Performance Investigation on Scan-On-Receive and Adaptive Digital Beam-Forming for High-Resolution Wide-Swath Synthetic Aperture Radar

The work investigates the performance of the Smart Multi-Aperture Radar Technique (SMART) Synthetic Aperture Radar (SAR) system for high-resolution wide-swath imaging based on Scan-on-Receive (SCORE) algorithm for receive beam steering. SCORE algorithm works under model mismatch conditions in presence of topographic height. A study on the potentiality of an adaptive approach for receive beam steering based on spatial spectral estimation is presented. The impact of topographic height on SCORE performance in different operational scenarios is examined, with reference to a realistic SAR system. The SCORE performance is compared to that of the adaptive approach by using the Cramèr Rao lower bound analysis

New Approach for Unambiguous High-Resolution Wide-Swath SAR Imaging

The high-resolution wide-swath (HRWS) SAR system uses a small antenna for transmitting waveform and multiple antennas both in elevation and azimuth for receiving echoes. It has the potential to achieve wide spatial coverage and fine azimuth resolution, while it suffers from elevation pattern loss caused by the presence of topographic height and impaired azimuth resolution caused by nonuniform sampling. A new approach for HRWS SAR imaging based on compressed sensing (CS) is introduced. The data after range compression of multiple elevation apertures are used to estimate direction of arrival (DOA) of targets via CS, and the adaptive digital beamforming in elevation is achieved accordingly, which avoids the pattern loss of scan-on-receive (SCORE) algorithm when topographic height exists. The effective phase centers of the system are nonuniformly distributed when displaced phase center antenna (DPCA) technology is adopted, which causes Doppler ambiguities under traditional SAR imaging algorithms. Azimuth reconstruction based on CS can resolve this problem via precisely modeling the nonuniform sampling. Validation with simulations and experiment in an anechoic chamber are presented

Multifrequency Subpulse SAR: Exploiting Chirp Bandwidth for an Increased Coverage

Spatial resolution and swath width are fundamental quality parameters for spaceborne synthetic aperture radar (SAR) products. They have driven the research on new spaceborne SAR system concepts in the last decades, and a new generation of SAR systems is emerging. Main feature of these future systems is the use of multiple digital channels and new SAR processing techniques. A further characteristic is that they can resort to a large radar signal bandwidth. In this paper, a novel SAR operational mode is presented, denoted as multifrequency subpulse (MFSP). The MFSP exploits the available radar signal bandwidth to increase the imaged swath extension, without the emergence of range ambiguities. The proposed approach is explained both theoretically and by a design example, based on the future German X-band SAR system, High-Resolution Wide-Swath (HRWS). Moreover, the achievable SAR imaging quality is investigated

MIMO SAR Imaging for Wide-Swath Based on Compressed Sensing

To reduce the amount of data to be stored and software/hardware complexity and suppress range ambiguity, a novel MIMO SAR imaging based on compressed sensing is proposed under the condition of wide-swath imaging. Random phase orthogonal waveform (RPOW) is designed for MIMO SAR based on compressed sensing (CS). Echo model of sparse array in range and compressive sampling is reconstructed with CS theory. Resolution in range imaging is improved by using the techniques of digital beamforming (DBF) in transmit. Zero-point technique based on CS is proposed with DBF in receive and the range ambiguity is suppressed effectively. Comprehensive numerical simulation examples are performed. Its validity and practicality are validated by simulations

Computational Algorithms for Improved Synthetic Aperture Radar Image Focusing

High-resolution radar imaging is an area undergoing rapid technological and scientific development. Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR) are imaging radars with an ever-increasing number of applications for both civilian and military users. The advancements in phased array radar and digital computing technologies move the trend of this technology towards higher spatial resolution and more advanced imaging modalities. Signal processing algorithm development plays a key role in making full use of these technological developments.In SAR and ISAR imaging, the image reconstruction process is based on using the relative motion between the radar and the scene. An important part of the signal processing chain is the estimation and compensation of this relative motion. The increased spatial resolution and number of receive channels cause the approximations used to derive conventional algorithms for image reconstruction and motion compensation to break down. This leads to limited applicability and performance limitations in non-ideal operating conditions.This thesis presents novel research in the areas of data-driven motion compensation and image reconstruction in non-cooperative ISAR and Multichannel Synthetic Aperture Radar (MSAR) imaging. To overcome the limitations of conventional algorithms, this thesis proposes novel algorithms leading to increased estimation performance and image quality. Because a real-time imaging capability is important in many applications, special emphasis is placed on the computational aspects of the algorithms.For non-cooperative ISAR imaging, the thesis proposes improvements to the range alignment, time window selection, autofocus, time-frequency-based image reconstruction and cross-range scaling procedures. These algorithms are combined into a computationally efficient non-cooperative ISAR imaging algorithm based on mathematical optimization. The improvements are experimentally validated to reduce the computational burden and significantly increase the image quality under complex target motion dynamics.Time domain algorithms offer a non-approximated and general way for image reconstruction in both ISAR and MSAR. Previously, their use has been limited by the available computing power. In this thesis, a contrast optimization approach for time domain ISAR imaging is proposed. The algorithm is demonstrated to produce improved imaging performance under the most challenging motion compensation scenarios. The thesis also presents fast time domain algorithms for MSAR. Numerical simulations confirm that the proposed algorithms offer a reasonable compromise between computational speed and image quality metrics

Advanced high-order nonlinear chirp scaling algorithm for high-resolution wide-swath spaceborne SAR

Spaceborne Synthetic Aperture Radar (SAR) is a well-established and powerful imaging technology that can provide high-resolution images of the Earth’s surface on a global scale. For future SAR systems, one of the key capabilities is to acquire images with both high-resolution and wide-swath. In parallel to the evolution of SAR sensors, more precise range models, and effective imaging algorithms are required. Due to the significant azimuth-variance of the echo signal in High-Resolution Wide-Swath (HRWS) SAR, two challenges have been faced in conventional imaging algorithms. The first challenge is constructing a precise range model of the whole scene and the second one is to develop an effective imaging algorithm since existing ones fail to process high-resolution and wide azimuth swath SAR data effectively. In this paper, an advanced high-order nonlinear chirp scaling (A-HNLCS) algorithm for HRWS SAR is proposed. First, a novel second-order equivalent squint range model (SOESRM) is developed to describe the range history of the whole scene, by introducing a quadratic curve to fit the deviation of the azimuth FM rate. Second, a corresponding algorithm is derived, where the azimuth-variance of the echo signal is solved by azimuth equalizing processing and accurate focusing is achieved through a high-order nonlinear chirp scaling algorithm. As a result, the whole scene can be accurately focused through one single imaging processing. Simulations are provided to validate the proposed range model and imaging algorithm

Phase inconsistency error compensation for multichannel spaceborne SAR based on the rotation-invariant property

The azimuth multichannel technique has been widely used in synthetic aperture radar (SAR) systems for improving the resolution and expanding the illumination area. However, due to phase inconsistency (PI) of different channels, the image quality deteriorates significantly, including resolution loss and appearance of ghost targets. In this letter, by exploiting the rotation-invariant property of the steering vector of the multichannel SAR signal, a PI error compensation method is proposed based on the estimation of signal parameters by rotation invariance technique (ESPRIT). Experimental results are presented using both simulated and real data to demonstrate the performance of the proposed method