Jammer Nulling Adaptive Waveforms with Cognitive Radar for Aircraft RCS Recognition in Presence of Frequency Sweep and Base Jammers

Tan, Q. Jeanette O.; Romero, Ric A.

doi:10.1109/acssc.2018.8645114

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Considering the UAV's energy constraints, the authors in [50] examined the performance of jammer nulling transmit-adaptive energy-constrained waveforms for UAVs to suppress the jamming signals generated by the sweep jammers and base jammers. Broadly, jamming attacks can be classified as pilot jamming, proactive jamming, and reactive jamming.…”

Section: ) Jammingmentioning

confidence: 99%

Security Threats and Mitigation Techniques in UAV Communications: A Comprehensive Survey

et al. 2022

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Unmanned aerial vehicles (UAVs) have been instrumental in enabling many new applications and services, including military and rescue operations, aerial surveillance, civilian applications, precision farming, as well as providing extensive wireless network access in remote areas. They have also been used in other areas such as transmission line and oil rig monitoring, disaster recovery, etc. With their increasing payload ability and flight duration, using UAVs is a preferred choice for a multitude of upcoming wireless communication systems. However, because of their open operational nature, UAVs are highly vulnerable to severe security breaches via cyber attacks, eavesdropping on navigational and communication links, etc. Given their widespread applications, the requirement of secured UAV communications has become more and more critical since security failures can lead to detrimental consequences. Several works have examined the extent of privacy and security issues in UAV-assisted networks and introduced various mitigation techniques to address different security challenges. In this paper, a comprehensive survey is conducted that centers on the security issues related to UAV-aided networks. A descriptive taxonomy of various security intrusions on the UAV networks and commonly-used secrecy performance metrics are thoroughly reviewed. An in-depth discussion is provided on alleviating threats with proactive security techniques blended with key wireless communication technologies such as mmWave, non-orthogonal multiple access (NOMA), massive multiple-input multiple-output (MIMO), and cognitive radio. Moreover, several emerging topics like machine learning, software-defined networks, fog and edge computing, blockchain, are discussed in the context of UAV-aided secure communications.INDEX TERMS Physical layer security, unmanned aerial vehicles (UAVs), proactive mitigation techniques, secrecy metrics, emerging wireless technologies.GAURAV KUMAR PANDEY (Graduate Student Member, IEEE) received the B.Tech. degree in electrical and electronics engineering from the

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Section: ) Jammingmentioning

confidence: 99%

Security Threats and Mitigation Techniques in UAV Communications: A Comprehensive Survey

et al. 2022

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“…If we were to apply target aircraft response recognition using adaptive waveforms in CRr as an ES measure in EW, it is imperative to consider the various types of EA noise jammers as significant sources of interference such that transmit-adaptive waveforms are designed to suppress/mitigate the effects of jammer interference. In our preliminary work [27], [28] we introduced jammer nulling transmit-adaptive waveforms that function as a countermeasure against narrowband, frequency sweep and base noise jammers. In this paper, we significantly expand our design to several transmit-adaptive jammer nulling waveforms in a CRr framework for aircraft radar cross section (RCS) response recognition against a substantial list of EA noise jammers.…”

Section: As a Technologicalmentioning

confidence: 99%

“…In addition, their corresponding SNR and MI-based jammer-uncompensated transmit-adaptive waveforms are summarized. The continuous jammer-nulling and jammer-uncompensated waveform design methodology were presented in our previous works [27], [28].…”

Section: Jammer Nulling and Jammer-uncompensated Waveform Designmentioning

confidence: 99%

Jammer-Nulling Transmit-Adaptive Radar Against Knowledge-Based Jammers in Electronic Warfare

Tan

Romero

2019

IEEE Access

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The authors present transmit-adaptive jammer nulling waveforms in cognitive radar (CRr) for aircraft response recognition as a form of electronic support in the electronic warfare domain. New forms of knowledge-based noise jammers that function as a form of electronic attack to matched illumination waveforms are also introduced. These knowledge-based noise jamming techniques capitalize on prior knowledge of the target's frequency response to obscure the true target response echo. The results from simulation show that real-time adaptive waveforms suppress the effects of electronic attack noise jammers and the newly introduced knowledge-based noise jammers. High bandwidth radar cross section (RCS) responses via electromagnetic (EM) simulations of true-to-physical-size aircraft are used for simulations to produce CRr classification performance against a comprehensive list of noise jammers.

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Optimal Target Classification Using Frequency-Based Radar Waveform Design

Alshirah

Gishkori²,

Mulgrew

2022

IEEE Trans. Geosci. Remote Sensing

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In this article, we introduce a frequency-based waveform design to maximize binary target classification. The optimization problems can be solved via optimal solvers available in the literature. The presented formulation is applicable to the classification scenarios where the extended target frequency responses (TFRs) are complex, random, and normally distributed with unequal mean vectors. However, their covariance matrices are either identical or different. For the former, i.e., identical covariance matrices, the optimization problem consists of a cost function that has been obtained by deriving a closed-form expression of the probability of misclassification. For the latter, i.e., different covariance matrices, we present an optimization problem where the cost function has been obtained via the Fisher separation function. For this, we also present a closed-form expression for an approximate solution to the optimization problem. We show that the proposed solution achieves performance levels comparable to the exact solution of the optimization problem obtained via state-of-the-art optimization solvers while incurring low computational complexity. We expand on the two main scenarios by introducing clutter (i.e., signal-dependent interference) in the signal model and studying possible closed-form designs in extreme waveform energy levels. Simulations are conducted using synthetically generated data in addition to the civilian vehicle data from the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset, in order to validate the proposed method.

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Jammer Nulling Adaptive Waveforms with Cognitive Radar for Aircraft RCS Recognition in Presence of Frequency Sweep and Base Jammers

Cited by 3 publications

References 7 publications

Security Threats and Mitigation Techniques in UAV Communications: A Comprehensive Survey

Security Threats and Mitigation Techniques in UAV Communications: A Comprehensive Survey

Jammer-Nulling Transmit-Adaptive Radar Against Knowledge-Based Jammers in Electronic Warfare

Optimal Target Classification Using Frequency-Based Radar Waveform Design

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