Taylan O. Gulum

Extraction of polyphase radar modulation parameters using a wigner-ville distribution - radon transform

Often used in low probability of intercept continuous waveform (CW) emitters, polyphase modulations can have extremely long code lengths (large processing gain), good sidelobe performance and robust Doppler tolerance. This paper presents an efficient algorithm to autonomously extract the polyphase radar modulation parameters from an intercepted waveform using a Wigner-Ville Radon transform. Results show that our method results in a small relative error in the extracted parameters for signal-to-noise ratios as low as - 6dB.

A parameter extraction technique for FMCW radar signals using Wigner-Hough-Radon transform

An autonomous parameter extraction algorithm for frequency modulated continuous wave (FMCW) radar signals using Wigner-Ville Distribution (WVD)-Hough transform was investigated in [1] and extraction of polyphase radar modulation parameters using a Wigner-Ville distribution-Radon transform was investigated in [2]. The algorithm in [1] produced very dependable results with as low as -6 dB SNR levels, however some degradation has been observed below -6 dB SNR. The proposed approach in this study uses the WVD as a time-frequency (T-F) detection technique and combined Hough-Radon transform (HRT) to identify the parameters of the modulation. We showed that our algorithm can extract FMCW radar modulation parameters at low SNR levels, such as -9 dB, efficiently.

Parameter extraction of FMCW modulated radar signals using Wigner-Hough transform

In this study, an autonomous parameter extraction algorithm for frequency modulated continuous wave (FMCW) radar signals using Wigner-Hough transform is investigated. The algorithm can be applied to other low probability of intercept (LPI) radar waveforms as well. The proposed method uses the Pseudo-Wigner-Ville Distribution (PWVD) as a time-frequency (T-F) detection technique and Hough Transform (HT) to identify the parameters of the modulation. Using the images obtained by the PWVD, the algorithm derives the significant modulation parameters of FMCW waveforms by using the HT. Autonomously detecting and analyzing FMCW and other LPI modulations can eliminate the need for human intervention and enable near real-time detection and analysis of signal modulations. The extracted parameters can later be compared with existing emitter parameters in a database for identification.

PWVD resolution considerations for LFMCW signal detection by WHT

Linear Frequency Modulated Continuous Waveform (LFMCW) is one of the most common waveforms used in low probability of intercept (LPI) radars. The Wigner-Hough transform (WHT) is a powerful technique for detection and parameter extraction of LFMCW waveforms that can be employed by Electronic Support Receivers. For a fast detection and a timely response to the adversary emitter, the selection of the pseudo Wigner-Ville distribution (PWVD) window length is critical. In this work we analyze the relation between PWVD window length, WHT span angle and span resolution. It is shown that faster correct detections can be achieved by decreasing the PWVD window length and consequently decreasing the WHT plane. A rapid detection and apiori estimation of target emitter signal chirp rate will allow enough time for a fine tuned post-processing which can be applied specifically to the a priori estimates.

Defining the effective threshold using modified wigner-hough transform in FMCW-signal detection

In response to the fast improvements in anti-radiation systems and electronic attack systems, radar systems began exploiting low power, wide-band, frequency agility techniques to decrease their intercept probability. This increase in the use of low probability of intercept (LPI) waveforms in current radar systems enforces the intercept receiver to use sophisticated signal processing algorithms. It has been observed that, the threshold applied on Wigner-Ville images has an impact on the efficiency of Wigner-Hough based algorithms. In this study, we investigated the effect of the WV threshold on signals with SNRs ranging from [0dB, -9dB], and suggested that the optimum threshold is between 20-40% of the max WV image energy intensity.

FMCW Signal Detection and Parameter Extraction by Cross Wigner–Hough Transform

The combination of Wigner–Ville distribution (WVD) and Hough transform (HT) has been successfully used in detection and parameter extraction of frequency modulated continuous waveform (FMCW) signals. In this paper, a combination of Cross–Wigner–Ville and HT [(Cross Wigner–Hough transform (XWHT)] is proposed for detection and parameter extraction of FMCW signals with a novel methodology. The XWHT method makes use of the cross-terms created by WVD instead of trying to suppress them. Utilization of the properties of the cross-terms to detect and unveil the parameters of FMCW signals on HT space is a new approach. The performance of the method is compared with other Wigner–Hough transform-based methods in terms of transform speed, parameter extraction, and detection performance. As a result, this study proposes that the XWHT is a candidate method to be used in digital electronic support receivers’ automatic signal detection and analysis capabilities due to its speed and performance.

Implementation aspects of Wigner-Hough Transform based detectors for LFMCW signals

Linear Frequency Modulated Continuous Waveform (LFMCW) waveforms are widely used in Low Probability of Intercept (LPI) radars. In this work, Wigner-Hough based transforms are used to detect such waveforms. They are investigated for three aims: Minimizing the effects of Wigner-Ville Distribution (WVD) cross-terms in the transforms, reducing the complexity of hardware implementation and producing the transform results faster. Modified Wigner-Hough Transform (MWHT) is analyzed for the first aim. Sample and hold type intermediate sampling and column-based thresholding techniques are examined for the second and third aims. A signal database (3000 signals with different SNR levels) is created and used to evaluate the performances of 8 alternative methods on probability of detection and probability of chirp rate estimation. The results are compared for -3dB down to -14dB SNR levels. Proposed method is found to be the best candidate to be implemented on Field Programmable Gate Arrays (FPGA) since it produces better performance with less computational density.

Improving Wigner-Hough Transform for hardware implementation to intercept LFMCW signals

Linear Frequency Modulated Continuous Waveform is generally used in Low Probability of Intercept radars. In studies to intercept this waveform with Wigner-Hough Transform based methods at low SNR (-8dB and below) values it is an important design criteria to obtain the resulting performance with less computation density. The decrease in computation density will provide the use of fewer resources in hardware implementation and less delay to obtain results. In this study; effects of sample and hold type intermediate sampling on Wigner Hough Transformation are examined and it is intended to reduce the complexity by means of the proposed columnar thresholding method. Using the simulated signal database, the Probability of Detection and the Probability of Chirp Rate Estimation are calculated for proposed and alternative methods, then performance for low SNR values are compared.

Elliptic Gaussian filtering for Time-Frequency signal analysis

Increased use of low probability of intercept (LPI) waveforms in current radar systems, enforces the use of sophisticated hardware and signal processing algorithms in intercept receiver technology. In this study, an adaptive filtering technique based on elliptic Gaussian filter is proposed to be used by intercept receivers. The filter is implemented on Wigner-Ville Distribution (WVD) images of different intercepted LPI radar waveforms to de-noise the image in order to help the Electronic Support operators in the signal analysis effort. The slope of the LFM waveforms, thus the filters, can be determined by using Hough Transform, Radon Transform or any other method.

Enhanced LPI Waveform Representation by Ambiguity-Domain Elliptical Gaussian Filtering

ESM systems need to use sophisticated signal processing, such as time-frequency representation techniques, for the interception of nonstationary LPI radar signals. In this study, an adaptive filtering technique using an ambiguity-domain elliptical Gaussian kernel is proposed to increase the readability of pseudo-Wigner–Ville distribution based representations for LPI waveform parameter extraction purposes. The complexity and information content of the outputs obtained by the proposed method are evaluated by objective criteria, such as ratio of norms, Rényi entropy, and Jubisa measure. The results quantify efficient filtering performance under severe SNR conditions with lower computational complexity.