Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"Cognitive Radar"”.
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Distributed Online Learning in Cognitive Radar Networks
Cognitive radar networks (CRNs) were first proposed in 2006 by Simon Haykin, shortly after the introduction of cognitive radar. In order for CRNs to benefit from many of the optimization techniques developed for cognitive radar, they must have some method of coordination and control. Both …
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Cognitive Radar Detection in Nonstationary Environments and Target Tracking
… 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 …
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Enabling and directing real-time cognitive radar transmitter optimization.
… inflexible methods. Among these users are radar systems, which have historically been allocated large sections of bandwidth. In order to adapt and coexist with new technology in a dynamically managed environment, next generation radars must be able to adjust their spectral configuration in …
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Cognitive Radar Applied To Target Tracking Using Markov Decision Processes
… States. Future platforms and devices, such as radars and radios, need to be adaptive to their spectral environment in order to continue serving the needs of their users. This thesis considers an environment with one tracking radar, a single target, and a communications system. The …
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Creation of a Cognitive Radar with Machine Learning: Simulation and Implementation
In this paper we address radar-communication coexistence by modelling the radar environment as a Markov Decision Process (MDP), and then apply Deep-Q Learning to optimize radar performance. The radar environment includes a single point target and a communications system that will potentially …
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On the Value of Online Learning for Cognitive Radar Waveform Selection
Modern radar systems must operate in a wide variety of time-varying conditions. These include various types of interference from neighboring systems, self-interference or clutter, and targets with fluctuating responses. It has been well-established that the quality and nature of radar measurements …
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Learning Schemes for Adaptive Spectrum Sharing Radar
… technology along with statically allocated radar systems have contributed to the increasing scarcity of the sub 6 GHz frequency bands. As a result, development of Dynamic Spectrum Access (DSA) techniques for sharing these frequencies has become a critical research area for the greater …
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Radar Detection, Tracking and Identification for UAV Sense and Avoid Applications
… targets by enabling rapid prototyping of novel radar techniques such as micro-Doppler radar target identification or cognitive radar. To enable empirical radar signal processing evaluations, an S-Band and X-Band frequency modulated, software-defined radar testbed is designed, implemented, and …
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Multidimensional power amplifier circuit optimizations for adaptive radar.
… the ability to dynamically reconfigure radar transmitter power amplifiers will become necessary for adaptive radar. Reconfigurable transmitters will require the ability to tune input parameters such as load impedance, waveform bandwidth, and amplifier bias voltage to provide excellent …
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Compressive Detection and Estimation with Applications to Cognitive Radio and Radar
… of compressive sensing to spectrum sensing in cognitive radio is discussed. Fast and reliable detection of available channels (i.e. temporarily unoccupied by primary users) is a fundamental challenge in cognitive radio design. The (mean) time to detection of an idle channel is governed by the …
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Value of Machine Learning and Cognition on Target Tracking
… considers an environment with one tracking radar, a single target, and a communications system that can passively interfere with the radar system. Three separate agents, Sense and Avoid, Machine Learning, and "Optimal", are tasked with the channel selection problem for radar communications …
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Contemporary Approaches to Radar Detection: Robust Statistics, Reinforcement Learning, and Reconfigurable Intelligent Surfaces
Radar detection is one of the most fundamental problems in wireless signal processing and has been thoroughly studied for decades. As such, there is very well established theory for radar detection under a myriad of different system models; however, as the machine that is research continues to …
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High-throughput perception-aware mmWave radar object recognition system
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01
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Faster circuit optimization techniques for full-band and notched waveforms to enable next-generation radar.
… needed. In order to coexist, next-generation radars will have to adapt their spectral use in real-time. Two useful baseline technologies in interference-avoiding, adaptive spectrum technologies are the fast reconfiguration of the transmitter power amplifier circuitry and the transmission of …
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Phased array impedance tuning, secure transmission, and nonlinear spatial intermodulation suppression for next-generation radar and communications systems.
Simultaneously transmitting radar and communications signals from the same multi-beam phased array system, using spatial diversity, allows multiple functions to use the same frequency and can alleviate spectral congestion. An issue arises, however in a transmitter array that consists of power …