Cognitive radar parameter optimization in a congested spectrum environment

Oechslin, R.; Wellig, Peter; Hinrichsen, S.; Wieland, Sebastian; Aulenbacher, Uwe; Rech, Klaus

doi:10.1109/radar.2018.8378560

Cited by 9 publications

(3 citation statements)

References 8 publications

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“…Cognitive radar methods use mimic elements of human cognition, such as the cycle of perception-action, deep learning, intelligence and the use of existing knowledge [22]. Cognitive radar vision methods use radar spectrum [23], [24], radiation optimization [25], tracking [26][27][28], beam control [29], interference reduction [30], network [31], resource management [32] .…”

Section: Organization Of Cognitive Computingmentioning

confidence: 99%

“…A backpropagation neural network is one known method for creating a trained machine or system that can provide a fi nal classifi cation decision through a series of learning processes. It can be developed using the tools provided in MATLAB, but sometimes this leads to diff erent detection and recognition accuracy of objects for each experiment [30][31].…”

Section: Deep Learning Of the Cognitivementioning

confidence: 99%

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The problem of developing the architecture of modern cognitive radar system

Kosovets¹,

Tovstenko²

2022

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The problem of developing the architecture of modern cognitive radar systems using artificial intelligence technologies is considered. The main diﬀerence from traditional systems is the use of a trained neural network. The heterogeneous multiprocessor system is rebuilt in the process of solving the problem, providing reliability and solving various types of problems of one class and deep learning of the neural network in real time. This architecture promotes the introduction of cognitive technologies that take into account the requirements for the purpose, the influence of external and internal factors.

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Section: Organization Of Cognitive Computingmentioning

confidence: 99%

Section: Deep Learning Of the Cognitivementioning

confidence: 99%

The problem of developing the architecture of modern cognitive radar system

Kosovets¹,

Tovstenko²

2022

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“…Another major limitation of large bandwidth is that the noise will increase with the bandwidth, resulting in a lowering of the SNR. In some radar systems, e.g., cognitive radars [115], the bandwidth can be tuned in real-time depending on the scenario. An UWB radar and multiple aerial vehicles tracking algorithms are used in [116].…”

Section: G Frequency and Bandwidthmentioning

confidence: 99%

A Survey on Radar Techniques for Detection,Tracking, and Classification of Aerial Threats

Khawaja¹

2022

Preprint

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<p> The use of unmanned aerial vehicles (UAVs) for different applications has increased many folds in recent years. The UAVs are expected to change the future air operations. However, there are instances where the UAVs can be used for malicious purposes. The detection, tracking, and classification of UAVs is challenging compared to manned aerial vehicles (MAVs) mainly due to small size, complex shapes, and ability to fly close to the terrain and in autonomous flight patterns in swarms. In this survey, we will discuss current and future aerial threats, and provide an overview of radar systems to counter such threats. We also study the performance parameters of radar systems for the detection, tracking, and classification of UAVs compared to MAVs. Finally, limitations of radar systems and comparison with other techniques that do not rely on radars for detection, tracking, and classification of aerial threats are also provided. </p>

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