| Current radar systems employ new types of signals which are difficult to detect and characterize. These signals are known as low probability of intercept radar signals, which have as their goal 'to see and not be seen' by intercept receivers, devices which are designed to detect and extract information from radar emissions. Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical time-frequency analysis techniques, based on 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 poor time-frequency localization, cross-term interference, and a mediocre performance in low signal-to-noise ratio environments. This lack of readability may lead to inaccurate detection and parameter extraction of these radar signals, making for a less informed (and therefore less safe) intercept receiver environment. In this dissertation, the reassignment method, because of its ability to smooth out cross-term interference and improve time-frequency localization, is proposed as an improved signal analysis technique. In addition, the Hough transform, due to its ability to suppress cross-term interference, separate signals from cross-term interference, and perform well in a low signal-to-noise ratio environment, is also proposed as an improved signal analysis technique. With these qualities, both the reassignment method and the Hough transform have the potential to produce better readability and consequently, more accurate signal detection and parameter extraction metrics. Simulations are presented that compare time-frequency representations of the classical time-frequency techniques with those of the reassignment method and the Hough transform. Two different triangular modulated frequency modulated continuous wave low probability of intercept radar signals and two frequency shift keying low probability of intercept radar signals (4-component and 8-component) were analyzed. The following metrics were used for evaluation of the analysis: percent error of: carrier frequency, modulation bandwidth, modulation period, time-frequency localization, and chirp rate. Also used were: percent detection, number of cross-term false positives, lowest signal-to-noise ratio for signal detection, and plot (processing) time. Experimental results demonstrate that the 'squeezing' and 'smoothing' qualities of the reassignment method, along with the cross-term interference suppressing/separating and low signal-to-noise ratio performance qualities of the Hough transform, do in fact lead to improved readability over the classical time-frequency analysis techniques, and consequently, provide more accurate signal detection and parameter extraction metrics than the classical time-frequency analysis techniques. In addition, the Hough transform was utilized to detect, extract parameters, and properly identify a real-world low probability of intercept radar signal in a low signal-to-noise ratio environment, where classical time-frequency analysis failed. In summary, this dissertation provides evidence that the reassignment method and the Hough transform have the potential to outperform the classical time-frequency analysis techniques, which are the current state-of-the-art, cutting edge techniques for this arena. An improvement in performance can easily translate into saved equipment and lives. Future work will include automation of metrics extraction process, analysis of additional low probability of intercept radar waveforms of interest, and analysis of other real-world low probability of intercept radar signals utilizing more powerful computing platforms. |
