A NEW SUBAPERTURE APPROACH TO HIGH SQUINT SYNTHETIC APERTURE RADAR PROCESSING

Synthetic Aperture Radar (SAR) usually operate in a strip-imaging mode with the antenna pointing 90-degree broadside (side-looking). However, in some applications like airborne fire control radar or military reconnaissance where the area of interests cannot be reached instantly, the antenna exhibits a pointing angle (called squint angle) offset from the zero Doppler direction (squint mode). In this project, a High Squint Subaperture (HSS) algorithm was developed. The HSS was developed from the perspective of a stripmap Synthetic Aperture Radar (SAR) system and has the ability to focus SAR data at extremely high squint angle of 55 degrees with less than 1.27 % mainlobe expansion or even higher squint angles if larger mainlobe expansion can be tolerated. In high squint mode, the range compressed azimuth chirped signal usually consists of a large linear range walk term in both its phase and envelope. As the linear range walk term phase (dependent on squint angle) is deterministic, it can be compensated by multiplying the raw signal with a conjugate of the linear range walk term. The conventional subaperture algorithm such as Step Transform algorithm removes this linear term in its envelope by taking data along the linear range walk line. However, by doing this, targets of different ranges may fall onto the same range cell and cause range focus problem. Therefore, the algorithm can only focus SAR data with a small squint angle. The HSS algorithm solve the above mentioned problem by deramping the input signal with short reference function of varying chirp rate in the azimuth direction followed by coarse-resolution Fast Fourier Transform (CRFFT) to produce the coarse-resolution image. Phase compensations are then performed onto the CRFFT outputs to remove the undesirable phase terms arise from deramping of the input signal. The final step of the HSS algorithm is a fine-resolution Fast Fourier Transform (FRFFT) to recover the full resolution of the image. The HSS has been implemented onto real and simulated SAR data and the image are relatively well formed without much deterioration of the azimuth resolution. As the HSS algorithm only involves short FFTs and avoids interpolation, it is a more computationally efficient algorithm as compared to conventional fast convolution and wavenumber domain algorithms such as the Range Migration and Chirp Scaling Algorithm , which usually involve long FFTs and interpolations. On an absolute comparison of the algorithms in terms of computation requirements which depends on the specific sensor parameters and application requirements, the HSS algorithm requires 16.33 % less computation requirements than the Range Migration and Chirp Scaling Algorithm. The distinct feature of this algorithm is its simplicity of implementation, which is vital in real time processing, and motion compensation when the squint angle may be changing continuously.

Author dc:creator

• TAN NGEE LENG