Airborne SAR Radiometric Calibration Based on Improved Sliding Window Integral Method

To verify the performance of the high-resolution fully polarimetric synthetic aperture radar (SAR) sensor carried by the Xinzhou 60 remote-sensing aircraft, we used corner reflectors to calibrate the acquired data. The target mechanism in high-resolution SAR images is more complex than it is in low-resolution SAR images, the impact of the point target pointing error on the calibration results is more obvious, and the target echo signal of high-resolution images is more easily affected by speckle noise; thus, more accurate extraction of the point target position and the response energy is required. To solve this problem, this paper introduces image context information and proposes a method to precisely determine the integration region of the corner reflector using sliding windows based on the integral method. The validation indicates that the fully polarimetric SAR sensor on the Xinzhou 60 remote-sensing aircraft can accurately reflect the radiometric characteristics of the ground features and that the integral method can obtain more stable results than the peak method. The sliding window allows the position of the point target to be determined more accurately, and the response energy extracted from the image via the integral method is closer to the theoretical value, which means that the high-resolution SAR system can achieve a higher radiometric calibration accuracy. Additionally, cross-validation reveals that the airborne SAR images have similar quality levels to Sentinel-1A and Gaofen-3 images.

Ground Moving Target Imaging for Highly Squint SAR by Modified Minimum Entropy Algorithm and Spectrum Rotation

Ground moving target (GMT) is displaced and defocused in conventional synthetic aperture radar (SAR) image due to the residual phase error of non-cooperative GMT motion. In this study, a GMT imaging (GMTIm) method is proposed for highly squint SAR. As the squint angle become large, the displace and defocus effect of the GMT image become severe and the geometry distortion of the GMT image cannot be ignored. The proposed method first deduced the two-dimensional (2-D) frequency domain signal of the GMT and the bulk compression function of the Range Migration Algorithm (RMA) in highly squint SAR. Then GMT ROI data are extracted and a modified minimum entropy algorithm (MMEA) is proposed to refocus the GMT image. MMEA introduces the idea of bisection into the iteration process to converge more efficiently than the previous minimum entropy method. To overcome the geometry distortion of the GMT image, an equivalent squint angle spectrum rotation method is proposed. Finally, to suppress the GMT image sidelobe, the sparse characteristic of GMT is considered and a sparse enhancement method is adopted. The proposed method can realize GMTIm in highly squint SAR where the squint angle reaches to 75 degrees. The PSNR and ISLR of point target in highly squint SAR is close to that in side-looking SAR. The simulated point target data and ship data are used to validate the effectiveness of the proposed method.

Exploiting Chirp Rate Estimation Methods to Improve Image Formation Quality of Synthetic Aperture Radar

A common assumption in SAR image formation and processing algorithms is that the chirp rates of the transmitted and received radar signals are exactly the same. Dechirp processing is also done based on this common assumption. In real scenarios, the chirp rate of the received signal is different from that of the transmitted signal due to several reasons. In case the difference between the chirp rates of the transmitted and received signals is obvious, the demodulation and compression of the received pulse are not carried out precisely and defocusing the targets and the output images of the SAR processor results. In the present paper, a new technique is proposed to improve the image formation quality of SAR by exploiting chirp rate estimation methods. Based on the proposed technique, the chirp rate of the received signal is estimated, and then, dechirp is carried out by using a time-reversed complex conjugate filter constructed based on the estimated chirp rate. In this stage, the existing chirp rate estimation algorithms can be used. The quality of the output image is assessed using PSLR as a quantitative criterion and the average number of point target extension pixels along the azimuth direction. Simulation results indicated that the smaller the average number of point target extension pixels along with azimuth and the higher the PSLR average is, the better the output image quality would be. Therefore, output images obtained from the proposed method by exploiting chirp rate estimation algorithms would have a better quality with a higher PSLR average (14.1 and 13.6) and also the lower average number of point target extension pixels along the azimuth directions (2.1 and 4.9) than the common method with PSLR average (8.3) and an average number of point target extension pixels along the azimuth direction (7.1).

Riemannian geometric approach to optimal binocular rotation, pyramid based interpolation and bio-mimetic pan-tilt movement

Over the past several years, we have been studying the problem of optimally rotating a rigid sphere about its center, where the rotation is actuated by a triplet of external torques acting on the body. The control objective is to repeatedly direct a suitable radial vector, called the gaze vector, towards a stationary point target in IR3. The orientation of the sphere is constrained to lie in a suitable submanifold of SO(3). Historically, the constrained rotational movements were studied by physiologists in the nineteenth century, interested in eye and head movements. In this paper we revisit the gaze control problem, where two visual sensors, are tasked to simultaneously stare at a point target in the visual space. The target position changes discretely and the problem we consider is how to reorient the gaze directions of the sensors, along the optimal pathway of the human eyes, to the new location of the target. This is done by first solving an optimal control problem on the human binocular system. Next, we use these optimal control and show that a pan-tilt system can be controlled to follow the gaze trajectory of the human eye requiring a nonlinear static feedback of the pan and tilt angles and their derivatives. Our problem formulation uses a new Riemannian geometric description of the orientation space. The paper also introduces a new, pyramid based interpolation method, to implement the optimal controller.

Aspect Dependent-based Ghost Suppression for Extended Targets in Through-the-wall Radar Imaging under Compressive Sensing Framework

Several approaches have been proposed to suppress multipath ghost in through-the-wall radar imaging (TWRI). One classical approach, called Aspect Dependent (AD), exploits locations of ghosts in the images without demanding prior knowledge of the reflecting geometry. This operation strategy makes the method superior over multipath exploitation-based approaches. However, the AD method assumes a point target that emulates unreal environment. Therefore, reconstructing extended targets with this method leads to incorrect scene interpretation. This work proposes a ghost suppression method for extended targets based on the AD feature that exploits duo sub-apertures. Firstly, we evaluate the best suppression method using a performance metric called relative clutter peak. Next, the evaluated method is extended to encompass the target extent during sub-images reconstruction. Following this strategy, an effective image fusion method suitable for extended targets is proposed. The method considers pixel neighborhood to effectively recover the given extended target. Simulation results show that the proposed method significantly improves signal-to-clutter ratio and relative clutter peak by 8.8% and 23.8%, respectively, relative to the existing AD based methods under point target assumption.