Stand-off Jamming Method in Electronic Warfare against Defense Systems

Majlesi Journal of Telecommunication Devices

دوره 12، شماره 4 - شماره پیاپی 48، اسفند 2023، صفحه 201-208   

نوع مقاله: Reseach Article

شناسه دیجیتال (DOI): 10.30486/mjtd.2023.1988165.1035

نویسندگان

Saeed Talati¹؛ Pouriya Etezadifar^{* 2}؛ Mohammad Reza Hassani Ahangar³؛ Mahdi Molazade⁴

¹PhD Candidate, Faculty of Electrical Engineering, Imam Hossein University, Tehran, Iran.

²Assistant Professor, Faculty of Electrical Engineering, Imam Hossein University, Tehran, Iran.

³Professor, Faculty of Electrical Engineering, Imam Hossein University, Tehran, Iran

⁴Assistant Professor, Faculty of Electrical Engineering, Imam Hossein University, Tehran, Iran

چکیده

This article compares the quality and complexity of LPC, CELP, and MELP standard audio encoders. These standards are based on linear predictive and are used in sound (speech) processing. These standards are powerful high-quality speech coding methods that provide highly accurate estimates of audio parameters and are widely used in the commercial (mobile) and military (NATO) communications industries. To compare LPC, CELP, and MELP audio encoders in two male and female voice modes and four voice models: quiet, Audio recorded without sound by the microphone, MCE, office, and two noise models 1% and 05% were used. The simulation results show the complexity of MELP is higher than LPC and CELP in terms of both processor and memory requirements. The MELP analyzer requires 72% of its total processing time. This additional memory is, of course, due to the vector quantization tables that MELP uses for the linear spectral frequencies (LSFs) and the Fourier magnitude. Also, according to the quality comparison test using the MOS index, MELP has the highest score, followed by CELP and LPC.

کلیدواژه‌ها

Quality؛ Complexity؛ LPC؛ CELP؛ MELP

مراجع

• Bishnu Atal "The History of Linear Prediction". ICASSP '78. IEEE Signal Processing Magazine, vol.23, no2, march 2006. 154-161.
• Bishnu Atal and Manfred Schroeder. "Predictive coding of speech signals and subjective error criteria". ICASSP '78. IEEE International Conference on Acoustics, Speech, and Signal Processing. 3: 573–576, 1978.
• V. McCree and T. P. Barnwell, "A mixed excitation LPC vocoder model for low bit rate speech coding". IEEE Transactions on Speech and Audio Processing, vol. 3, no. 4, pp. 242-250, July 1995.
• J. D. van Schalkwyk, D. J. Joubert and J. G. van der Linde, "Linear predictive speech coding at 2400 b/s," in Transactions of the South African Institute of Electrical Engineers, vol. 84, no. 3, pp. 146-152, June 1993.
• Schroeder and B. Atal, "Code-excited linear prediction (CELP): High-quality speech at very low bit rates,"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1985, pp. 937-940, doi: 10.1109/ICASSP.1985.1168147.
• Weiran Lin, Soo Ngee Koh and Xiao Lin, "Mixed excitation linear prediction coding of wideband speech at 8 kbps,"2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2000, pp. II1137-II1140 vol.2, doi: 10.1109/ICASSP.2000.859165.
• D. Tardelli, E.W. Kreamer, “Vocoder Intelligibility and Quality Test Methods”, IEEE International Conference on Acoustics, Speech, and Signal Processing, Atlanta, Georgia, USA, 1996.
• A. Kohler, "A comparison of the new 2400 bps MELP Federal Standard with other standard coders,"1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1997, pp. 1587-1590 vol.2, doi: 10.1109/ICASSP.1997.596256.
• Saeed Talati, Pouriya Etezadifar. (2020). “Providing an Optimal Way to Increase the Security of Data Transfer Using Watermarking in Digital Audio Signals”,MJTD, vol. 10, no. 1.
• Hashemi, Seyed & Barati, Shahrokh & Talati, S. & Noori, H. (2016). “A genetic algorithm approach to optimal placement of switching and protective equipment on a distribution network”. Journal of Engineering and Applied Sciences. 11. 1395-1400.
• Hashemi, Seyed & Abyari, M. & Barati, Shahrokh & Tahmasebi, Sanaz & Talati, S. (2016). “A proposed method to controller parameter soft tuning as accommodation FTC after unknown input observer FDI”. Journal of Engineering and Applied Sciences. 11. 2818-2829.
• Talati, A. Rahmati, and H. Heidari. (2019) “Investigating the Effect of Voltage Controlled Oscillator Delay on the Stability of Phase Lock Loops”,MJTD, vol. 8, no. 2, pp. 57-61.
• Talati, S., & Alavi, S. M. (2020). “Radar Systems Deception using Cross-eye Technique”.Majlesi Journal of Mechatronic Systems, 9(3), 19-21.
• Saeed Talati, mohamadreza Hasani Ahangar (2020) “Analysis, Simulation and Optimization of LVQ Neural Network Algorithm and Comparison with SOM”, MJTD, vol. 10, no. 1.
• Talati, S., & Hassani Ahangar. M. R. (2020) “Combining Principal Component Analysis Methods and Self-Organized and Vector Learning Neural Networks for Radar Data”,Majlesi Journal of Telecommunication Devices, 9(2), 65-69.
• Hassani Ahangar, M. R., Talati, S., Rahmati, A., & Heidari, H. (2020). “The Use of Electronic Warfare and Information Signaling in Network-based Warfare”. Majlesi Journal of Telecommunication Devices, 9(2), 93-97.
• Aslinezhad, M., Mahmoudi, O., & Talati, S. (2020). “Blind Detection of Channel Parameters Using Combination of the Gaussian Elimination and Interleaving”.Majlesi Journal of Mechatronic Systems, 9(4), 59-67.
• Talati, S., & Amjadi, A. (2020). “Design and Simulation of a Novel Photonic Crystal Fiber with a Low Dispersion Coefficient in the Terahertz Band”.Majlesi Journal of Mechatronic Systems, 9(2), 23-28.
• Talati, Saeed, Hassani Ahangar, Mohammad Reza. (2021). “Radar Data Processing Using a Combination of Principal Component Analysis Methods and Self-Organized and Digitizing Learning Vector Neural Networks”, Electronic and Cyber Defense, 9 (2), pp. 1-7.
• Talati, S., Alavi, S. M., & Akbarzade, H. (2021). “Investigating the Ambiguity of Ghosts in Radar and Examining the Diagnosis and Ways to Deal with it”. Majlesi Journal of Mechatronic Systems, 10(2).
• Etezadifar, P., & Talati, S. (2021). “Analysis and Investigation of Disturbance in Radar Systems Using New Techniques of Electronic Attack”.Majlesi Journal of Telecommunication Devices, 10(2), 55-59.
• Talati, Behzad. Ebadi, Houman. Akbarzade “Determining of the fault location in distribution systems in presence of distributed generation resources using the original post phasors”. QUID 2017, pp. 1806-1812, Special Issue No.1- ISSN: 1692-343X, Medellín-Colombia. April 2017.
• Talati, Saeed, Akbari Thani, Milad, Hassani Ahangar, Mohammad Reza. (2020). “Detection of Radar Targets Using GMDH Deep Neural Network”, Radar Journal, 8 (1), pp. 65-74.
• Talati, S., Abdollahi, R., Soltaninia, V., & Ayat, M. (2021). “A New Emitter Localization Technique Using Airborne Direction Finder Sensor”.Majlesi Journal of Mechatronic Systems, 10(4), 5-16.
• Sharifi-Tehrani, "Design, Simulation and Fabrication of Microstrip Hairpin and Interdigital BPF for 2.25 GHz Unlicensed Band," Majlesi Journal of Telecommunication Devices, vol. 6, no. 4, 2017.
• Sharifi-Tehrani and S. Talati. (2017) “PPU Adaptive LMS Algorithm, a Hardware-Efficient Approach; a Review on”,Majlesi Journal of Mechatronic Systems, vol. 6, no. 1.
• Sharifi-Tehrani, "Hardware Design of Image Channel Denoiser for FPGA Embedded Systems," Przegląd Elektrotechniczny, vol. 88, no. 3b, pp. 165-167, 2012.
• Sharifi-Tehrani, A. Sadeghi, and S. M. J. Razavi, "Design and Simulation of IFF/ATC Antenna for Unmanned Aerial Vehicle," Majlesi Journal of Mechatronic Systems, vol. 6, no. 1, pp. 1-4, 2017.
• S. Tehrani, M. Ashourian, and P. Moallem, "An FPGA-based implementation of fixed-point standard-LMS algorithm with low resource utilization and fast convergence," International Review on Computers and Software, vol. 5, no. 4, pp. 436-444, 2010.
• Sharifi-Tehrani, "Novel hardware-efficient design of LMS-based adaptive FIR filter utilizing Finite State Machine and Block-RAM," Przeglad Elektrotechniczny, vol. 87, no. 7, pp. 240-244, 2011.
• Sharifi-Tehrani, M. F. Sabahi, and M. R. Danee, "Low-Complexity Framework for GNSS Jamming and Spoofing Detection on Moving Platforms," IET Radar, Sonar & Navigation, vol. 14, no. 12, pp. 2027-2038, 2020.
• Ashourian and O. Sharifi-Tehrani, "Application of semi-circle law and Wigner spiked-model in GPS jamming confronting," Signal, Image and Video Processing, pp. 1-8, 2022.
• Sharifi-Tehrani, M. F. Sabahi, and M. Danaee, "Null broadened–deepened array antenna beamforming for GNSS jamming mitigation in moving platforms," ICT Express, vol. 8, no. 2, pp. 161-165, 2022.
• Sharifi-Tehrani, H. Lashgarian, M. Soleymanzade, and M. H. Ghasemian, "Futurology of Electronic Warfare Systems for IR. IRAN's Fast Crafts," Majlesi Journal of Telecommunication Devices, vol. 8, no. 2, 2019.
• Sharifi-Tehrani, A. Sadeghi, and S. M. J. Razavi, "Design and Simulation of IFF/ATC Antenna for Unmanned Aerial Vehicle," Majlesi Journal of Mechatronic Systems, vol. 6, no. 1, pp. 1-4, 2017.
• Sharifi-Tehrani, M. F. Sabahi, and M. R. Danee, "GNSS Jmming Detection of UAV Ground Control Station Using Random Matrix Theory," ICT Express, vol. In Press, 2020.
• Sharifi-Tehrani, "Novel hardware-efficient design of LMS-based adaptive FIR filter utilizing Finite State Machine and Block-RAM," Przeglad Elektrotechniczny, vol. 87, no. 7, pp. 240-244, 2011.
• Pourghassem, O. Sharifi-Tehrani, and M. Nejati, "A novel weapon detection algorithm in X-ray dual-energy images based on connected component analysis and shape features," Australian Journal of Basic and Applied Sciences, vol. 5, pp. 300-307, 2011.
• S. Tehrani, M. Ashourian, and P. Moallem, "Fpga implementation of a channel noise canceller for image transmission," in Machine Vision and Image Processing (MVIP), 2010 6th Iranian, 2010, pp. 1-6: IEEE.
• Ghazali, S. M., Baleghi, Y. “Pedestrian Detection in Infrared Outdoor Images Based on Atmospheric Situation Estimation”Journal of AI and Data Mining, 2019; 7(1): 1-16. doi: 10.22044/jadm.2018.5742.1696
• Talati, S., Ghazali, S. M., Hassani Ahangar, M., & Alavi, S. M. (2021). “Analysis and Evaluation of Increasing the Throughput of Processors by Eliminating the Lobe’s Disorder”Majlesi Journal of Telecommunication Devices, 10(3), 119-123. https://doi.org/10.52547/mjtd.10.3.119
• Seyed Morteza Ghazali, Jalil Mazloum, Yasser Baleghi. “Modified binary salp swarm algorithm in EEG signal classification for epilepsy seizure detection” Biomedical Signal Processing and Control. Volume 78, September 2022, 103858.
• P., Talati. S., Hassani Ahangar. M.R., Molazade. M., “Investigation of Steganography Methods in Audio Standard Coders: LPC, CELP, MELP” Majlesi Journal of Telecommunication Devices, 12(1), in press, 2023.