## 3 Performance Evaluation of the Proposed SAR Processor
### Precision Comparison of the Proposed SAR Processor and MATLAB-Based SAR Processor
Figure 8 shows the range-compressed data processed by MATLAB based SAR processing software, while Figure 9 shows the range-compressed data processed by the proposed SAR processor. In the figures, the similarities between the range-compressed data are visually identical. Hence, the differences between these two sets of range-compressed data are computed in the same manner in order to obtain a quantitative comparison. Figure 10 shows the difference in SAR range-compressed data in the range profile. The majority differences of the results are acceptable, and they are in the range of \(\pm 0.5\%\), as indicated in the figure. Only a few samples had spikes of +2% to +3% of errors that can be neglected. In Figure 10, it can be noticed that the overall similarities between these two compressed data are considered reasonably high, as the expected patterns are recognisable. After evaluating the intermediate results for range compression, evaluation was carried out by observing the intermediate results for azimuth compression. The evaluation was conducted in the same manner as for range compression. The range-compressed  
Figure 7: Difference in SAR raw data (range profile) in the frequency domain transformed by MATLAB and the proposed SAR processor. After the data were transformed into the range-Doppler domain, they were then passed through the azimuth compression, which consist of the azimuth-matched filtering process. The data were multiplied with the precomputed azimuth reference function using the designed complex multiplier. The output of the matched filter is transformed into time domain and the data appear as azimuth-compressed data. The final output of the SAR processor is the azimuth compressed data, which is the single-look complex SAR image. Figure 14 shows the azimuth-compressed data processed by MATLAB, while Figure 15 shows the azimuth-compressed data processed by the proposed SAR processor. Figure 11: Range-compressed data in the range-Doppler domain by MATLAB 2048-FFT. Figure 10: Difference in range-compressed data (range profile) by MATLAB and the proposed SAR processor. From the figures, the similarities between the azimuth-compressed data are visually identical. Thus, in order to obtain a quantitative comparison, the differences between these two azimuth-compressed data were computed and portrayed as Figure 16 for the range profile and Figure 17 for the azimuth profile, respectively. Figures 16 and 17 show that the majority of differences are in the range of \(\pm\)1%. This error is mainly due to the quantisation error from the system. It can also be concluded that both profiles consist of a quantisation noise floor around \(\pm\)0.5%, even when there is no point target in the data. Another observation from the difference is that when there is a point target in the image for a particular range and azimuth samples, the difference error  
Figure 12: Range-compressed data in the range-Doppler domain by the proposed SAR processor, 2048-FFT. Figure 13: Difference in range-compressed data (range profile) in the range-Doppler domain (range time, azimuth frequency). also increases. The sample points with the reflected point targets have a slightly higher difference error of about 3.5% as compared to the background. This is mainly due to the low dynamic range of the fixed-point data formatting used in the proposed processor. Overall, the processed SAR image is satisfactory, as the proposed SAR processor is capable of processing the SAR raw data and forming the SAR image with an acceptable low margin of difference error. Based on the compressed SAR image, the results are regarded as satisfactory because the overall similarities between the two SAR images are considered identical, as the expected patterns are recognisable. Figure 4:0 Azimuth-compressed SAR image by MATLAB. Figure 4:1 Azimuth-compressed SAR image by the proposed SAR processor.