A Novel Sub-Image Local Area Minimum Entropy Reconstruction Method for HRWS SAR Adaptive Unambiguous Imaging

Abstract

Multichannel high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) is a vital technique for modern remote sensing. As multichannel SAR systems usually face the problem of azimuth nonuniform sampling resulting in azimuth ambiguity, the conventional reconstruction methods are adopted to obtain the uniformly sampled signal. However, various errors, especially amplitude, phase, and baseline errors, always significantly degrade the performance of the reconstruction methods. To solve this problem, in this paper, a novel sub-image local area minimum entropy reconstruction method (SILAMER) is proposed, which has favorable adaptability to the HRWS SAR system with various errors. First, according to the idea of image domain reconstruction, the sub-images are generated by employing the back-projection algorithm. Then, we proposed an estimation algorithm based on sub-image local area minimum entropy to obtain the optimal reconstruction coefficient and the compensation phase, which can greatly improve the estimation efficiency by using a local area of the sub-image as the input for estimation. Finally, the sub-images are weighted by the optimal estimated reconstruction coefficient and calibrated by the compensation phase to obtain the unambiguous reconstruction image. The experimental results verify the effectiveness of the proposed method. Noticeably, the proposed algorithm has two additional advantages, i.e., (1) it can perform well under the condition of low signal-to-noise ratio (SNR), and (2) it is suitable for the curved trajectory SAR reconstruction. The simulations verify these advantages of the proposed method.

Target-Oriented High-Resolution and Wide-Swath Imaging with an Adaptive Receiving–Processing–Decision Feedback Framework

“…Third, for online processing, BP can be implemented in parallel through graphical processing units (GPU). Fourth, for platforms with maneuverability, BP can be implemented with a nonlinear trajectory [19]. Due these advantages, we prefer BP as the azimuth imaging method.…”

“…To avoid the miscalculation with the target's pixels being mixed in, guard pixels are set adjacent to the pixel under detection, as shown in Figure 10. Meanwhile, the module uses image entropy [19] to decide the necessary resolution in the azimuth resolution. The image entropy is calculated as follows:…”

“…The entropy is to measure the randomness of the image statistically. In the SAR imaging community, it is usually used to indicate the degree of image focusing [19]. Normally, the more the image is focused, the lower the entropy is.…”

“…Due to these additional receiving channels, new imaging models need to be established, and corresponding imaging algorithms need to be studied. Researchers mainly studied these two aspects over the last decade [3,4,[15][16][17][18][19][20][21][22], among which issues related to imaging such as multichannel signal reconstruction [13,[15][16][17][18], amplitude/phase balancing, and motion error compensation [3][4][5]19,20] were studied the most. In the meantime, along with these developments, multiple new spaceborne and airborne SAR systems have been designed with HRWS imaging capability [2,8,[21][22][23], which again shows its attractive practical value.…”

Radar and Sonar Imaging and Processing (2nd Edition)

“…However, this solution suffers from various errors, among which the most important are amplitude error, phase error, and baseline error. Taking them into consideration, a novel sub-image local area minimum entropy reconstruction method (SILAMER) is proposed in [13]. The proposed method consists of three steps: sub-image generation, reconstruction coefficient and compensation phase estimation, and unambiguous reconstruction.…”