Educational Journey
Clarkson University
Ph.D., B.S. in Electrical Engineering, M.S. in Physics • Electrical Engineering
Experience
United States Air Force Research Laboratory
0 - 0Clarkson University
0 - 0Research
A Unique Method for Detecting and Characterizing Low Probability of Intercept Frequency Hopping Radar Signals by means of the Wigner-Ville Distribution and the Reassigned Smoothed Pseudo Wigner-Ville Distribution
Low probability of intercept radar signals, which are may times difficult to detect and characterize, have as their goal ‘to see but not be seen’. Digital intercept receivers are currently moving away from Fourier-based techniques and toward classical time-frequency techniques for analyzing low probability of intercept radar signals. This paper brings forth the unique approach of both detecting and characterizing low probability of intercept frequency hopping radar signals by employing and comparing the Wigner-Ville Distribution and the Reassigned Smoothed Pseudo Wigner-Ville Distribution. Four-component frequency hopping low probability of intercept radar signals were analyzed. 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 relative processing time. Experimental results demonstrate that overall, the Reassigned Smoothed Pseudo Wigner-Ville Distribution produced more accurate characterization metrics than the Wigner-Ville Distribution. An improvement in performance could potentially translate into saved equipment and lives.
Joint Sequential Use of the Reassigned Smoothed Pseudo Wigner
Digital intercept receivers are moving away from Fourier-based analysis towards classical time-frequency analysis techniques along with other novel analysis techniques for the purpose of analyzing low probability of intercept radar signals. This paper presents a novel approach of the joint sequential use of the Reassigned Smooth Pseudo Wigner-Ville Distribution and the Hough Transform versus the Reassigned Smooth Pseudo Wigner-Ville Distribution for characterizing low probability of intercept triangular modulated frequency modulated continuous wave radar signals. The metrics used for evaluation were - percent error of the chirp rate, percent detection, and lowest signal-to-noise ratio for signal detection. Experimental results demonstrate that overall, the joint sequential use of the Reassigned Smooth Pseudo Wigner-Ville Distribution and the Hough Transform signal processing techniques produced more accurate metrics than the Reassigned Smooth Pseudo Wigner-Ville Distribution signal processing technique. An improvement in the accuracy of metrics may well equate to an increase in personnel safety.
Detection and Characterization of Low Probability of Intercept Triangular Modulated Frequency Modulated Continuous Wave Radar Signals in Low SNR Environments Using the Scalogram and the Reassigned Scalogram
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 Scalogram versus the Reassigned Scalogram. 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, and chirp rate. Also used were: percent detection, lowest signal-to-noise ratio for signal detection, and time-frequency localization (x and y direction). Experimental results demonstrate that overall, the Reassigned Scalogram produced more accurate characterization metrics than the Scalogram.
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
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.
Detection and Parameter Extraction of Low Probability of Intercept Frequency Hopping Signals using the Spectrogram and the Reassigned Spectrogram
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 Fourierbased techniques, they still suffer from a lack of readability –which can be caused by poor timefrequency 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.
Discrete-Time, Discrete-Frequency Reassignment Method
The reassignment method is a non-linear, postprocessin technique which cans improve the localization of a time-frequency distribution by moving its values according to a suitable vector field. The reassignment method’s scheme assumes that the energy distribution in the time-frequency plane resembles a mass distribution and moves each value of the time-frequencyplane located at a point (ð’•ð’•ð’•ð’•, ð’‡ð’‡ð’‡ð’‡)to another point,(ð’•ð’•ð’•ð’•â„˜,ð’‡ð’‡ð’‡ð’‡ ℘), which is the center of gravity of the energy distribution in the area of (ð’•ð’•ð’•ð’•, ð’‡ð’‡ð’‡ð’‡). The result is a focused representation with very highintensity [11]. During this research it was investigated and determined that the frequency reassignment corrections derived from the Flandrin reassignment method have undesired noise sensitivity at very small noise levels as well as undesired observed distortions. In order to address these issues, a novel approach was derived-the discrete-time, discrete-frequency formulation of frequency reassignment. It is shown that in noise-free tone scenarios, this novel approach eliminates ambiguity and provides less distortion than the Flandrin reassignment method.
Low Probability of Intercept Frequency Hopping Signal Characterization Comparison Using the Wigner Ville Distribution and the Choi Williams Distribution
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 signalto- 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 could potentially translate into saved equipment and lives.
Low Probability of Intercept Triangular Modulated Frequency Modulated Continuous Wave Signal Characterization Comparison using the Spectrogram and the Scalogram
Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical timefrequency 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.
Low Probability of Intercept Frequency Hopping Signal Characterization Comparison using the Spectrogram and the Scalogram
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 timefrequency localization. Also used were: percent detection, lowest signal-to-noise ratio for signal detection, and plot (processing) time. Experimental results demonstrate that overall, the Scalogram produced more accurate characterization metrics than the Spectrogram. An improvement in performance may well translate into saved equipment and lives.
Detection and Parameter Extraction of Low Probability of Intercept Radar Signals using the Hough Transform
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 suppress cross-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.
