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Frontiers of Information Technology & Electronic Engineering

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Efficient coherent detection of maneuvering targets based on location rotation transform and non-uniform fast Fourier transform

Author(s): Ke Jin, Tao Lai, Yan-li Qi, Jie Huang, Yong-jun Zhao
Affiliation(s): National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450001, China; more
Corresponding email(s): jinke_xd@outlook.com
Key Words: Coherent integration, Maneuvering target, Parameter estimation, Location rotation transform (LRT), Non-uniform fast Fourier transform (NuFFT)

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Ke Jin, Tao Lai, Yan-li Qi, Jie Huang, Yong-jun Zhao. Efficient coherent detection of maneuvering targets based on location rotation transform and non-uniform fast Fourier transform[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.1900272

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author="Ke Jin, Tao Lai, Yan-li Qi, Jie Huang, Yong-jun Zhao",
journal="Frontiers of Information Technology & Electronic Engineering",
year="in press",
publisher="Zhejiang University Press & Springer",
doi="https://doi.org/10.1631/FITEE.1900272"
}

%0 Journal Article
%T Efficient coherent detection of maneuvering targets based on location rotation transform and non-uniform fast Fourier transform
%A Ke Jin
%A Tao Lai
%A Yan-li Qi
%A Jie Huang
%A Yong-jun Zhao
%J Frontiers of Information Technology & Electronic Engineering
%P 1251-1266
%@ 2095-9184
%D in press
%I Zhejiang University Press & Springer
doi="https://doi.org/10.1631/FITEE.1900272"

TY - JOUR
T1 - Efficient coherent detection of maneuvering targets based on location rotation transform and non-uniform fast Fourier transform
A1 - Ke Jin
A1 - Tao Lai
A1 - Yan-li Qi
A1 - Jie Huang
A1 - Yong-jun Zhao
J0 - Frontiers of Information Technology & Electronic Engineering
SP - 1251
EP - 1266
%@ 2095-9184
Y1 - in press
PB - Zhejiang University Press & Springer
ER -
doi="https://doi.org/10.1631/FITEE.1900272"

Abstract
Chinese Summary
Academic Network
Reviewer Comment

Abstract: Long-term coherent integration can remarkably improve the ability of detection and motion parameter estimation of radar for maneuvering targets. However, the linear range migration, quadratic range migration (QRM), and Doppler frequency migration within the coherent processing interval seriously degrade the detection and estimation performance. Therefore, an efficient and noise-resistant coherent integration method based on location rotation transform (LRT) and non-uniform fast Fourier transform (NuFFT) is proposed. QRM is corrected by the second-order keystone transform. Using the relationship between the rotation angle and Doppler frequency, a novel phase compensation function is constructed. Motion parameters can be rapidly estimated by LRT and NuFFT. Compared with several representative algorithms, the proposed method achieves a nearly ideal detection performance with low computational cost. Finally, experiments based on measured radar data are conducted to verify the proposed algorithm.

基于位置旋转变换和非均匀快速傅立叶变换的机动目标高效相参检测

靳科¹，赖涛²，齐艳丽³，黄洁¹，赵拥军¹
¹国家数字交换系统工程技术研究中心，中国郑州市，450001
²中山大学电子与通信工程学院，中国广州市，510000
³安徽省质量和标准化研究院，中国合肥市，230000

摘要：长时间相参积累能够显著提升雷达对机动目标的检测和运动参数估计性能。然而，相参积累期间目标的线性距离徙动、二次距离徙动和多普勒频率徙动将导致检测性能急剧下降。提出基于位置旋转变换和非均匀快速傅里叶变换的高效稳健相参积累方法。首先，利用二阶Keystone变换消除二次距离徙动。然后，利用旋转角度和多普勒频率之间的对应关系，构建相位补偿函数，从而利用位置旋转和非均匀快速傅里叶变换实现高效的参数估计。与现有代表性算法相比，所提算法能以较低运算复杂度实现近乎理想的检测性能。最后，基于雷达实测数据的实验证明所提算法有效。

关键词组：相参积累；机动目标；参数估计；位置旋转变换；非均匀快速傅立叶变换

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Reference

[1]Chen XL, Guan J, Liu NB, et al., 2014. Maneuvering target detection via Radon-fractional Fourier transform-based long-time coherent integration. IEEE Trans Signal Process, 62(4):939-953.

[2]Guida M, Longo M, Lops M, 1993. Biparametric CFAR procedures for lognormal clutter. IEEE Trans Aerosp Electron Syst, 29(3):798-809.

[3]Huang PH, Liao GS, Yang ZZ, et al., 2016. Long-time coherent integration for weak maneuvering target detection and high-order motion parameter estimation based on keystone transform. IEEE Trans Signal Process, 64(15):4013-4026.

[4]Huang X, Zhang LR, Li SY, et al., 2018. Radar high speed small target detection based on keystone transform and linear canonical transform. Dig Signal Process, 82:203- 215.

[5]Huang X, Tang SY, Zhang LR, et al., 2019. Ground-based radar detection for high-speed maneuvering target via fast discrete chirp-Fourier transform. IEEE Access, 7:12097- 12113.

[6]Jin K, Lai T, Li GQ, et al., 2017. Ultra-wideband FMCW ISAR imaging with a large rotation angle based on block-sparse recovery. Front Inform Technol Electron Eng, 18(12):2058-2069.

[7]Jin K, Lai T, Wang YB, et al., 2019a. Coherent integration for radar high-speed maneuvering target based on frequency- domain second-order phase difference. Electronics, 8(3):287.

[8]Jin K, Lai T, Wang YB, et al., 2019b. Parameter estimation of quadratic frequency modulated signal based on three-dimensional scaled Fourier transform. IET Radar Sonar Navig, 13(10):1689-1696.

[9]Kirkland D, 2011. Imaging moving targets using the second- order keystone transform. IET Radar Sonar Navig, 5(8):902-910.

[10]Li XL, Cui GL, Yi W, et al., 2014. A fast maneuvering target motion parameters estimation algorithm based on ACCF. IEEE Signal Process Lett, 22(3):270-274.

[11]Li XL, Cui GL, Yi W, et al., 2015. Coherent integration for maneuvering target detection based on Radon-Lv’s distribution. IEEE Signal Process Lett, 22(9):1467-1471.

[12]Li XL, Cui GL, Yi W, et al., 2016a. Manoeuvring target detection based on keystone transform and Lv’s distribution. IET Radar Sonar Navig, 10(7):1234-1242.

[13]Li XL, Kong LJ, Cui GL, et al., 2016b. CLEAN-based coherent integration method for high-speed multi-targets detection. IET Radar Sonar Navig, 10(9):1671-1682.

[14]Li XL, Cui GL, Yi W, et al., 2016c. Fast coherent integration for maneuvering target with high-order range migration via TRT-SKT-LVD. IEEE Trans Aerosp Electron Syst, 52(6):2803-2814.

[15]Li XL, Cui GL, Kong LJ, et al., 2016d. Fast non-searching method for maneuvering target detection and motion parameters estimation. IEEE Trans Signal Process, 64(9): 2232-2244.

[16]Li XL, Kong LJ, Cui GL, et al., 2016e. A low complexity coherent integration method for maneuvering target detection. Dig Signal Process, 52:137-147.

[17]Li XL, Sun Z, Yi W, et al., 2018. Computationally efficient coherent detection and parameter estimation algorithm for maneuvering target. Signal Process, 155:130-142.

[18]Li XL, Sun Z, Yi W, et al., 2019a. Radar detection and parameter estimation of high-speed target based on MART- LVT. IEEE Sens J, 19(4):1478-1486.

[19]Li XL, Sun Z, Yeo TS, et al., 2019b. STGRFT for detection of maneuvering weak target with multiple motion models. IEEE Trans Signal Process, 67(7):1902-1917.

[20]Luo S, Bi GA, Lv XL, et al., 2013. Performance analysis on Lv distribution and its applications. Dig Signal Process, 23(3):797-807.

[21]Lv XL, Bi GA, Wan CR, et al., 2011. Lv’s distribution: principle, implementation, properties, and performance. IEEE Trans Signal Process, 59(8):3576-3591.

[22]Niu ZY, Zheng JB, Su T, et al., 2017. Fast implementation of scaled inverse Fourier transform for high-speed radar target detection. Electron Lett, 53(16):1142-1144.

[23]Perry RP, Dipietro F, Fante RL, 1999. SAR imaging of moving targets. IEEE Trans Aerosp Electron Syst, 35(1):188-200.

[24]Pignol F, Colone F, Martelli T, 2018. Lagrange-polynomial- interpolation-based keystone transform for a passive radar. IEEE Trans Aerosp Electron Syst, 54(3):1151-1167.

[25]Qu ZY, Qu FX, Hou CB, et al., 2018. Quadratic frequency modulation signals parameter estimation based on two- dimensional product modified parameterized chirp rate- quadratic chirp rate distribution. Sensors, 18(5):1624.

[26]Rao X, Tao HH, Su J, et al., 2014. Axis rotation MTD algorithm for weak target detection. Dig Signal Process, 26:81-86.

[27]Rao X, Tao HH, Su J, et al., 2015. Detection of constant radial acceleration weak target via IAR-FRFT. IEEE Trans Aerosp Electron Syst, 51(4):3242-3253.

[28]Su J, Xing M, Wang G, et al., 2010. High-speed multi-target detection with narrowband radar. IET Radar Sonar Navig, 4(4):595-603.

[29]Sun Z, Li XL, Yi W, et al., 2018. A coherent detection and velocity estimation algorithm for the high-speed target based on the modified location rotation transform. IEEE J Sel Top Appl Earth Observ Remote Sens, 11(7):2346-2361.

[30]Tian J, Cui W, Shen Q, et al., 2013. High-speed maneuvering target detection approach based on joint RFT and keystone transform. Sci China Inform Sci, 56(6):1-13.

[31]Tian J, Cui W, Wu S, 2014. A novel method for parameter estimation of space moving targets. IEEE Geosci Remote Sens Lett, 11(2):389-393.

[32]Wu W, Wang GH, Sun JP, 2018. Polynomial Radon- polynomial Fourier transform for near space hypersonic maneuvering target detection. IEEE Trans Aerosp Electron Syst, 54(3):1306-1322.

[33]Xing MD, Su JH, Wang GY, et al., 2011. New parameter estimation and detection algorithm for high speed small target. IEEE Trans Aerosp Electron Syst, 47(1):214-224.

[34]Xu J, Yu J, Peng YN, et al., 2011a. Radon-Fourier transform for radar target detection, I: generalized Doppler filter bank. IEEE Trans Aerosp Electron Syst, 47(2):1186-1202.

[35]Xu J, Yu J, Peng YN, et al., 2011b. Radon-Fourier transform for radar target detection (II): blind speed sidelobe suppression. IEEE Trans Aerosp Electron Syst, 47(4):2473-2489.

[36]Xu J, Xia XG, Peng SB, et al., 2012. Radar maneuvering target motion estimation based on generalized Radon-Fourier transform. IEEE Trans Signal Process, 60(12):6190- 6201.

[37]Yu J, Xu J, Peng YN, et al., 2012. Radon-Fourier transform for radar target detection (III): optimality and fast implementations. IEEE Trans Aerosp Electron Syst, 48(2):991- 1004.

[38]Zhang JC, Su T, Zheng JB, et al., 2017. Novel fast coherent detection algorithm for radar maneuvering target with jerk motion. IEEE J Sel Top Appl Earth Observ Remote Sens, 10(5):1792-1803.

[39]Zheng JB, Su T, Zhang L, et al., 2014. ISAR imaging of targets with complex motion based on the chirp rate-quadratic chirp rate distribution. IEEE Trans Geosci Remote Sens, 52(11):7276-7289.

[40]Zheng JB, Su T, Zhu WT, et al., 2015. Radar high-speed target detection based on the scaled inverse Fourier transform. IEEE J Sel Top Appl Earth Observ Remote Sens, 8(3): 1108-1119.

[41]Zheng JB, Liu HW, Liu J, et al., 2018. Radar high-speed maneuvering target detection based on three-dimensional scaled transform. IEEE J Sel Top Appl Earth Observ Remote Sens, 11(8):2821-2833.

[42]Zhu DY, Li Y, Zhu ZD, 2007. A keystone transform without interpolation for SAR ground moving-target imaging. IEEE Geosci Remote Sens Lett, 4(1):18-22.

[43]Zhu SQ, Liao GS, Yang D, et al., 2014. A new method for radar high-speed maneuvering weak target detection and imaging. IEEE Geosci Remote Sens Lett, 11(7):1175-1179.

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基于位置旋转变换和非均匀快速傅立叶变换的机动目标高效相参检测

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