Spectrogram-based Frequency Hopping Signal Detection in a Complex Electromagnetic Environment

Deng, Zhe; Lei, Jing

doi:10.1109/icsip55141.2022.9886713

Cited by 3 publications

(3 citation statements)

References 10 publications

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“…The duration clustering based on the DBSCAN algorithm is performed on the connected domains, and the density parameter of sample distribution within the neighborhood is set to (30,1), which represents clustering with at least one point in a circular neighborhood with a radius of 30. The clustering result is shown in Figure 6, where labels [1,2,4,5] are category 1, label 3 is category 2, labels [6,8,10,11,14,15,17,19,20,22,24] are category 3, and labels [7,9,12,13,16,18,21,23] are category 4. Due to the duration of category 1 being equal to the observation time, labels [1,2,4,5] belong to fixed-frequency interference signal.…”

Section: Connected Domain Labeling and Signal Sortingmentioning

confidence: 99%

“…Then, we reuse the time alignment algorithm for the remaining signal segments. Figure 7 shows the result of signal sorting, where fixed-speed FH signal 1 is made up of labels [6,8,10,11,14,15,17,19,22,24], fixed-speed FH signal 2 is made up of labels [7,9,13,18,21], and the variable-speed FH signal is made up of labels [3,12,16,20,23].…”

Section: Connected Domain Labeling and Signal Sortingmentioning

confidence: 99%

“…The real electromagnetic environment is complex and unpredictable, which poses a problem to the detection algorithm based on simulation data. To address this problem, an interference cancellation network that introduces a graph attention mechanism and an ensemble channel attention module with Siamese nested U-Net backbone was proposed [14], but requires a great lot of calculation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Variable-Speed Frequency-Hopping Signal Sorting: Spectrogram Is Sufficient

Zhu,

Jin,

Wang

et al. 2023

Electronics

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In this paper, we present a novel signal sorting method aimed at reducing the impact of interference and noise while achieving blind detection and accurate sorting of a variable-speed frequency-hopping communication system. To achieve this, we combine spectrogram analysis with an innovative sorting approach. First, we generate the spectrogram of the received signal, and then employ a morphology filter to effectively eliminate noise and sweep frequency interference from the spectrogram. Subsequently, we identify and mark connected domains in the spectrogram, from which we extract the duration data to create a dataset specifically for separating fixed-frequency interference. Furthermore, we propose a specialized time alignment algorithm designed to accommodate the unique characteristics of variable-speed frequency-hopping signals, enabling precise sorting of variable-speed frequency-hopping signals. Through rigorous comparative evaluations against existing algorithms, we demonstrate that our proposed approach provides superior accuracy by offering a clearer representation of the time–frequency situation of the received signals. The proposed method provides a high correct sorting probability which is equal to 0.8 when signal-to-noise ratio is 0 dB and reaches 1 when signal-to-noise ratio reaches over 12 dB. In comparison, the correct sorting probability of the comparison algorithm is far inferior to the proposed algorithm.

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Section: Connected Domain Labeling and Signal Sortingmentioning

confidence: 99%

Section: Connected Domain Labeling and Signal Sortingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Variable-Speed Frequency-Hopping Signal Sorting: Spectrogram Is Sufficient

Zhu,

Jin,

Wang

et al. 2023

Electronics

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Virtual Simulation Experiment Training Platform of Radio Measurement Technology Based on Electromagnetic Spectrum Monitoring Method Combined Online and Offline

Chu,

Chen,

Wang

2024

2024 Photonics &Amp; Electromagnetics Research Symposium (PIERS)

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The Fast and Reliable Detection of Multiple Narrowband FH Signals: A Practical Framework

Aydin,

Dalveren,

Kara

et al. 2024

Sensors

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Frequency hopping (FH) is a well-known technique that is commonly used in communication systems owing to its many advantages, including its strong anti-jamming capability. In this technique, basically, radio signals are transmitted by switching the carrier between different frequency channels. As a result, the FH signal is not stationary; hence, its spectrum is expected to change over time. Therefore, the task of detection and parameter estimation of FH signals is very challenging in practice. To address this challenge, the study presented in this article proposes a method that detects and estimates the parameters of multiple narrowband FH signals. In the proposed method, first, short-time Fourier transform (STFT) is utilized to analyze FH signals, and a practical binarization process based on thresholding is used to detect FH signals. Then, a new algorithm is proposed to ensure that the center frequencies of the detected signals are successfully separated. Next, another algorithm is proposed to estimate the parameters of the detected signals. After estimating the parameters for the entire spectrum, an approach is used to detect FH signals. Lastly, the hop-clustering process is applied to separate the hops into groups without time overlap. The simulation results show that the proposed method can be an efficient way for the fast and accurate parameter estimation and detection of multiple narrowband FH signals.

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Spectrogram-based Frequency Hopping Signal Detection in a Complex Electromagnetic Environment

Cited by 3 publications

References 10 publications

Variable-Speed Frequency-Hopping Signal Sorting: Spectrogram Is Sufficient

Variable-Speed Frequency-Hopping Signal Sorting: Spectrogram Is Sufficient

Virtual Simulation Experiment Training Platform of Radio Measurement Technology Based on Electromagnetic Spectrum Monitoring Method Combined Online and Offline

The Fast and Reliable Detection of Multiple Narrowband FH Signals: A Practical Framework

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