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Kayvan shokooh R, Okhovvat M, Raees Danaee M. Extending the Radar Dynamic Range using Adaptive Pulse Compression. JSDP 2021; 18 (3) :91-108
URL: http://jsdp.rcisp.ac.ir/article-1-992-en.html
Faculty of Electrical Engineering, University of Imam Hossein
Abstract:   (1331 Views)
The matched filter in the radar receiver is only adapted to the transmitted signal version and its output will be wasted due to non-matching with the received signal from the environment. The sidelobes amplitude of the matched filter output in pulse compression radars are depended on the transmitted coded waveforms that extended as much as the length of the code on both sides of the target location. In order to detect a weak target in vicinity of strong target, the sidelobes of the matched filter output resulting from the strong target masked the weak target and didn’t detect its. Generally, the radar dynamic range is defined by the maximum power ratio to the minimum detectable power that is depended on the level of the threshold and the sidelobe levels. Adaptive algorithms suppress the sidelobe levels to noise level with condition of maintain the range resolution and therefore increase the dynamic range. In this paper, an improved algorithm (in terms of computational cost and Doppler robustness) is proposed based on the minimum mean square error (MMSE) estimator denoted as Flexible Filter Length-Adaptive Pulse Compression Repair (FFL-APCR), which filter length depends on the length of transmitted code. It is also shown that the length of the code is influenced by determining the asymptotic peak sidelobe level and the dynamics range. In addition, the influence of the high-speed target on main lobe broadening and the performance degradation of adaptive filters is investigated. Finally, extending of radar dynamic range with the proposed FFL-APCR algorithm is shown in various conditions and its performance evaluated by mean square error criteria.
Where return signals coincide with the transmission of a pulse, pulse eclipsing can occur which results in detection performance loss. The mismatches (Doppler phase shift and pulse eclipsing) degrades performance of sidelobes suppression algorithms. The FFL-APCR algorithm suppresses range sidelobes by using a smaller filter length and reduces the computational cost. Consequently, this algorithm should be computationally efficient (real-time) to enable the practical application of RMMSE.
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Type of Study: Research | Subject: Paper
Received: 2019/04/7 | Accepted: 2021/05/22 | Published: 2022/01/20 | ePublished: 2022/01/20

References
1. [1] M. I. Skolnik, Introduction to Radar Systems, (3rd ed.), New York: McGraw-Hill, 2001, pp. 339-369.
2. [2] R. Kayvan Shokooh and 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. [3] 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, Apr. 2006. [DOI:10.1109/TAES.2006.1642573]
4. [4] S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory., Upper Saddle River, NJ: Prentice-Hall, 1993, pp. 219-286 and 344-350.
5. [5] N. Levanon, "Creating Sidelobe-Free Range Zone Around Detected Radar Target," in IEEE 28-th Convention of Electrical and Electronics Engineers in Israel, 2014. [DOI:10.1109/EEEI.2014.7005837]
6. [6] Kayvan shokooh, R., Okhovvat, M., "Efficient Masked Target Detection by Fast Adaptive Pulse Compression Algorithm with Flexible Filter Length," Tabriz Journal of Electrical Engineering (in persian), vol. 49, no. 2, pp. 819-831, 2019.
7. [7] R. Kayvan shokooh and M. Okhovvat, "An Integrated Algorithm for Optimal Detection of Radar Weak Targets Masked by the Sidelobes of a Strong Target," ECDJ Journal (In Persian), vol. 6, no. 4, 2018.
8. [8] Kayvan shokooh, R., Okhovvat, M., "Modified-adaptive pulse compression repair algorithm based on post-processing for eclipsing effects," IET Radar, Sonar & Navigation, vol. 12, no. 12, pp. 1527-1534, 2018. [DOI:10.1049/iet-rsn.2018.5254]
9. [9] T. K. Moon and W. C. Stirling, Mathematical Methods and Algorithms for Signal Processing, Upper Saddle River, NJ: Prentice-Hall, 1999.
10. [10] S.D. Blunt, K. Gerlach, and E. Mokole, "Pulse compression eclipsing repair," in IEEE Radar Conf, Rome, Italy, 26-30 May 2008. [DOI:10.1109/RADAR.2008.4720725]
11. [11] Wai Ho Mow and S. R. Li, "Aperiodic autocorrelation and crosscorrelation of polyphase sequences," IEEE Transactions on Information Theory, vol. 43, no. 3, pp. 1000-1007, 1997. [DOI:10.1109/18.568711]
12. [12] M. Antweiler and L. Bomer, "Merit Factor of Chu and Frank sequences," Electron. Letter, vol. 26, pp. 2068-2070, 1990. [DOI:10.1049/el:19901334]
13. [13] W. H. Mow, A STUDY OF CORRELATION OF SEQUENCES, THE CHINESE UNIVERSITY OF HONG HONG, 1993.
14. [14] M. A. Richards, J. A. Scheer and W. A. Holm, Principles of Modern Radar: Basic principles, vol. 1, Sci Tech, 2010. [DOI:10.1049/SBRA021E]
15. [15] Z. Li, Z. Yan, S. Wang, L. Li, and M. Mclinden, "Fast adaptive pulse compression based on matched filter outputs," IEEE Trans. on Aerospace and Electronic Systems, vol. 51, no. 1, pp. 548-564, 2015. [DOI:10.1109/TAES.2014.130544]

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