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A 360° video synthetic aperture radar (VideoSAR) appears as an interactive observation capability to understand the dynamic scenarios. VideoSAR system mounted on an unmanned aerial vehicle (UAV) delivers a highly flexible and cost-effective approach. In this letter, the UAV-borne repeat-pass circular stripmap (CSM) VideoSAR observation is formulated in the format of video area overflown to enhance the wide-area surveillance capability. A completely two-dimensional interpolation-free polar format algorithm is employed, especially in terms of repeat-pass CSM-VideoSAR configuration. We conduct the repeat-pass CSM-VideoSAR experiments on multirotor UAV-borne system in the interests of imaging demonstration and promoting the inspirations on the related open issues. [ABSTRACT FROM AUTHOR]

The piecewise constant Doppler (PCD) algorithm is a novel radar imaging process recently proposed for the generalized continuous-wave synthetic aperture radar (GCW-SAR). This article presents a detailed theoretical analysis on the PCD algorithm's performance and proposes a further complexity-reduced PCD algorithm with motion compensation (MOCO) suitable for practical applications. First, the difference between conventional SAR imaging and PCD imaging, i.e., the zeroth-order versus the first-order slant range approximation, is revealed. Exact ambiguity function expressions of the PCD imaging in range and azimuth directions, respectively, are then derived. An error function of the PCD imaging as compared with the ideal matched filtering method is further defined and shown to be a function of an image quality factor, which can be used to quantify the PCD imaging performance. Finally, a faster and more flexible imaging process, called decimated PCD algorithm, is proposed, by which the image azimuth spacing can be easily extended, and hence, the computational complexity can be significantly reduced. The decimated PCD implementation incorporated with the MOCO is developed for practical GCW-SAR applications, and its imaging error lower-bounded by the PCD imaging error function is analyzed accordingly. Simulation and experimental results validate the theoretical analysis of the PCD imaging and show that the decimated PCD algorithm can achieve a high imaging quality at low cost. [ABSTRACT FROM AUTHOR]

In this paper, we extend the forward-scanning synthetic aperture radar (SAR) methodology to reconstruct images of the moving targets, for a forward-looking automotive radar. We adapt a matrix decomposition approach to forward-scanning SAR in order to separate moving targets from clutter/stationary objects. To solve our optimization problem, we propose an iterative solution based on augmented Lagrangian method. Image focusing, over the synthetic aperture, is achieved through spatial segmentation and cross-correlation maximization. Our proposed method results in well-focused imaging of the moving targets with enhanced angular resolution. Experimental results from simulation as well as real-data corroborate our proposed methodology. [ABSTRACT FROM AUTHOR]

In this paper, we propose a forward scanning synthetic aperture radar methodology for a forward-looking automotive (low-terahertz) radar, which combines scene scanning with synthetic aperture processing, resulting in enhanced angular resolution and improved imaging. We propose two algorithms, first, a modified back-projection (BP) algorithm and, second, a compressed sensing-based BP algorithm. We suggest techniques to reduce computational complexity of the proposed algorithms. Results of simulation and real-data experiments corroborate the validity of our proposed methodology and algorithms. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) inverse synthetic aperture radar (ISAR) imaging has been proven feasible by combining traditional ISAR imaging and interferometry. Such technique, namely Inteferometric ISAR (InISAR), allows for the main target scattering centers to be mapped into a 3-D spatial domain, therefore forming 3-D images under the form of 3-D point clouds. 3-D InISAR overcomes some main limitations of traditional 2-D ISAR imaging, such as the problem of cross-range scaling and unknown image projection plane. Despite the great advantage of 3-D imaging over traditional 2-D imaging, some issues remain, such as scatterer scintillation, shadowing effects, poor SNR, etc., which limit the effectiveness of 3-D imaging. A solution to these issues can be found in the use of multiple 3-D views, which can be obtained exploiting either multitemporal or multiperspective configurations or a combination of both. This paper proposes this concept and develops the image fusion algorithms that are necessary to produce multiview 3-D ISAR images. The effectiveness of the proposed technique is tested by using real data collected with a multistatic InISAR system. [ABSTRACT FROM AUTHOR]

The radar echoes of space debris sometimes have drawbacks of inadequate pulse samples, self-occlusion, and data missing, while the state-of-art radar imaging algorithms become unproductive. To tackle this problem, this paper proposes a novel method for three-dimensional (3-D) imaging of space debris. This iterative algorithm terminates automatically and can recover the intensity of space debris radar cross section, making it practical in real-world applications. Unlike the 3-D imaging methods based on multistatic inverse synthetic aperture radar, the proposed method is applicable to monostatic ISAR. [ABSTRACT FROM AUTHOR]