volume | PIER Journals

Abstract

Radon-Fourier transform (RFT) is able to effectively overcome the coupling between the range cell migration (RCM) effect and Doppler modulation by searching along range and velocity dimensions jointly for the moving target, which depends on envelope alignment and Doppler phase compensation. However, without effective clutter suppression, clutter would also be intergraded via RFT. Thus, the adaptive RFT (ARFT) has been proposed to clutter suppression by introducing an optimal filter weight, which is determined from the clutter's covariance matrix as well as the steering vector for the moving target with the consideration of RCM effect. Nevertheless, the ARFT needs to address the difficulty for real implementation, i.e., computational complexity is too high to a large number of pulse samples. It is known that to obtain the inversion the sample covariance matrix (R_cn^-1) is order M³, i.e., O(M³), in which $M$ is the order of the matrix. It is the most complexity consumed step in ARFT. In this paper, we propose a modified adaptive RFT (MARFT) method to obtain R_cn^-1 with recursive computation, which takes the complexity order M², i.e., O(M²). Simulations show that the proposed method has the same clutter suppression results as the conventional ARFT method, where the computational complexity is much lower.

1. Aubry, Augusto, Antonio De Maio, Vincenzo Carotenuto, and Alfonso Farina, "Radar phase noise modeling and effects --- Part I: MTI filters," IEEE Transactions on Aerospace and Electronic Systems, Vol. 52, No. 2, 698-711, 2016. Google Scholar

2. Xu, Jia, Ji Yu, Ying-Ning Peng, and Xiang-Gen Xia, "Radon-Fourier transform for radar target detection, I: Generalized Doppler filter bank," IEEE Transactions on Aerospace and Electronic Systems, Vol. 47, No. 2, 1186-1202, 2011. Google Scholar

3. Lang, Ping, Xiongjun Fu, Jian Dong, and Jian Yang, "An efficient Radon-Fourier transform-based coherent integration method for target detection," IEEE Geoscience and Remote Sensing Letters, Vol. 20, 1-5, 2023. Google Scholar

4. Hussain, Musadiq, Rehan Ahmed, and Hammad M. Cheema, "Segmented Radon-Fourier transform for long time coherent radars," IEEE Sensors Journal, Vol. 23, No. 9, 9582-9594, 2023. Google Scholar

5. Longman, Oren and Igal Bilik, "Spectral Radon-Fourier transform for automotive radar applications," IEEE Transactions on Aerospace and Electronic Systems, Vol. 57, No. 2, 1046-1056, 2021. Google Scholar

6. Xu, Jia, Xiang-Gen Xia, Shi-Bao Peng, Ji Yu, Ying-Ning Peng, and Li-Chang Qian, "Radar maneuvering target motion estimation based on generalized Radon-Fourier transform," IEEE Transactions on Signal Processing, Vol. 60, No. 12, 6190-6201, 2012. Google Scholar

7. Wu, Wei, Guo Hong Wang, and Jin Ping Sun, "Polynomial Radon-polynomial Fourier transform for near space hypersonic maneuvering target detection," IEEE Transactions on Aerospace and Electronic Systems, Vol. 54, No. 3, 1306-1322, 2017. Google Scholar

8. Qian, L.-C., J. Xu, X.-G. Xia, W.-F. Sun, T. Long, and Y.-N. Peng, "Fast implementation of generalised Radon-Fourier transform for manoeuvring radar target detection," Electronics Letters, Vol. 48, No. 22, 1427-1428, 2012. Google Scholar

9. Zhang, Zhenghe, Nan Liu, Yongning Hou, Shiyu Zhang, and Linrang Zhang, "A coherent integration segment searching based GRT-GRFT hybrid integration method for arbitrary fluctuating target," Remote Sensing, Vol. 14, No. 11, 2695, 2022. Google Scholar

10. Xu, J., J. Yu, Y.-N. Peng, X.-G. Xia, and T. Long, "Space-time Radon-Fourier transform and applications in radar target detection," IET Radar, Sonar & Navigation, Vol. 6, No. 9, 846-857, 2012. Google Scholar

11. Qian, Li-Chang, Jia Xu, Xiang-Gen Xia, Wen-Feng Sun, Teng Long, and Ying-Ning Peng, "Wideband‐scaled Radon‐Fourier transform for high‐speed radar target detection," IET Radar, Sonar & Navigation, Vol. 8, No. 5, 501-512, 2014. Google Scholar

12. Xu, Jia, Liang Yan, Xu Zhou, Teng Long, Xiang-Gen Xia, Yong-Liang Wang, and Alfonso Farina, "Adaptive Radon-Fourier transform for weak radar target detection," IEEE Transactions on Aerospace and Electronic Systems, Vol. 54, No. 4, 1641-1663, 2018. Google Scholar

13. Pillai, S. Unnikrishna, Array Signal Processing, Springer-Verlag, 1989.
doi:10.1007/978-1-4612-3632-0

14. Guerci, Joseph R., Space-Time Adaptive Processing for Radar, 2nd Ed., Artech House, 2015.

15. Carlson, Blair D., "Covariance matrix estimation errors and diagonal loading in adaptive arrays," IEEE Transactions on Aerospace and Electronic Systems, Vol. 24, No. 4, 397-401, 1988. Google Scholar

16. Reed, Irving S., John D. Mallett, and Lawrence E. Brennan, "Rapid convergence rate in adaptive arrays," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-10, No. 6, 853-863, 1974. Google Scholar

Dr. Haibo Wang

Dr. Wenhua Huang

Dr. Haichuan Zhang

Dr. Tao Ba

Dr. Zhiqiang Yang