Download or read book Cognitive Radar Detection in Nonstationary Environments and Target Tracking written by Yijian Xiang and published by . This book was released on 2020 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Target detection and tracking are the most fundamental and important problems in a wide variety of defense and civilian radar systems. In recent years, to cope with complex environments and stealthy targets, the concept of cognitive radars has been proposed to integrate intelligent modules into conventional radar systems. To achieve better performance, cognitive radars are designed to sense, learn from, and adapt to environments. In this dissertation, we introduce cognitive radars for target detection in nonstationary environments and cognitive radar networks for target tracking.For target detection, many algorithms in the literature assume a stationary environment (clutter). However, in practical scenarios, changes in the nonstationary environment can perturb the parameters of the clutter distribution or even alter the clutter distribution family, which can greatly deteriorate the target detection capability. To avoid such potential performance degradation, cognitive radar systems are envisioned which can rapidly recognize the nonstationarity, accurately learn the new characteristics of the environment, and adaptively update the detector. To achieve this cognition, we propose a unifying framework that integrates three functions: (i) change-point detection of clutter distributions by using a data-driven cumulative sum (CUSUM) algorithm and its extended version, (ii) learning/identification of clutter distribution by using kernel density estimation (KDE) methods and similarity measures (iii) adaptive target detection by automatically modifying the likelihood-ratio test and the corresponding detection threshold. We also conduct extensive numerical experiments to show the merits of the proposed method compared to a nonadaptive case, an adaptive matched filter (AMF) method, and the clairvoyant case.For target tracking, with remarkable advances in sensor techniques and deployable platforms, a sensing system has freedom to select a subset of available radars, plan their trajectories, and transmit designed waveforms. Accordingly, we propose a general framework for single target tracking in cognitive networks of radars, including joint consideration of waveform design, path planning, and radar selection. We formulate the tracking procedure using the theories of dynamic graphical models (DGM) and recursive Bayesian state estimation (RBSE). This procedure includes two iterative steps: (i) solving a combinatorial optimization problem to select the optimal subset of radars, waveforms, and locations for the next tracking instant, and (ii) acquiring the recursive Bayesian state estimation to accurately track the target. Further, we use an illustrative example to introduce a specific scenario in 2-D space. Simulation results based on this scenario demonstrate that the proposed framework can accurately track the target under the management of a network of radars.
Download or read book The Impact of Cognition on Radar Technology written by Alfonso Farina and published by SciTech Publishing. This book was released on 2017 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive dynamic systems are inspired by the computational capability of the brain and the viewpoint that cognition is a supreme form of computation. The key idea behind this new paradigm is to mimic the human brain as well as that of other mammals with echolocation capabilities which continuously learn and react to stimulations according to four basic processes: perception-action cycle, memory, attention, and intelligence. The Impact of Cognition on Radar Technology is an essential exploration of the application of cognitive concepts in the development of modern phased array radar systems for surveillance. It starts by asking whether our current radar systems already have cognitive capabilities and then discusses topics including: mimicking the visual brain; applications to CFAR detection and receiver adaptation; cognitive radar waveform design for spectral compatibility; cognitive optimization of the transmitter-receiver pair; theory and application of cognitive control; cognition in radar target tracking; anticipative target tracking; cognition in MIMO radar, electronic warfare, and synthetic aperture radar. The book concludes with a cross-disciplinary review of cognition studies with potential lessons for radar systems.
Download or read book The Impact of Cognition on Radar Technology written by Alfonso Farina and published by . This book was released on 2017 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The following topics are dealt with: cognitive radar; CFAR detection; receiver adaptation; cognitive optimization; transmitter-receiver pair; radar target tracking; MIMO radar; electronic warfare and synthetic aperture radar.
Download or read book Knowledge Based Radar Detection Tracking and Classification written by Fulvio Gini and published by John Wiley & Sons. This book was released on 2008-06-09 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the technology for the next generation of radar systems Here is the first book that brings together the key concepts essential for the application of Knowledge Based Systems (KBS) to radar detection, tracking, classification, and scheduling. The book highlights the latest advances in both KBS and radar signal and data processing, presenting a range of perspectives and innovative results that have set the stage for the next generation of adaptive radar systems. The book begins with a chapter introducing the concept of Knowledge Based (KB) radar. The remaining nine chapters focus on current developments and recent applications of KB concepts to specific radar functions. Among the key topics explored are: Fundamentals of relevant KB techniques KB solutions as they apply to the general radar problem KBS applications for the constant false-alarm rate processor KB control for space-time adaptive processing KB techniques applied to existing radar systems Integrated end-to-end radar signals Data processing with overarching KB control All chapters are self-contained, enabling readers to focus on those topics of greatest interest. Each one begins with introductory remarks, moves on to detailed discussions and analysis, and ends with a list of references. Throughout the presentation, the authors offer examples of how KBS works and how it can dramatically improve radar performance and capability. Moreover, the authors forecast the impact of KB technology on future systems, including important civilian, military, and homeland defense applications. With chapters contributed by leading international researchers and pioneers in the field, this text is recommended for both students and professionals in radar and sonar detection, tracking, and classification and radar resource management.
Download or read book Cognitive Radar The Knowledge Aided Fully Adaptive Approach Second Edition written by Joseph R. Guerci and published by Artech House. This book was released on 2020-06-30 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly-anticipated second edition of the bestselling Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach, the first book on the subject, provides up-to-the-minute advances in the field of cognitive radar (CR). Adaptive waveform methods are discussed in detail, along with optimum resource allocation and radar scheduling. Chronicling the field of cognitive radar (CR), this cutting-edge resource provides an accessible introduction to the theory and applications of CR, and presents a comprehensive overview of the latest developments in this emerging area. It covers important breakthroughs in advanced radar systems, and offers new and powerful methods for combating difficult clutter environments. You find details on specific algorithmic and real-time high-performance embedded computing (HPEC) architectures. This practical book is supported with numerous examples that clarify key topics, and includes more than 370 equations.
Download or read book Novel Radar Techniques and Applications written by Richard Klemm and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The following topics are dealt with: waveform diversity; cognitive radar; target tracking and data fusion.
Download or read book Cognitive Radar written by Yanbo Xue and published by . This book was released on 2010 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: For over six decades, the theory and design of radar systems have been dominated by probability theory and statistics, information theory, signal processing and control. However, the similar encoding-decoding property that exists between the visual brain and radar has been sadly overlooked in all radar systems. This thesis lays down the foundation of a new generation of radar systems, namely cognitive radar, that was described in a 2006 seminal paper by Haykin. Four essential elements of cognitive radar are Bayesian filtering in the receiver, dynamic programming in the transmitter, memory, and global feedback to facilitate computational intelligence. All these elements excluding the memory compose a well known property of mammalian cortex, the perception-action cycle. As such, the cognitive radar that has only this cycle is named as the basic cognitive radar (BCR). For tracking applications, this thesis presents the underlying theory of BCR, with emphasis being placed on the cubature Kalman filter to approximate the Bayesian filter in the receiver, dynamic optimization for transmit-waveform selection in the transmitter, and global feedback embodying the transmitter, the radar environment, and the receiver all under one overall feedback loop. Built on the knowledge learnt from the BCR, this thesis expands the basic perception-action cycle to encompass three more properties of human cognition, that is, memory, attention, and intelligence. Specifically, the provision for memory includes the three essential elements, i.e., the perceptual memory, executive memory, and coordinating perception-action memory that couples the first two memories. Provision of the three memories adds an advanced version of cognitive radar, namely the nested cognitive radar (NCR) in light of the nesting of three memories in the perception-action cycle. In this thesis, extensive computer simulations are also conducted to demonstrate the ability of this new radar concept over a conventional radar structure. Three important scenarios of tracking applications are considered, they are (a), linear target tracking; (b), falling object tracking; and (c), high-dimensional target tracking with continuous-discrete model. All simulation results confirm that cognitive radar outperforms the conventional radar systems significantly. In conducting the simulations, an interesting phenomenon is also observed, which is named the chattering effect . The underlying physics and mathematical model of this effect are discussed. For the purpose of studying the behaviour of cognitive radar in disturbance, demonstrative experiments are further conducted. Simulation results indicate the superiority of NCR over BCR and the conventional radar in low, moderate and even strong disturbance.
Download or read book A Novel Data driven Learning Method for Radar Target Detection in Nonstationary Environments written by and published by . This book was released on 2016 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detect changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.
Download or read book Cognitive Radar Network Design and Applications written by Yogesh Anil Nijsure and published by . This book was released on 2012 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cognitive Radar written by and published by . This book was released on 2010 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several advances were made toward a foundation for cognitive radar. Several extensions to optimum or matched waveform theory were completed, including formalization of a random-target variance function used in the design methods, extensions to MIMO radar for target identification, information-based waveforms in the presence of ground clutter, incorporation of constant-modulus design techniques, and an adaptive PRK selection technique. These techniques were also applied to spatial waveform design (i.e. beamshaping) in order to develop the fundamentals for a cooperative multiplatform air-to-ground surveillance capability. Two techniques based on the covariance of target track states were developed for integrating detection and tracking into the same Bayesian framework, as well as probability updating techniques in target parameter space for multi-platform detection and tracking. This allowed for beamsteering toward areas in a scene where target presence and/or parameters were most uncertain.
Download or read book Advancing Fully Adaptive Radar Concepts for Real time Parameter Adaptation and Decision Making written by Peter John-Baptiste (Jr) and published by . This book was released on 2020 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive or Fully Adaptive Radar (FAR) is an area of research that is inspired by biological systems and focuses on developing a radar system capable of autonomously adapting its characteristics to achieve a variety of different tasks such as improved environment sensing and spectral agility. The FAR framework implements a dynamic feedback loop (sense, learn, adapt) within a software defined radar (SDR) system and the environment that emulates a Perception Action Cycle (PAC). The implementation of the FAR framework on SDRs relies on solver-based optimization techniques for their action selection. However, with the increase of optimization complexity, there becomes a heavy impact on time to solution convergence, which limits real-time experimentation. Additionally, many "cognitive radars" lack a memory component resulting in repetitive optimization routines for similar/familiar perceptions. Using an existing model of the FAR framework, a neural network inspired refinement is made. Through the use of neural networks, a subset of machine learning, and other machine learning concepts, a substitution is made for the solver-based optimization component for the FAR framework applied to single target tracking. Static feedforward neural networks and dynamic neural networks were trained and implemented in both a simulation and experimentation environment. Performance comparisons between the neural network and the solver-based optimization approaches show that the static neural network based approach had faster runtimes which lead to more perceptions and sometimes better performance through lower resource consumption. A comparison between the simulation results of the static feed-forward neural network, the dynamic recurrent neural network, and the solver is also made. These comparisons further support the notion of neural networks being able to provide a memory component for cognitive radar through the incorporation of learning, moving toward truly cognitive radars. Additional research was also performed to further show the advantages of neural networks in radar applications of rapid waveform generation. The FAR framework is also extended from the single-target tracking FAR framework to a multiple target tracking implementation. The multi-target implementation of the FAR framework displays the benefits of adaptive radar techniques for multiple target environments where complexity is increased due to the increased number of targets present in the scene as well as the need to resolve all targets. Refinements and additions were made to the existing cost functions and detection/tracking frameworks due to the multiple target environment. Experimental and simulated results demonstrate the benefit of the FAR framework by enabling a robust adaptive algorithm that results in improved tracking and efficient resource management for a multiple target environment. In addition to this, the Hierarchical Fully Adaptive Radar (HFAR) framework was also applied to the problem of resource allocation for a system needing to perform multiple tasks. The Hierarchical Fully Adaptive Radar for Task Flexibility (HFAR-TF)/Autonomous Decision Making (ADM) work applies the HFAR framework to a system needing to engage in balancing multiple tasks: target tracking, classification and target intent discernment ("friend", "possible foe", and "foe"). The goal of this Ph.D. is to combine these objectives to form a basis for establishing a method of improving current cognitive radar systems. This is done by fusing machine learning concepts and fully adaptive radar theory, to enable real-time operation of truly cognitive radars, while also advancing adaptive radar concepts to new applications.
Download or read book Novel Radar Techniques and Applications written by Hugh Griffiths and published by SciTech Publishing. This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cognitive Radar written by J. R. Guerci and published by Artech House. This book was released on 2010 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chronicling the new field of cognitive radar (CR), this cutting-edge resource provides an accessible introduction to the theory and applications of CR, and presents a comprehensive overview of the latest developments in this emerging area. The first book on the subject, Cognitive Radar covers important breakthroughs in advanced radar systems, and offers new and powerful methods for combating difficult clutter environments. You find details on specific algorithmic and real-time high-performance embedded computing (HPEC) architectures. This practical book is supported with numerous examples that clarify key topics, and includes more than 370 equations.
Download or read book Advances in Radar Systems for Target Detection and Tracking written by and published by . This book was released on 2024-05-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Non Line of Sight Radar written by Brian Watson and published by Artech House. This book was released on 2019-02-28 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-Line-of-Sight Radar is the first book on the new and exciting area of detecting and tracking targets via radar multipath without direct-line-of-sight (DLOS). This revolutionary capability is finding new applications in the tracking of objects in non-line-of-sight (NLOS) urban environments including detection and tracking of UAVs. This book brings together for the first time all the essential underpinnings and techniques required to develop and field a viable NLOS radar. It presents many examples, including electromagnetic radiation propagation in urban NLOS environments, extracting building location and morphology from readily available terrain databases, predictive ray-tracing techniques, and multi-target NLOS tracking. Readers will learn how to apply radar to urban tracking that was previously deemed impossible. The book shows how real-time physics calculations can be incorporated into the radar processor, and how existing radar hardware can be adopted for non-line-of-sight radar use without major upgrades. Including results from both high-fidelity, physics-based simulations and actual flight test data, this book establishes the efficacy of NLOS radar in practical applications.
Download or read book Advanced Signal Processing Techniques for Cognitive Radar Systems written by Ahmed Abdou Abouelfadl Mohamed Abdalla and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This thesis introduces novel signal processing algorithms for cognitive radar systems that consider the constraints of operation under real scenarios as well as hardware limitations. Specifically, the thesis focuses on the analysis and practical solution of three key problems encountered in the design and realization of the signal processing chain within the cognitive new-generation radars. Firstly, we consider detecting and excluding the non-homogeneous received data from the estimation of the interference covariance matrix. The available non-homogeneity detectors (NHDs) in the literature require estimating the covariance matrix for each examined data cell, leading to exacerbating the NHD complexity, especially with large-dimensional data. Instead, we employ the projection depth functions, inherited from the field of robust statistics, to formulate a new NHD test statistic that avoids estimating the covariance matrix. Moreover, the projection depth function converts the multivariate problem to a scalar one, evading the exponential growth of the computational complexity with the data dimension.\par Secondly, we turn our attention to a scarcely but nevertheless important discussed aspect of radar system, namely the waveform design for cognitive multi-input multi-output (MIMO) radars taking into account the reflective properties of the transmitting antenna array. For the first time, we propose a waveform design method using proximal optimization that not only improves the signal-to-interference plus noise ratio (SINR), but also lowers the reflected power from the transmitting antenna array. Consequently, the proposed waveform design method increases the radar system efficiency and protects the amplification unit of the transmitter, while at the same time, significantly improves the SINR. Finally, we introduce a novel formulation of the target frequency response (TFR) estimation problem, a crucial requirement for cognitive radars. Under the conventional assumption of a linear Gaussian model, the TFR is usually estimated using the Kalman filter. Surprisingly, even though in practice this assumption is often violated and the Kalman filter is no longer an optimal solution, the study of TFR estimation for more general models has not yet been considered. In our proposed formulation, the infinite hidden Markov model (iHMM) is used in TFR estimation without prior knowledge of the channel or the interference. Interestingly, when iterated over multiple pulses and under jamming conditions, the proposed estimation method exhibits superior performance compared to the Kalman and particle filters for different TFR models. Throughout the thesis, the newly proposed algorithms are evaluated by objective Monte Carlo simulations with different clutter distributions and radar parameters. Under the considered evaluation conditions, the results clearly show that the proposed methods can provide superior performance to existing benchmarks from the literature"--
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1989 with total page 968 pages. Available in PDF, EPUB and Kindle. Book excerpt:
