Most of the existing Non-Cooperative Target Recognition (NCTR) systems follow the “closed world” assumption, i.e., they only work with what was previously observed. Nevertheless, the real world is ...relatively “open” in the sense that the knowledge of the environment is incomplete. Therefore, unknown targets can feed the recognition system at any time while it is operational. Addressing this issue, the Openmax classifier has been recently proposed in the optical domain to make convolutional neural networks (CNN) able to reject unknown targets. There are some fundamental limitations in the Openmax classifier that can end up with two potential errors: (1) rejecting a known target and (2) classifying an unknown target. In this paper, we propose a new classifier to increase the robustness and accuracy. The proposed classifier, which is inspired by the limitations of the Openmax classifier, is based on proportional similarity between the test image and different training classes. We evaluate our method by radar images of man-made targets from the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset. Moreover, a more in-depth discussion on the Openmax hyper-parameters and a detailed description of the Openmax functioning are given.
This book explores the challenges that disinformation, fake news, and post-truth politics pose to democracy from a multidisciplinary perspective. The authors analyse and interpret how the use of ...technology and social media as well as the emergence of new political narratives has been progressively changing the information landscape, undermining some of the pillars of democracy.The volume sheds light on some topical questions connected to fake news, thereby contributing to a fuller understanding of its impact on democracy. In the Introduction, the editors offer some orientating definitions of post-truth politics, building a theoretical framework where various different aspects of fake news can be understood. The book is then divided into three parts: Part I helps to contextualise the phenomena investigated, offering definitions and discussing key concepts as well as aspects linked to the manipulation of information systems, especially considering its reverberation on democracy. Part II considers the phenomena of disinformation, fake news, and post-truth politics in the context of Russia, which emerges as a laboratory where the phases of creation and diffusion of fake news can be broken down and analysed; consequently, Part II also reflects on the ways to counteract disinformation and fake news. Part III moves from case studies in Western and Central Europe to reflect on the methodological difficulty of investigating disinformation, as well as tackling the very delicate question of detection, combat, and prevention of fake news.This book will be of great interest to students and scholars of political science, law, political philosophy, journalism, media studies, and computer science, since it provides a multidisciplinary approach to the analysis of post-truth politics.
The atmosphere affects the propagation of radar signals by provoking unwanted signal phase changes. In interferometric applications, such as coherent change detection and displacement measurements, ...this effect may significantly degrade the system performances. Moreover, atmosphere-induced phase changes are both time and space variants, and therefore, they are not easy to be removed. This article proposes a novel method to remove atmospheric effects by using a parametric model of the refractive index, which is derived as an extension of the International Telecommunication Union-Radiocommunication model. The proposed algorithm has been tested on real data acquired by using a ground-based synthetic aperture radar system in conjunction with data collected by a weather station. Data have been acquired continuously for three consecutive days, approximatively every 5 min. Results have shown how the proposed method can effectively remove atmospheric effects and restore the signal phase.
Staggered synthetic aperture radar (SAR), which operates with variable pulse repetition interval (PRI), staggers blind areas to solve the blind range problem caused by constant PRI in conventional ...high-resolution wide-swath SAR imaging. The PRI variation strategy determines the blind area distribution, and thus has a significant influence on the imaging performance in staggered mode. Generally, the existing strategies based on linear PRI variation can control the blind areas in a straightforward way, which has achieved impressive results. However, the linearity of the PRI variation imposes regularity or even periodicity on the locations of the blind areas, which limits the distribution of the blind areas. The imaging performance has the potential to be further improved by introducing much more irregularity into the PRI sequences. To this end, this article proposes an optimized nonlinear PRI variation strategy for staggered SAR mode. First, a novel objective function is defined that quantitatively measures the uniformity of the blind area distribution along the slant range and the discontinuity of the blind area distribution along the azimuth. Subsequently, the optimum nonlinear PRI variation strategy is found using an optimization problem and the proposed objective function. A knowledge-guided genetic algorithm is proposed to solve the optimization problem. Comparisons with the existing linear variation strategies show that the proposed strategy can provide a superior imaging performance after reconstruction with a lower objective function value. Simulations and experiments on raw data generated in staggered SAR mode are performed to verify the effectiveness of the optimized nonlinear PRI variation strategy.
Integrating an automatic target recognition (ATR) system into real-world applications presents a challenge as it may frequently encounter new samples from unseen classes. To overcome this challenge, ...it is necessary to adopt incremental learning, which enables the continuous acquisition of new knowledge while retaining previous knowledge. This article introduces a novel, multipurpose interpretability metric for ATR systems that employs synthetic aperture radar images. The metric leverages the local interpretable model-agnostic explanation algorithm, enhancing human decision-making by providing a secondary measure alongside the conventional classification score. In addition, the proposed metric is employed to analyze the robustness of convolutional neural networks by examining the impact of target features and irrelevant background correlations on recognition results. Finally, we demonstrate the effectiveness of the proposed metric in the context of incremental learning. By utilizing the proposed interpretability metric, we select exemplars in an incremental learning scenario, resulting in improved performance and showcasing the application potential of our proposed methodology. The network is fine-tuned sequentially with unknown samples recognized by the Openmax classifier and exemplars from the old known classes, which are selected based on the proposed interpretability metric. The effectiveness of this approach is demonstrated using the publicly available MSTAR dataset.
Three-dimensional ISAR imaging: a review Martorella, Marco; Salvetti, Federica; Staglianò, Daniele ...
Journal of engineering (Stevenage, England),
October 2019, Letnik:
2019, Številka:
20
Journal Article
Recenzirano
Odprti dostop
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 ...(In-ISAR), allows for the main target scattering centres to be mapped into a 3D spatial domain as point clouds. Specifically, the use of an In-ISAR system can overcome the main geometrical interpretation issues imposed by the monostatic acquisition geometry as the problem of cross-range scaling and unknown image projection plane (IPP). However, some issues remain such as scatterer scintillation, shadowing effects, poor SNR etc., which limit the effectiveness of 3D imaging. A solution to such unsolved issues can be found in the use of multiple 3D views, which can be obtained exploiting either multi-temporal or multi-perspective configurations or a combination of both. This study aims to review the main concepts to produce multi-view 3D ISAR images by using In-ISAR systems also presenting real data collected with a multi-static In-ISAR system.
...the recent technological advances have made the realization of array systems (ground/air/space borne) and real-time processing possible. The algorithm makes use of the worst-case performance ...optimization (WCPO) for avoiding target self-nulling effect. ...in the proposed approach, a modified objective function (with respect to D3 approach) is used to enhance the output signal to interference plus noise ratio (SINR) even in low SNR conditions. An analysis on pointing errors with respect to the number of array elements has shown that a MLC antenna with 2 or 3 elements provides significant improvement in the sea clutter echo DoA estimation. ...the examination of the interelement spacing against performance shows that a spacing greater than the theoretical limits of half a wavelength is allowed.
The aim of this Printed Edition of Special Issue entitled "Recent Advancements in Radar Imaging and Sensing Technology” was to gather the latest research results in the area of modern radar ...technology using active and/or radar imaging sensing techniques in different applications, including both military use and a broad spectrum of civilian applications. As a result, the 19 papers that have been published highlighted a variety of topics related to modern radar imaging and microwave sensing technology. The sequence of articles included in the Printed Edition of Special Issue dealt with wide aspects of different applications of radar imaging and sensing technology in the area of topics including high-resolution radar imaging, novel Synthetic Apertura Radar (SAR) and Inverse SAR (ISAR) imaging techniques, passive radar imaging technology, modern civilian applications of using radar technology for sensing, multiply-input multiply-output (MIMO) SAR imaging, tomography imaging, among others.
The applicability of compressive sensing (CS) to inverse synthetic aperture radar (ISAR) imagery has been widely discussed over the past few years. In particular, CS-based ISAR image-reconstruction ...algorithms have been developed and their effectiveness proven when dealing with incomplete ISAR data. Resolution enhancement has also been identified as a case for which CS can be effectively applied to ISAR imagery. In this case, the acquired signal can be interpreted as incomplete data in the frequency/slow-time domain and CS used to reconstruct the super-resolved ISAR image. In this paper, an exhaustive performance analysis is carried out along with a comparison between CS and conventional super-resolution techniques. Several concepts and methods have been introduced in order to effectively define the performance, which is not simply based on visual inspection.
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.
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