer to the final 1 arcsec. Such filtering is done on the interferogram (complex multilooking) and on the coherence image. PHASE UNWRAPPING Reconstructing the terrain topography requires the knowledge of the phase values together with the unknown integer multiples of 2π. The reconstruction of a function given its values modulo 2π is known as phase unwrapping. We use Costantini Method ([R3], [R4]) that exploits the fact that the neighbouring pixels differences of the unwrapped phase can be estimated with a potential error which is an integer multiple of 2π. This suggests the formulation of the phase unwrapping problem as a global weighted minimization problem for the integer error variables: the weighted deviation of the estimated and the unknown unwrapped phase neighbouring pixels differences is minimized with the constraint that the two functions must differ by integer multiples of 2π. 2

4 IMAGE GEOMETRIC CALIBRATION The unwrapping processing (as any differential equation solution) defines the phase image except an offset. This value can be calibrated comparing the unwrapped phase with the true phase geometrically determined on a set of ground control points (GCP). Such points can be obtained from GPS measures, from a DEM or simply using sea areas. To allow the calibration on sea areas, each Data Take acquisition starts and ends on sea so it is always possible to use these extremes as a high quality GCP set. The only care which shall be held is not to confuse the sea level with the earth ellipsoid (in other words it is necessary to remove the tide and add the geoid height) and in interpolation of values between the two extremes. This technique can be simply extended to refine the knowledge of further parameters as the baseline length and angle, (eventually also with their azimuth variation) to improve accuracy during geocoding operation. In this processing should be also kept into account the electrical phase due to X band receiver electronics and by mast cable length variation. The electrical phase data seems to introduce artefacts in the interferogram, so this step is now removed from the processing chain and it will be object of further investigations. GEOCODING AND MOSAIKING The unwrapped, calibrated phase image is converted in terrain heights projected in a geographic grid during the geocoded processing. Phase to height conversion. For each image line, we know the corresponding shuttle position and velocity and the baseline vector too (expressed in the same earth fixed 3D reference system). Assuming that only small errors arise by the reduction of the interferometry acquisition to the zero doppler plane, we can determinate exactly a triangle in this plane, having as corners the image pixel, the master and the slave antennas positions and hence localise in the 3D space (in rectangular coordinates or equivalently, height, latitude, longitude) each pixel of the phase image (see Fig. 2). Image interpolation in a regular geodetic grid. The heights in slant range, azimuth projection can be interpolated in a geo-referenced regular grid using the knowledge of the latitude and longitude of each pixel, obtained as described before. The height geocoding is based on the Delaunay triangulation followed by a re-gridding [R2] and uses input image segmentation since the huge memory requirement of triangulation. Fig. 2: a sketch of the triangle in the zero doppler plane used to determine the target height Error map generation. The generation of the HEM is based on the partial differentiation of the height function. Using a simplified model (see [R1]) it is possible to evaluate the HEM with a closed formula which gives the height error as function of: phase noise, baseline and orbit error, phase offset error. Mosaiking. Since SRTM DEMs overlap where the orbits cross together and also on high latitude areas, there is the need to combine them together. This is done in mosaiking processing where the various DEMs are weighted with the related HEM and also combined with external DEMs, covering the holes of SRTM coverage. IMAGE QUALITY ANALYSIS AND VALIDATION The SRTM Quality Control System is able to perform the quality analysis of all SRTM products (DEMs but even intermediate products) using a set of quality measure functions. The list of some of the possible quality checks is the following: Pixel Precise Localization Co-Registration quality Test Phase Preserving test Doppler Centroid Trend analysis Coherence Map Analysis Geometric calibration quality test Unwrapping processing quality test Mosaiking analysis Absolute vertical accuracy Relative vertical accuracy Absolute horizontal accuracy Relative horizontal accuracy

5 PRELIMINARY RESULTS Test site: Gargano, South Italy Data Take Auxiliary data available: Reference DEM posting 1 arc-sec MET Start 02:01:30:34 MET End 02:02:40:00 The following figure shows the localization of the Gargano Area and a 3D view of the obtained DEM. The view has been obtained with a combination of DEM height and Image Module values. EXAMPLE OF DEM Fig. 5: 3D view of an image of the Data Take (Tasmania) Fig. 3: Test area localization Fig. 6: 3D view of a portion of Datatake (Kamchatka). The image represents a 3D view of the interferometric DEM with heights represented with arbitrarily chosen false colors Fig. 4: 3D view of Gargano DEM Fig. 7: First processed image on White Sands - New Mexic.The displayed area covers surface of about 100 Km x 100 Km.

6 REFERENCES [R1] C. Prati, F.Rocca, A. Monti Guarnieri, P. Pasquali, Report on ERS-1 SAR Interferometric Techniques and Applications, Dipartimento di Elettronica - Politecnico di Milano, June 1994 [R2] IDL v , Reference Guide [R3] H. A. Zebker, "Decorrelation in Interferometric Radar Echoes", IEEE Trans. on Ge. and Rem. Sens., Vol. 30, No. 5, September 1992 [R4] M. Costantini, A Phase Unwrapping Method Based on Network Programming, in Proc. Fringe 96 Workshop, Zurich, Switzerland, ESA SP-406, pp [R5] M.D.Pritt J.S.Shipman, Least-Squares Two- Dimensional Phase Unwrapping Using FFT's, IEEE Transaction on Geoscience And Remote Sensing May Vol.32 N.3, 1994