Efficient Masked Target Detection by Fast Adaptive Pulse Compression Algorithm with Flexible Filter Length

Document Type : Original Article

Authors

Faculty of Information Technology and Communications, University of Imam Hossein (a.s.), Tehran, Iran

Abstract

In this paper, we investigate the detection of masked weak moving targets in the adjacent fast strong target by using FAPC algorithm. The matched filter of conventional pulse compression radars induces range sidelobes in surrounding a target with high SNR that could mask the smaller targets. The mismatch created in received signal by Doppler phase shift, degrades APC filter performance in side lobe suppression. In this paper, the FFL-FAPC algorithm is proposed to reduce the range side lobes using the RMMSE estimator in its post-processing method. In various scenarios, we will investigate the detection of masked targets in comparsion with previous methods. Simulation results show that the FFL-FAPC algorithm reduce significantly of computational cost, in addition to provides improved Doppler robustness. 

Keywords

References

[1] M. I. Skolnik, Introduction to Radar Systems, (3rd ed.), New York: McGraw-Hill, 2001.
[2] R. Kayvan Shokooh, M. Okhovvat, “Design and implementation of parallel matched filter bank in pulse compression radars, ”Journal of passive defence science and technology, vol.1, no.2, pp.75-85, WINTER 2011.
[3] Z. Li, Z. Yan, S. Wang, L. Li, and M. Mclinden,“Fast adaptive pulse compression based on matched filter outputs,” IEEE Transactions on Aerospace and Electronic Systems, vol.1, no.51, pp. 548-564, 2015.
[4] M. H. Ackroyd and F. Ghani, “Optimum mismatched filter for sidelobe suppression,” IEEE Transactions on Aerospace and Electronic Systems, AES-9, pp. 214-218, 1973.
[5] R. Sato and M. Shinrhu, “Simple mismatched filter for binary pulse compression code with small PSL and small S/N loss,”  IEEE Transactions on Aerospace and Electronic Systems, vol. 39, no. 2, pp. 711 -718, 2003.
 [6] مجتبی حاجی آبادی، عباس ابراهیمی مقدم، حسین خوشبین، «حذف نویز صوتی مبتنی بر یک الگوریتم وفقی نوین»، مجله مهندسی برق دانشگاه تبریز، صفحه 129-121، جلد 46، شماره 3، 1395
[7] S. Wang, Z. Li, Y. Zhang, B. Cheong and L. Li, “Implementation of Adaptive Pulse Compression in Solid-State Radars: Practical Considerations,” IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, vol. 12, no. 10, pp. 2170-2174, 2015.
[8] T. Felhauer, “Digital signal processing for optimum wideband channel estimation in the presence of noise,” ME Proceedings, vol. 140, no. 3, pp. 179 -186, 1993.
[9] S. M. Song, W. M. Kim, D. Park, and Y. Kim, “Estimation theoretic approach for radar pulse compression processing and its optimal codes,” Electronic Letters, vol.36, no.3, 2000.
[10] B. Zrnic, A. Zejak, A. Petrovic, and I. Simic, “Range sidelobe suppression for pulse compression radars utilizing modified RLS algorithm,” IEEE International Symposium Spread Spectrum Techniques and Applications, vol. 3, pp. 1008-1011, 1998.
[11] T. K. Sarkar and R. D. Brown, “An ultra-low sidelobe pulse compression technique for high performance radar systems,”IEEE National Radar Conference, pp. 111-114, 1997.
[12] S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Upper Saddle River, NJ: Prentice-Hall, 1993.
[13] S. D. Blunt and K. Gerlach, “Adaptive pulse compression via MMSE estimation,” IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 2, pp. 572-584, 2006.
[14] T. D. Cuprak and K. E. Wage, “Efficient Doppler-Compensated Reiterative Minimum Mean-Squared-Error Processing,” IEEE Transactions on Aerospace and Electronic Systems, vol. 53, no. 2, pp. 562-574, 2017.
[15] S. D. Blunt, T. Higgins and K. Gerlach, “Dimensionality reduction techniques for efficient adaptive pulse compression,” IEEE Transactions on Aerospace and Electronic Systems, vol. 46, no. 1, pp. 349-362, 2010.
[16] L. Kong, M. Yang and B. Zhao, “Fast implementation of adaptive multi-pulse compression via dimensionality reduction technique,” IEEE Radar Conference, 2012.
[17] B. Zhao, L. J. Kong, M. Yang and G. L. Cui, “Range-Doppler sidelobe and clutter suppression via time range adaptive processing,” IEEE CIE International Conference on Radar, October 2011.
[18] Y. Yang, L. Li, G. Cui, W Yi, L Kong and X Yang, “A modified adaptive multi-pulse compression algorithm for fast implementation,” IEEE Radar Conference (RadarCon), May 2015.
[19] M. Patrick McCormick, S. D. Blunt and T. Higgins, “A gradient descent implementation of adaptive pulse compression,” IEEE Radar Conference, May 2016.
[20] محمود آتشبار، محمدحسین کهائی، «جهت­یابی چند گوینده با استفاده از نمونه­برداری فشرده مبتنی بر فاز»، مجله مهندسی برق دانشگاه تبریز، صفحه 11-1، جلد 40، شماره 2، 1389
[21] S. Treitel and E. A. Robinson,“ The design of high-resolution digital filters,” IEEE Transactions on Geoscience Electronics, vol. GE-4, no.1, pp. 25-38, 1966.
[22] J. M. Baden and M. N. Cohen, “Optimal peak sidelobe filters for biphase pulse compression,” IEEE International Radar Conference, 1990.
[23] J. M. Baden and M. N. Cohen, “Optimal sidelobe suppression for biphase codes,” National Telesystems Conference, 1991.
[24] H. J. Blinchikof, “Range sidelobe reduction for the quadriphase codes,” IEEE Transactions on Aerospace and Electronic Systems, vol.32, no.2, pp.668 – 675, 1996.
[25] H. L. Van Trees, Optimum Array Processing, New York: Wiley, 2002.

Files

Share

How to cite

Statistics