Akış Verilerinde PRI Türü Tanıma için Pencere Tabanlı Bir Yaklaşım
Year 2025,
Volume: 17 Issue: 2, 272 - 281, 15.07.2025
Şefika Çağlan
,
Ali Değirmenci
,
İlyas Çankaya
Abstract
Darbe Tekrarlama Aralığı (DTA) tipinin tespiti radar tanımlamasında temel bir adımdır. Bu nedenle, PRI tipi tanımlama için birçok yöntem önerilmiştir. Sunulan çalışmada, yeni bir çevrimiçi kayan pencere tabanlı PRI tipi tespit yöntemi önerilmiştir. Metot başlangıçta operatörden pencere boyutu ve pencere kaydırma miktarı hiperparametrelerini alır. Sonrasında, gelen veri örneklerinin sayısı pencere boyutunun 1,5 katına ulaşana kadar verilerin toplanmasını bekler. Pencere, gelen Darbe Tanımlayıcı Kelime verilerinin Varış Zamanı Farkı üzerinden kaydırılır ve pencere içindeki değişim özelliklerine göre PRI tipi belirlenir. Deneyler, PRI türlerinin olası senaryolarını içeren 13 farklı veri kümesi üzerinde gerçekleştirilmiştir. Yapılan deneylerin sonuçlarına göre önerilen yöntem sabit, bekle&değiştir, yukarı kayan ve aşağı kayan PRI türlerini ayırt edebildiğini göstermektedir.
References
- Ahmadi, M., & Mohamedpour, K. (2012). PRI modulation type recognition using level clustering and autocorrelation. American Journal of Signal Processing, 2(5), 83-91.
- Ahmed, U. I., ur Rehman, T., Baqar, S., Hussain, I., & Adnan, M. (2018, May). Robust pulse repetition interval (PRI) classification scheme under complex multi emitter scenario. In 2018 22nd International Microwave and Radar Conference (MIKON) (pp. 597-600). IEEE.
- Ata'a, A. W., & Abdullah, S. N. (2007). Deinterleaving of radar signals and PRF identification algorithms. IET radar, sonar & navigation, 1(5), 340-347.
- Bagheri, M., & Sedaaghi, M. H. (2017). A new approach to pulse deinterleaving based on adaptive thresholding. Turkish Journal of Electrical Engineering and Computer Sciences, 25(5), 3827-3838.
- Chao, W., Weisong, L., Xueqiong, L., Xiang, W., & Zhitao, H. (2022). A new radar signal multiparameter-based deinterleaving method. arXiv preprint arXiv:2208.09786.
- Cheng, W., Zhang, Q., Dong, J., Wang, C., Liu, X., & Fang, G. (2021). An enhanced algorithm for deinterleaving mixed radar signals. IEEE Transactions on Aerospace and Electronic Systems, 57(6), 3927-3940.
- Cheng, W., Zhang, Q., Dong, J., Wang, H., & Liu, X. (2023). An Efficient Algorithm for De-Interleaving Staggered PRI Signals. Applied Sciences, 13(13), 7977.
- Fang, Y., Bi, D., Pan, J., & Chen, Q. (2019, December). Multi-function radar behavior state detection algorithm based on Bayesian criterion. In 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) (Vol. 1, pp. 213-217). IEEE.
- Feng, H.C., Tang, B., Wan, T. (2022) Radar pulse repetition interval modulation recognition with combined net and domain-adaptive few-shot learning. Digital Signal Processing, 127(C), 1-11.
- Ge, Z., Sun, X., Ren, W., Chen, W., & Xu, G. (2019) Improved algorithm of radar pulse repetition interval deinterleaving based on pulse correlation. IEEE Access, 7, 30126-30134.
- Gencol, K., At N., & Kara, A. (2016) A wavelet-based feature set for recognizing pulse repetition interval modulation patterns. Turkish Journal of Electrical Engineering and Computer Sciences, 24(4), 3078-3090.
- Ghani, K. A., Sha'ameri, A. Z., Dimyati, K., & Daud, N. G. N. (2017, May). Pulse repetition interval analysis using decimated Walsh-Hadamard transform. In 2017 IEEE Radar Conference (RadarConf) (pp. 0058-0063). IEEE.
- Han, J. W., & Park, C. H. (2021). A unified method for deinterleaving and PRI modulation recognition of radar pulses based on deep neural networks. IEEE Access, 9, 89360-89375.
- Hu, G., & Liu, Y. (2010, April). An efficient method of pulse repetition interval modulation recognition. In 2010 International Conference on Communications and Mobile Computing (Vol. 2, pp. 287-291). IEEE.
- Kauppi, J. P., & Martikainen, K. S. (2007, October). An efficient set of features for pulse repetition interval modulation recognition. In 2007 IET International Conference on Radar Systems (pp. 1-5). IET.
- Keshavarzi, M., Pezeshk, A. M., & Farzaneh, F. (2012, October). A new method for detection of complex pulse repetition interval modulations. In 2012 IEEE 11th International Conference on Signal Processing (Vol. 3, pp. 1705-1709). IEEE.
- Kumar, N. U., Dhananjayulu, V., & Kumar, V. A. (2014). Deinterleaving of radar signals and its parameter estimation in EW environment. International Journal of Emerging Technology and Advanced Engineering, 4(9), 490-494.
- Li, X., Liu, Z., & Huang, Z. (2020). Deinterleaving of pulse streams with denoising autoencoders. IEEE transactions on aerospace and electronic systems, 56(6), 4767-4778.
- Liu, Z.M. (2021) Pulse deinterleaving for multifunction radars with hierarchical deep neural networks. IEEE transactions on aerospace and electronic systems, 57(6), 3585–3599.
- Liu, Z. M., & Philip, S. Y. (2018). Classification, denoising, and deinterleaving of pulse streams with recurrent neural networks. IEEE Transactions on Aerospace and Electronic Systems, 55(4), 1624-1639.
- Liu, Y., & Zhang, Q. (2017, October). An improved algorithm for PRI modulation recognition. In 2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) (pp. 1-5). IEEE.
- Qiao, G., Dai, D., Zhang, C., Ji, P., & Pang, B. (2022). Recognition and parameter estimation of spaceborne synthetic aperture radar pulse repetition interval modulation based on short time modified pulse repetition interval transform. IET Radar, Sonar & Navigation, 16(10), 1696-1716.
- Ryoo, Y. J., Song, K. H., & Kim, W. W. (2007). Recognition of PRI modulation types of radar signals using the autocorrelation. IEICE transactions on communications, 90(5), 1290-1294.
- Shi, Z., Wu, H., Shen, W., Cheng, S., & Chen, Y. (2016, October). Feature extraction for complicated radar PRI modulation modes based on auto-correlation function. In 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) (pp. 1617-1620). IEEE.
- Sridharan, S., Prasad, N. N. S. S. R. K., George, R., & Brindha, M. (2015). Improved pulse repetition interval (PRI) deinterleaving for electronic support measure (ESM) receiver. Int. Journal of Advanced Computing and Electronics Technology (IJACET), 2(3), 37-43.
- Tang, Z., & Li, X. (2023) Change point detection of multi-functional radar work mode based on window-sliding algorithm. 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT), 570-574.
- Xie, M., Zhao, C., Zhao, Y., Hu, D., & Wang, Z. (2023). A novel method for deinterleaving radar signals: First‐order difference curve based on sorted TOA difference sequence. IET Signal Processing, 17(1), e12162.
- Zhang, C., Liu, Y., Si, W. (2023) PRI modulation recognition and sequence search under small sample prerequisite. Journal of Systems Engineering and Electronics, 34(3), 706-713.
- Zhu, M., Li, Y., & Wang, S. (2021). Model-based time series clustering and interpulse modulation parameter estimation of multifunction radar pulse sequences. IEEE Transactions on Aerospace and Electronic Systems, 57(6), 3673-3690.
A Window-Based Approach for PRI Type Recognition in Streaming Data
Year 2025,
Volume: 17 Issue: 2, 272 - 281, 15.07.2025
Şefika Çağlan
,
Ali Değirmenci
,
İlyas Çankaya
Abstract
Pulse Repetition Interval (PRI) type detection is a fundamental step in radar identification. Therefore, many methods have been proposed for PRI type identification. In this study, a new online sliding window-based PRI type detection method is proposed. Initially, the method takes the hyperparameters of window size and window shifting amount from the operator. The method then waits for data to be collected until the number of incoming data samples reaches 1.5 times the window size. The window is shifted over the Difference of Time of Arrival parameter of the incoming Pulse Descriptor Word data and the PRI type is determined according to the change characteristics within the window. The experiments are performed on 13 different datasets containing possible scenarios of PRI types. The results of the experiments show that proposed method can distinguish between constant, dwell&switch, sliding-up, and sliding-down PRI types.
References
- Ahmadi, M., & Mohamedpour, K. (2012). PRI modulation type recognition using level clustering and autocorrelation. American Journal of Signal Processing, 2(5), 83-91.
- Ahmed, U. I., ur Rehman, T., Baqar, S., Hussain, I., & Adnan, M. (2018, May). Robust pulse repetition interval (PRI) classification scheme under complex multi emitter scenario. In 2018 22nd International Microwave and Radar Conference (MIKON) (pp. 597-600). IEEE.
- Ata'a, A. W., & Abdullah, S. N. (2007). Deinterleaving of radar signals and PRF identification algorithms. IET radar, sonar & navigation, 1(5), 340-347.
- Bagheri, M., & Sedaaghi, M. H. (2017). A new approach to pulse deinterleaving based on adaptive thresholding. Turkish Journal of Electrical Engineering and Computer Sciences, 25(5), 3827-3838.
- Chao, W., Weisong, L., Xueqiong, L., Xiang, W., & Zhitao, H. (2022). A new radar signal multiparameter-based deinterleaving method. arXiv preprint arXiv:2208.09786.
- Cheng, W., Zhang, Q., Dong, J., Wang, C., Liu, X., & Fang, G. (2021). An enhanced algorithm for deinterleaving mixed radar signals. IEEE Transactions on Aerospace and Electronic Systems, 57(6), 3927-3940.
- Cheng, W., Zhang, Q., Dong, J., Wang, H., & Liu, X. (2023). An Efficient Algorithm for De-Interleaving Staggered PRI Signals. Applied Sciences, 13(13), 7977.
- Fang, Y., Bi, D., Pan, J., & Chen, Q. (2019, December). Multi-function radar behavior state detection algorithm based on Bayesian criterion. In 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) (Vol. 1, pp. 213-217). IEEE.
- Feng, H.C., Tang, B., Wan, T. (2022) Radar pulse repetition interval modulation recognition with combined net and domain-adaptive few-shot learning. Digital Signal Processing, 127(C), 1-11.
- Ge, Z., Sun, X., Ren, W., Chen, W., & Xu, G. (2019) Improved algorithm of radar pulse repetition interval deinterleaving based on pulse correlation. IEEE Access, 7, 30126-30134.
- Gencol, K., At N., & Kara, A. (2016) A wavelet-based feature set for recognizing pulse repetition interval modulation patterns. Turkish Journal of Electrical Engineering and Computer Sciences, 24(4), 3078-3090.
- Ghani, K. A., Sha'ameri, A. Z., Dimyati, K., & Daud, N. G. N. (2017, May). Pulse repetition interval analysis using decimated Walsh-Hadamard transform. In 2017 IEEE Radar Conference (RadarConf) (pp. 0058-0063). IEEE.
- Han, J. W., & Park, C. H. (2021). A unified method for deinterleaving and PRI modulation recognition of radar pulses based on deep neural networks. IEEE Access, 9, 89360-89375.
- Hu, G., & Liu, Y. (2010, April). An efficient method of pulse repetition interval modulation recognition. In 2010 International Conference on Communications and Mobile Computing (Vol. 2, pp. 287-291). IEEE.
- Kauppi, J. P., & Martikainen, K. S. (2007, October). An efficient set of features for pulse repetition interval modulation recognition. In 2007 IET International Conference on Radar Systems (pp. 1-5). IET.
- Keshavarzi, M., Pezeshk, A. M., & Farzaneh, F. (2012, October). A new method for detection of complex pulse repetition interval modulations. In 2012 IEEE 11th International Conference on Signal Processing (Vol. 3, pp. 1705-1709). IEEE.
- Kumar, N. U., Dhananjayulu, V., & Kumar, V. A. (2014). Deinterleaving of radar signals and its parameter estimation in EW environment. International Journal of Emerging Technology and Advanced Engineering, 4(9), 490-494.
- Li, X., Liu, Z., & Huang, Z. (2020). Deinterleaving of pulse streams with denoising autoencoders. IEEE transactions on aerospace and electronic systems, 56(6), 4767-4778.
- Liu, Z.M. (2021) Pulse deinterleaving for multifunction radars with hierarchical deep neural networks. IEEE transactions on aerospace and electronic systems, 57(6), 3585–3599.
- Liu, Z. M., & Philip, S. Y. (2018). Classification, denoising, and deinterleaving of pulse streams with recurrent neural networks. IEEE Transactions on Aerospace and Electronic Systems, 55(4), 1624-1639.
- Liu, Y., & Zhang, Q. (2017, October). An improved algorithm for PRI modulation recognition. In 2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) (pp. 1-5). IEEE.
- Qiao, G., Dai, D., Zhang, C., Ji, P., & Pang, B. (2022). Recognition and parameter estimation of spaceborne synthetic aperture radar pulse repetition interval modulation based on short time modified pulse repetition interval transform. IET Radar, Sonar & Navigation, 16(10), 1696-1716.
- Ryoo, Y. J., Song, K. H., & Kim, W. W. (2007). Recognition of PRI modulation types of radar signals using the autocorrelation. IEICE transactions on communications, 90(5), 1290-1294.
- Shi, Z., Wu, H., Shen, W., Cheng, S., & Chen, Y. (2016, October). Feature extraction for complicated radar PRI modulation modes based on auto-correlation function. In 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) (pp. 1617-1620). IEEE.
- Sridharan, S., Prasad, N. N. S. S. R. K., George, R., & Brindha, M. (2015). Improved pulse repetition interval (PRI) deinterleaving for electronic support measure (ESM) receiver. Int. Journal of Advanced Computing and Electronics Technology (IJACET), 2(3), 37-43.
- Tang, Z., & Li, X. (2023) Change point detection of multi-functional radar work mode based on window-sliding algorithm. 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT), 570-574.
- Xie, M., Zhao, C., Zhao, Y., Hu, D., & Wang, Z. (2023). A novel method for deinterleaving radar signals: First‐order difference curve based on sorted TOA difference sequence. IET Signal Processing, 17(1), e12162.
- Zhang, C., Liu, Y., Si, W. (2023) PRI modulation recognition and sequence search under small sample prerequisite. Journal of Systems Engineering and Electronics, 34(3), 706-713.
- Zhu, M., Li, Y., & Wang, S. (2021). Model-based time series clustering and interpulse modulation parameter estimation of multifunction radar pulse sequences. IEEE Transactions on Aerospace and Electronic Systems, 57(6), 3673-3690.