Detection of the chirp signal features caused by Doppler phenomenon in the presence of destructive agents based on cyclostationary and Hough transform methods. Issue 4 (1st June 2018)

• Record Type: Journal Article
• Authors: Heydari, Kazem; Azmi, Paeiz; Arand, Bijan Abbasi; Heydari, Akbar
• Is Part Of: IET signal processing. Volume 12:Issue 4(2018)
• Page Start: 394
• Page End: 402
• Publication Date: 2018-06-01
• Subjects: Hough transforms -- signal detection -- feature extraction -- Doppler effect -- chirp modulation -- Gaussian noise -- frequency modulation -- object detection; cyclostationary subspace -- target detection -- linear frequency modulation detection -- linear frequency modulation extraction -- GACS‐HT approach -- generalised almost‐cyclostationary signal processing -- Gaussian noise -- destructive factor -- Hough transform methods -- destructive agents -- Doppler phenomenon -- chirp signal feature detection; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/iet-spr.2017.0092
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract : This study deals with investigating the chirp signal detection obtained from the moving target in the presence of the destructive factor (leakage) and Gaussian noise using the generalised almost‐cyclostationary (GACS) and Hough transform (HT) signal processing altogether (i.e. GACS–HT) approaches. To do so, a receiver was designed hierarchically using the above approach in this study. In this receiver, the detection and extraction of linear frequency modulation takes place in the subspace of the cyclostationary and Hough which have unique characteristics. In order to detect the target, the relative velocity was analysed in the cyclostationary subspace while the relative acceleration was analysed in the Hough space. Due to using the simulation, the behaviour of this receiver was measured by different subspaces for different parameters in the presence of noise and destructive factor. Ultimately, the efficiency of the presented approach was analysed and compared with other approaches. The results indicated that the GACS–HT approach is more efficient than the energy detector approach and in terms of complexity it is almost as complex as the LV transform approach.