# A Novel Spaceborne Sliding Spotlight Range Sweep Synthetic Aperture Radar: System and Imaging
## 6 Simulation and Discussion
To assess the effectiveness of the MPFA for the SSS-RSSAR imaging, the contour plots of amplitudes of the focused marginal targets \(T_{11}\), \(T_{13}\), \(T_{15}\), \(T_{31}\), \(T_{33}\), \(T_{35}\), \(T_{51}\), \(T_{53}\) and \(T_{55}\) are inspected in Figure 14. The new PA technique is employed in generating the transmitted pulses. The indicators for the focusing quality evaluation, including the peak side lobe ratio (PSLR), integrate side lobe ratio (ISLR) and resolution, are listed in Table 5. The fact that for all the targets the PSLRs and ISLRs match well with their theoretical values, \(-10.26\) dB and \(-9.8\) dB, respectively, and that the measured resolutions match well with their expected performances in Table 4, the validity of the MPFA in focusing the SSS-RSSAR data has been demonstrated. The slight inconsistency of the azimuth resolutions in Table 5 is caused by the slight difference of the beam dwell time of different targets. To demonstrate the advantages of the SSS-RSSAR over the traditional sliding spotlight SAR, the least required total sample numbers and the total computational load for imaging are shown in Figures 15 and 16, respectively. The variation of the minimum total sample numbers of the SSS-RSSAR  
Figure 13: Focusing performances of \(T_{33}\) when: (**a**) using the parameter adjusting technique; and (**b**) not using the parameter adjusting technique. and the traditional SSS-SAR with respect to the range and azimuth swaths are shown in Figure 15a,b. The inspected range swath ranges from 1 km to 10 km and the inspected azimuth swath ranges from 1 to 20 km. It is found that while for a smaller ROI swath the total sample number of the SSS-RSSAR is much lower than that of the traditional SSS-SAR, for a large ROI swath, however, there would be no obvious advantage of the SSS-RSSAR because a large swath will lead to wider range and azimuth bandwidths after the 2D dechirp and thus, larger sampling rates, both in range and in azimuth, are required, accompanied with more sample numbers. This also implies that the SSS-RSSAR is especially suitable for imaging a moderate-swath ROI tilted with the satellite track in a high resolution. Note that, as the total sample number of the SSS-RSSAR 6477 \(\times\) 23,492 (range \(\times\) azimuth), as shown in Figure 15a, represents the least required number, the real total sample used for the simulation experiments is 7344 \(\times\) 26,124 (range \(\times\) azimuth), which turns to be higher than the least required value in observing the 5 km \(\times\) 10 km (range \(\times\) azimuth) tilted ROI. The least required total computational loads when using the MPFA and other imaging algorithms, including the RDA, CSA and RMA, are compared in Figure 16. Based on the discussion in Section 5.2, while the computational loads of the RDA, CSA and RMA are calculated based on the least total sample number in Figure 15b, the computational load of the MPFA is calculated based on the total sample number in Figure 15a. For the simulated case, the total computational loads of the RDA, CSA and RMA are 93.5 GFLOP, 86.6 GFLOP and 91.8 GFLOP, respectively. Comparatively, the total computational load of the MPFA is only 50.9 GFLOP, much lower than all those of the RDA, CSA and RMA. The comparisons in Figures 15 and 16 have demonstrated that, for a moderate swath, the SSS-RSSAR is superior to the traditional SSS-SAR by contributing to less total data amount and lighter computational load for the imaging processing. This is the very motivation of proposing the SSS-RSSAR in