Non‐analytical direction‐finding method as a key step in pursuing low size, weight, costs, and computational power in the deinterleaving of radar pulses

Mello, Rafael Gonçalves Licursi de; Sousa, Francinalva Cordeiro de

doi:10.1049/iet-rsn.2018.5011

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Cited by 3 publications

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Emerging Use Cases of Metasurfaces in EW

2024

Metasurface‐Driven Electronic Warfare

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Emerging Use Cases of Metasurfaces in EW

2024

Metasurface‐Driven Electronic Warfare

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Wideband Machine-Learning-Based Amplitude-Only Direction Finding With Spiral Antennas

Friedrichs,

Elmansouri,

Filipovic

2023

IEEE Trans. Antennas Propagat.

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Real-Time Radar Classification Based on Software-Defined Radio Platforms: Enhancing Processing Speed and Accuracy with Graphics Processing Unit Acceleration

Oncu,

Karakaya,

Dalveren

et al. 2024

Sensors

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This paper presents a comprehensive evaluation of real-time radar classification using software-defined radio (SDR) platforms. The transition from analog to digital technologies, facilitated by SDR, has revolutionized radio systems, offering unprecedented flexibility and reconfigurability through software-based operations. This advancement complements the role of radar signal parameters, encapsulated in the pulse description words (PDWs), which play a pivotal role in electronic support measure (ESM) systems, enabling the detection and classification of threat radars. This study proposes an SDR-based radar classification system that achieves real-time operation with enhanced processing speed. Employing the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm as a robust classifier, the system harnesses Graphical Processing Unit (GPU) parallelization for efficient radio frequency (RF) parameter extraction. The experimental results highlight the efficiency of this approach, demonstrating a notable improvement in processing speed while operating at a sampling rate of up to 200 MSps and achieving an accuracy of 89.7% for real-time radar classification.

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Non‐analytical direction‐finding method as a key step in pursuing low size, weight, costs, and computational power in the deinterleaving of radar pulses

Cited by 3 publications

References 20 publications

Emerging Use Cases of Metasurfaces in EW

Emerging Use Cases of Metasurfaces in EW

Wideband Machine-Learning-Based Amplitude-Only Direction Finding With Spiral Antennas

Real-Time Radar Classification Based on Software-Defined Radio Platforms: Enhancing Processing Speed and Accuracy with Graphics Processing Unit Acceleration

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