Real-Time Implementation of the Extended Chirp Scaling Algorithm for Air- and Spaceborne SAR-Processing Albert0 Moreira, Rolf Scheiber, Josef Mittermayer and Rainer Spielbauer Deutsche Forschungsanstalt fur Luft- und Raumfahrt (DLR) Institut fur Hochfrequenztechnik 82234 Oberpfaffenhofen, Germany T: +49-8153-28-2360, EMail:
[email protected] The kernel of all these processors is the chirp scaling operation which is a multiplication of the uncompressed range signal in the range-Doppler domain with a quadratic phase function resulting in an equalization of all range migration trajectories at a reference range. The CS algorithm is phase preserving because only FFT’s and phase multiplications are performed. This is a n extremely important feature when considering the processor t o be useful1 for higher SAR products such as interferograms or polarimetric images.
Abstract - This paper presents the first results of a feasibility analysis concerning an air- and spaceborne real-time SAR processor for strip and ScanSAR mode. The Extended Chirp Scaling approach is used for both operation modes. Using dedicated digital signal processors, a special hardware can be developed with a power consumption of less than 250 W.
I. INTRODUCTION An on-board high-resolution real-time SAR processor has been developed at DLR for the experimental airborne SAR system. A Real-Time Subaperture (RTS) approach, which is suitable for airborne real-time SAR processing, was chosen for the hardware implementation. However, this RTS processor is not suitable for the processing of spaceborne SAR data due to the limited compression ratio in range and azimuth processing. In [Z], the traditional chirp scaling algorithm has been extended, so that the motion error compensation required for airborne SAR processing could be included. Additionally, the extended chirp scaling algorithm (ECS) accommodates the Doppler centroid variation with range by means of a n azimuth spectral length extension in the range-Doppler domain. The Doppler centroid update with azimuth is introduced by means of azimuth subaperture processing. This features make the ECS algorithm a good candidate for real-time processing of air- and spaceborne SAR data. Section I1 of this paper reviews shortly the ECS algorithm and section I11 describes the inclusion of the algorithms for Doppler parameters estimation in the processing. Section IV proposes an implementation of the extended chirp scaling algorithm for processing SAR data in the ScanSAR mode of operation. Section V concludes the paper giving some considerations concerning the hardware implementation.
11. THE EXTENDED CHIRP SCALING ALGORITHM Common t o all implementations of the chirp scaling (CS) algorithm is that no interpolation is required for range cell migration correction (RCMC) or for performing the Stolt approximation in wavenumber processors.
0-7803-2567-2195 $4.00 0 1995 IEEE
The extended chirp scaling (ECS) algorithm was primarily developed for airborne SAR processing, but has some unique characteristics which make it undispensable also for spaceborne SAR systems, especially for real time processing. In figure 1 a block diagram of the ECS for blockwise processing is presented. The algorithm for the spaceborne case is presented including the algorithms for Doppler parameters estimation (in light grey boxes). Within the dark grey boxes the additional computing for the airborne case is displayed, which is required due to the motion compensation. The first part of it compensates the motion errors for a reference range and is performed directly on the raw data before any other calculation is done. The ECS-algorithm starts with a FFT in azimuth direction, followed by a spectral length extension in order to accomodate the variation of the Doppler centroid in range during the following processing steps. The chirp scaling operation is performed by multiplying the range signal in the range-Doppler domain with a Doppler-frequency dependent quadratic phase function H I (cubic for more accurate high squint processing). Now, having all RCMtrajectories equalized, the data are transformed into the wavenumber domain. The multiplication with a linear, Doppler-frequency dependent phase function corrects the RCM for all ranges at once. Also matched filtering in range direction and secondary range compression (SRC) are included in this domain. All these operations are described by the phase function H z l . When transforming the data back to the range-Doppler domain, a residual phase correction Hzz is applied, which compensates for artifacts introduced by the chirp scaling operation. The next step of the processing is different for air- and spaceborne SAR systems. For spaceborne SAR systems the last operation is a one dimensional azimuth compression which is done in the range-Doppler domain. Finally
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an inverse F F T gives the processed d a t a block. In the airborne case an accurate motion compensation, distinct for each range, is applied on the d a t a which are therefore transformed into the time domain, and afterwards back into the range-Doppler domain. Finally, the one dimensional azimuth compression H3 for air- and spaceborne cases is the last operation of the ECS.
111. INCLUSION O F DOPPLER PARAMETERS ESTIMATION The real-time implementation of Doppler parameters estimation is essential when considering the architecture of a real-time processor. Figure 1 shows, how these algorithms are included into the signal flow of the extended chirp scaling algorithm. In the following a small description of these algorithms is given as well as the reasons why they are included in their specific way.
Doppler centroid estimation with the CDE approach The Correlation Doppler Estimator (CDE) is a time domain approach and exploits the fact, that the phase of the first coefficient of the autocorrelation function of the azimuth signal is proportional to the frequency shift of the azimuth power spectrum due to a Doppler centroid. This very efficient approach is used directly on the raw data, giving a first rough estimate of the Doppler centroid foc,l. The estimated variation of the Doppler centroid with range is slightly smeared out because the range signal at this stage of the processing is uncompressed. PRF ambiguity resolving: There is a n uncertainty in estimating the correct multiple N of the P R F which must be added to the estimated value f ~ c ,ofl the Doppler centroid. This is due to the discrete sampling of the azimuth signal with the pulse repetition frequency P R F . The multiple N can he estimated by using the estimates of the Doppler centroid obtained by sampling the azimuth signal with different P R F ' s . Using this approach is more convenient for real-time processing than other PRF-ambiguity resolvers which require a much greater two dimensional storage capability. Knowing the correct Doppler centroid estimate, the PRF-ambiguity number as well as the nominal velocity, the chirp scaling operation and the wavenumber domain calculations can he performed with sufficient accuracy. But for the azimuth compression the Doppler parameters must be known more exactly. Thus, additional algorithms have t o be incorporated into the processing. Therefore the d a t a are range compressed and transformed back into the range- Doppler domain.
Doppler centroid estimation using energy balancing: Energy balancing is a frequency domain approach and is basically a correlation of the Doppler spectrum with an appropriate chosen function, in order to determine the center frequency (Doppler centroid). Therefore the Doppler spectrum is computed by averaging several azimuth lines
in the range-Doppler domain, thus giving reliable estimates of the Doppler centroid f D c , z for particular range intervals. These values are used when computing the azimuth compression. Velocity estimation with the modified SAC approach [4]: The modified Shift And Correlate algorithm (SAC) is essentially a frequency shift of the azimuth Doppler spectrum and a time domain correlation. The signals to be correlated are the original spectrum and the frequency shifted spectrum. The correlation is performed in the rangeDoppler domain resulting in a time domain peak which is detected a t the position At = A f / k a after Fourier transforming. The detected position gives information about the actual Doppler rate k , which is a function of range and velocity. Thus different estimates over range can be averaged yielding a precise value for the velocity 'U. Since the quality of every estimate is dependent on the contrast of the scene, only selected estimates are used which result from high correlation peaks. The exact estimate of the velocity 'U is used when computing the reference function for the azimuth compression. IV. SCANSAR PROCESSING ScanSAR is a special mode for SAR systems in which the antenna is scanned between different look angles t o obtain a wider swath composed of subswaths. The synthetic aperture is shared to subapertures, one for each subswath. In the following a modification is presented, which allows the processing of ScanSAR d a t a using the Chirp Scaling algorithm. The required modifications are small so that the real-time hardware implementation is optimized. The modified method uses the SPECAN [l]approach for the azimuth processing. Two modifications have to be applied to the CS algorithm. Instead of the multiplication of a phase function for the motion compensation (see fig. 1, airborne case), a phase function for deramping is used. The final I F F T in azimuth is exchanged by a resampling step. The first part of the processing is identical to the strip mode airborne case. After the azimuth signal has been transformed to the time domain, azimuth subchirps in the same range but in different azimuth positions possess approximately the same Doppler rate but different central frequencies. The phase function for the deramping is a chirp with positive Doppler rate. After the deramping we obtain a signal which consists of the superposition of all the central frequencies. By means of an azimuth F F T , these frequencies are separated and located as peaks at different positions. The valid points in all range distances are resampled to (T, - T,) PRF points in order to obtain the correct azimuth scaling, where T, is the illumination time for each subswath and T, is the full aperture duration. In the mosaiking of the processed blocks, a along track
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cross-track radiometric correction is neccessary because of the antenna weighting in azimuth and range. Methods for performing such correction are already used and described for example in [l]. V. HARDWARE REQUIREMENTS
As far as the hardware is concerned, two main digital signal processors (DSP) have been selected for the hardware implementation. The SHARP DSP LH 9124/9320 is used for all the FFT’s and phase multiplications with exception of the FFT’s and phase multiplications involved in the azimuth processing. In this case, the multi-looking operation as well as the higher dynamic range makes this processor not adequate. The Analog Devices ADSP 21060 was selected for the azimuth processing and also for the operation involved in the estimation of the Doppler parameters and generation of all the phase functions. For the processing of spaceborne d a t a with a P R F of 1800 Hz and 4096 range bins, approximatelly 12 SHARP processors and 40 ADSP are required. Including the data memory and control circuits, ca. 250 W are necessary for the continuous high-resolution real-time processing. For the airborne case, a reduced hardware version with less power consumption can be used. Future work includes the introduction of subaperture processing into the first part of the chirp scaling approach, so that the memory requirements for the first corner turn and recorner turn operations are considerably reduced.
I Chirp Scaling ( H1 )
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Azimuth Snectral Length Extension v
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Range IFFI
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Phase Correction due to CS ( H 2 2 )
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Azimuth Spectral Length Reduction
Doppler centroid: energy balancing
VI. REFERENCES
[l] Eldhuset, K. & Valand, P.A.:”ScanSAR Processing and Simulation for ASAR using ERS-1 Raw Data”, submitted t o Int. J. Remote Sensing, 1994 [2] Moreira, A. & Huang, Y.:”Airborne SAR Processing of Highly Squinted Data Using a Chirp Scaling Approach with Integrated Motion Compensation”, IEEE Trans. Geosc. Remote Sensing, vo1.32, no.5, 1994 [3] Raney, R.K. et a1:”Precision SAR Processing without Interpolation for Range Cell Migration Correction”, IEEE Trans. Geosc. Remote Sensing, ~01.32,no.4, 1994 [4] Scheiber, R. & Moreira, A.:”Extension of the Correlation Doppler Estimator for determination of the Doppler Rate and for Resolving the PRF-Ambiguity”, Proc. of SPIE, ~01.2316,1994, pp. 33-41
Azimuth - Compression ( H3 )
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Figure 1: Signal flow of the Extended Chirp Scaling for processing of one d a t a block in the spaceborne case. The dark grey boxes show the additional processing for the airborne case.
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