scholarly journals A Novel Approach for the Characterization of Triangular Modulated Frequency Modulated Continuous Wave Low Probability of Intercept Radar Signals via Application of the Wigner-Ville Distribution

2021 ◽  
pp. 19-28
Author(s):  
Daniel L. Stevens
Keyword(s):  
Signal Processing ◽  
Continuous Wave ◽  
Processing Technique ◽  
Signal Processing Technique ◽  
Time Frequency ◽  
Novel Approach ◽  
Wave Radar ◽  
Low Probability ◽  
Low Probability Of Intercept ◽  
Radar Signals

Digital intercept receivers are changing from Fourier-based analysis to classical time-frequency analysis techniques for analyzing low probability of intercept radar signals. This paper presents a novel approach of characterizing low probability of intercept triangular modulated frequency modulated continuous wave radar signals through utilization and direct comparison of the signal processing techniques Wigner-Ville Distribution versus the Reassigned Smooth Pseudo Wigner-Ville Distribution. The following metrics were used for evaluation: percent error of: carrier frequency, modulation bandwidth, modulation period, chirp rate, and time-frequency localization (x and y direction). Also used were: percent detection, lowest signal-to-noise ratio for signal detection, and plot (processing) time. Experimental results demonstrate that overall, the Reassigned Smooth Pseudo Wigner-Ville Distribution signal processing technique produced more accurate characterization metrics than the Wigner-Ville Distribution signal processing technique.

scholarly journals Low Probability of Intercept Triangular Modulated Frequency Modulated Continuous Wave Signal Characterization Comparison using the Spectrogram and the Scalogram

2017 ◽  
pp. 37-47
Author(s):  
Daniel L. Stevens ◽  
Stephanie A. Schuckers
Keyword(s):  
Continuous Wave ◽  
Signal To Noise Ratio ◽  
Time Frequency ◽  
Novel Approach ◽  
Wave Radar ◽  
Time Frequency Localization ◽  
Low Probability ◽  
Low Probability Of Intercept ◽  
Radar Signals ◽  
Continuous Wave Signal

Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical time-frequency analysis techniques for the purpose of analyzing low probability of intercept radar signals. This paper presents the novel approach of characterizing low probability of intercept frequency modulated continuous wave radar signals through utilization and direct comparison of the Spectrogram versus the Scalogram. Two different triangular modulated frequency modulated continuous wave signals were analyzed. The following metrics were used for evaluation: percent error of: carrier frequency, modulation bandwidth, modulation period, chirp rate, and time-frequency localization (x and y direction). Also used were: percent detection, lowest signal-to-noise ratio for signal detection, and plot (processing) time. Experimental results demonstrate that overall, the Spectrogram produced more accurate characterization metrics than the Scalogram. An improvement in performance may well translate into saved equipment and lives.

scholarly journals Low Probability of Intercept Triangular Modulated Frequency Modulated Continuous Wave Signal Characterization Comparison Using the Wigner Ville Distribution and the Choi Williams Distribution

2019 ◽  
pp. 35-44
Author(s):  
Daniel L. Stevens
Keyword(s):  
Continuous Wave ◽  
Signal To Noise Ratio ◽  
Time Frequency ◽  
Novel Approach ◽  
Wave Radar ◽  
Time Frequency Localization ◽  
Low Probability ◽  
Low Probability Of Intercept ◽  
Radar Signals ◽  
Continuous Wave Signal

Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical time frequency analysis techniques for the purpose of analyzing low probability of intercept radar signals. This paper presents the novel approach of characterizing low probability of intercept triangular modulated frequency modulated continuous wave radar signals through utilization and direct comparison of the Wigner Ville Distribution versus the Choi Williams Distribution. The following metrics were used for evaluation: percent error of: carrier frequency, modulation bandwidth, modulation period, chirp rate, and time-frequency localization (x and y direction). Also used were: percent detection, lowest signal-to noise ratio for signal detection, and plot (processing) time. Experimental results demonstrate that overall, the Wigner Ville Distribution produced more accurate characterization metrics than the Choi Williams Distribution. An improvement in performance may well translate into an increase in personnel safety.

scholarly journals Detection and Parameter Extraction of Low Probability of Intercept Radar Signals using the Hough Transform

2016 ◽  
pp. 9-25
Author(s):  
Daniel L. Stevens ◽  
Stephanie A. Schuckers
Keyword(s):  
Hough Transform ◽  
Continuous Wave ◽  
Parameter Extraction ◽  
Time Frequency ◽  
Low Snr ◽  
Analysis Technique ◽  
Shift Keying ◽  
Low Probability ◽  
Low Probability Of Intercept ◽  
Radar Signals

Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical time-frequency analysis techniques, such as the Wigner-Ville distribution, Choi-Williams distribution, spectrogram, and scalogram, for the purpose of analyzing low probability of intercept radar signals (e.g. triangular modulated frequency modulated continuous wave and frequency shift keying). Although these classical time-frequency techniques are an improvement over the Fourier-based analysis, they still suffer from a lack of readability, due to cross-term interference, and a mediocre performance in low SNR environments. This lack of readability may lead to inaccurate detection and parameter extraction of these radar signals. In this paper, the use of the Hough transform, because of its ability to suppresscross-term interference, separate signals from cross-terms, and perform well in the presence of noise, is proposed as an improved signal analysis technique. With these qualities, the Hough transform has the potential to produce better readability and consequently, more accurate signal detection and parameter extraction metrics.

scholarly journals Low Probability of Intercept Frequency Hopping Signal Characterization Comparison Using the Wigner Ville Distribution and the Choi Williams Distribution

2018 ◽  
pp. 1-10
Author(s):  
Daniel L. Stevens ◽  
Stephanie A. Schuckers
Keyword(s):  
Frequency Hopping ◽  
The Novel ◽  
Modulation Bandwidth ◽  
Time Frequency ◽  
Novel Approach ◽  
Time Frequency Localization ◽  
Low Probability ◽  
Low Probability Of Intercept ◽  
Radar Signals ◽  
Signal Characterization

Low probability of intercept radar signals, which are often challenging to detect and characterize, have as their objective ‘to see and not be seen’. Digital intercept receivers are currently moving from Fourier-based techniques to classical time-frequency techniques for the analysis of low probability of intercept radar signals. This paper presents the novel approach of characterizing low probability of intercept frequency hopping radar signals through utilization and direct comparison of the Wigner Ville Distribuion versus the Choi Williams Distribution. Two different frequency hopping low probability of intercept radar signals were analyzed (4-component and 8-component). The following metrics were used for evaluation: percent error of:carrier frequency, modulation bandwidth, modulation period, and time-frequency localization. Also used were: percent detection, lowest signaltonoise ratio for signal detection, and plot (processing) time.

scholarly journals Low Probability of Intercept Frequency Hopping Signal Characterization Comparison using the Spectrogram and the Scalogram

2016 ◽  
pp. 13-23 ◽  
Author(s):  
Daniel L. Stevens ◽  
Stephanie A. Schuckers
Keyword(s):  
Signal To Noise Ratio ◽  
Frequency Hopping ◽  
The Novel ◽  
Time Frequency ◽  
Novel Approach ◽  
Time Frequency Localization ◽  
Low Probability ◽  
Low Probability Of Intercept ◽  
Radar Signals ◽  
Signal Characterization

Low probability of intercept radar signals, which are often problematic to detect and characterize, have as their goal ‘to see and not be seen’. Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical time-frequency analysis techniques for the purpose of analyzing these low probability of intercept radar signals. This paper presents the novel approach of characterizing low probability of intercept frequency hopping radar signals through utilization and direct comparison of the Spectrogram versus the Scalogram. Two different frequency hopping low probability of intercept radar signals were analyzed(4-component and 8-component). The following metrics were used for evaluation: percent error of:carrier frequency, modulation bandwidth, modulation period, and time-frequency localization. Also used were: percent detection, lowest signal-to-noise ratio for signal detection, and plot (processing) time. Experimental results demonstrate that overall,theScalogram produced more accurate characterization metrics than the Spectrogram. An improvement in performance may well translate into saved equipment and lives.

scholarly journals Application of UAV in Search and Rescue Actions in Underground Mine—A Specific Sound Detection in Noisy Acoustic Signal

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3725
Author(s):  
Paweł Zimroz ◽  
Paweł Trybała ◽  
Adam Wróblewski ◽  
Mateusz Góralczyk ◽  
Jarosław Szrek ◽  
...  
Keyword(s):  
Signal Processing ◽  
Acoustic Signal ◽  
Processing Technique ◽  
Underground Mine ◽  
Search And Rescue ◽  
Reference Spectrum ◽  
Signal Processing Technique ◽  
Time Frequency ◽  
Communication Device ◽  
Frequency Representation

The possibility of the application of an unmanned aerial vehicle (UAV) in search and rescue activities in a deep underground mine has been investigated. In the presented case study, a UAV is searching for a lost or injured human who is able to call for help but is not able to move or use any communication device. A UAV capturing acoustic data while flying through underground corridors is used. The acoustic signal is very noisy since during the flight the UAV contributes high-energetic emission. The main goal of the paper is to present an automatic signal processing procedure for detection of a specific sound (supposed to contain voice activity) in presence of heavy, time-varying noise from UAV. The proposed acoustic signal processing technique is based on time-frequency representation and Euclidean distance measurement between reference spectrum (UAV noise only) and captured data. As both the UAV and “injured” person were equipped with synchronized microphones during the experiment, validation has been performed. Two experiments carried out in lab conditions, as well as one in an underground mine, provided very satisfactory results.

Detection and Parameter Extraction of Low Probability of Intercept Frequency Hopping Signals using the Spectrogram and the Reassigned Spectrogram

2020 ◽  
pp. 11-20
Author(s):  
Daniel L. Stevens
Keyword(s):  
Frequency Analysis ◽  
Parameter Extraction ◽  
Frequency Hopping ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Analysis Techniques ◽  
Time Frequency Localization ◽  
Low Probability ◽  
Low Probability Of Intercept ◽  
Radar Signals

Low probability of intercept radar signals, which are often problematic to detect and characterize, have as their goal ‘to see and not be seen’. Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical time-frequency analysis techniques for the purpose of analyzing these low probability of intercept radar signals. Although these classical time-frequency analysis techniques are an improvement over existing Fourier-based techniques, they still suffer from a lack of readability –which can be caused by poor time-frequency localization (such as the spectrogram), which may in turn lead to inaccurate detection and parameter extraction. In this study, the reassignment method, because of its ability to improve time-frequency localization, is proposed as an improved signal analysis technique to address the poor time-frequency localization deficiency of the spectrogram. This paper presents the novel approach of characterizing low probability of intercept frequency hopping radar signals through utilization and direct comparison of the spectrogram versus the reassigned spectrogram.

scholarly journals A Reservoir Information Extraction Method Based on Improved Hilbert-Huang Transform

2019 ◽  
pp. 85-90
Author(s):  
Qingmi Yang
Keyword(s):  
Signal Processing ◽  
Seismic Signal ◽  
Ensemble Empirical Mode Decomposition ◽  
Processing Technique ◽  
Intrinsic Mode Functions ◽  
Signal Processing Technique ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Non Stationary Signal

Hilbert-Huang transform (HHT) is a nonlinear non-stationary signal processing technique, which is more effective than traditional time-frequency analysis methods in complex seismic signal processing. However, this method has problems such as modal aliasing and end effect. The problem causes the accuracy of signal processing to drop. Therefore, this paper introduces the method of combining the Ensemble Empirical Mode Decomposition (EEMD) and the Normalized Hilbert transform (NHT) to extract the instantaneous properties. The specific process is as follows: First, the EEMD method is used to decompose the seismic signal to a series of Intrinsic Mode Functions (IMF), and then The IMFs is screened by using the relevant properties, and finally the NHT is performed on the IMF to obtain the instantaneous properties.

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