基于相位分析与散射点关联的速度估计方法

doi:10.12305/j.issn.1001-506X.2021.12.03

Abstract

Abstract:

Wideband detection provides a way to estimate targets' motion parameters with a high degree of accuracy. However, some factors limit the promotion of velocity measurement performance, such as target's multiple scattering characteristics, change of target's posture, and so on. To solve this problem, an effective method based on phase analysis and scatterers association is put forward. Firstly, by building a segment model to present constant-acceleration motion in a straight line, and combining range alignment and adaptive Chirplet decomposition, we can get motion information of the target by analyzing change of phase. Secondly, the prediction-observation association method can be used to get rid of the influence of the not-translational factor, and lead to an improvement on estimate accuracy of translational velocity. Finally, experimental results using measured data confirm the practicality of the proposed algorithm.

Key words: velocity estimate, range alignment, Chirplet decomposition, scatterers association

CLC Number:

TN95

Xuebin CHEN, Chunmao YE, Yan ZHANG, Qingrong HU. Velocity estimate method based on phase analysis and scatterers association[J]. Systems Engineering and Electronics, 2021, 43(12): 3429-3438.

Figures/Tables 13

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References 27

1	DAI Z N, ZHANG X G, BAI Y C. A method of high accuracy velocity measurement for LFM radar[C]//Proc. of the International Conference on Wireless Communication & Signal Processing, 2015.
2	ZHENG J B , SU T , ZHU W T , et al. Radar high-speed target detection based on the scaled inverse fourier transform[J]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2015, 8 (3): 1108- 1119.
3	CHEN X L, GUAN J, ZHAO Z J, et al. Radar maneuvering target detection based on scaling processing and Radon-Fourier transform[C]//Proc. of the IET Radar Conference, 2015.
4	ZHENG J B , SU T , LIU H W , et al. Radar high-speed target detection based on the frequency-domain deramp-keystone transform[J]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2016, 9 (1): 285- 294.
5	CHEN V C , LI F , HO S S , et al. Micro-Doppler effect in radar: phenomenon, model, and simulation study[J]. IEEE Trans.on Aerospace & Electronic Systems, 2006, 42 (1): 2- 21.
6	XU G , XING M D , YANG L , et al. Joint approach of translational and rotational phase error corrections for high-resolution inverse synthetic aperture radar imaging using minimum-entropy[J]. IET Radar Sonar & Navigation, 2016, 10 (3): 586- 594.
7	ZHOU W , YE C M , JIN R J , et al. ISAR imaging of targets with rotating parts based on robust principal component analysis[J]. IET Radar Sonar & Navigation, 2017, 11 (4): 563- 569.
8	包云霞, 毛二可, 何佩琨. 基于一维高分辨距离像的相关测速补偿算法[J]. 北京理工大学学报, 2008, 28 (2): 160- 163.
	BAO Y X , MAO E K , HE P K . Motion compensation method based on one-dimension high resolution range profile cross-correlation[J]. Transactions of Beijing Institute of Technology, 2008, 28 (2): 160- 163.
9	PENG S B , XU J , PENG Y N , et al. Parametric inverse synthetic aperture radar manoeuvring target motion compensation based on particle swarm optimiser[J]. IET Radar Sonar & Navigation, 2011, 5 (3): 305- 314.
10	CHEN C C , ANDREWS H C . Target-motion-induced radar imaging[J]. IEEE Trans.on Aerospace & Electronic Systems, 1980, 16 (1): 2- 14.
11	保铮, 邢孟道, 王彤. 雷达成像技术[M]. 北京: 电子工业出版社, 2005.
	BAO Z , XING M D , WANG D . Radar imaging technology[M]. Beijing: Publishing House of Electronic Industry, 2005.
12	CHEN V C . The micro-Doppler effect in radar[M]. America: Artech House, 2011.
13	WANG C, WANG J, ZHANG X D. Automatic radar waveform recognition based on time-frequency analysis and convolutional neural network[C]//Proc. of the IEEE International Conference on Acoustics, 2017: 2437-2441.
14	REN M Q, TIAN Y H. Radar signal cognition based time-frequency transform and high order spectra analysis[C]//Proc. of the IEEE International Conference on Signal Processing, Communications and Computing, 2017.
15	CEXUS J C, TOUMI A. Radar target recognition using time-frequency analysis and polar transformation[C]//Proc. of the 4th International Conference on Advanced Technologies for Signal and Image Processing, 2018.
16	REN K , DU L , WANG B S , et al. Statistical compressive sensing and feature extraction of time-frequency spectrum from narrowband radar[J]. IEEE Trans.on Aerospace & Electronic Systems, 2020, 56 (1): 326- 342.
17	WANG Y , WANG Z F , ZHAO B , et al. Compensation for high-frequency vibration of platform in SAR imaging based on adaptive chirplet decomposition[J]. IEEE Geoscience & Remote Sensing Letters, 2016, 13 (6): 792- 795.
18	CHEN W J, SHENG J, YUAN L, et al. A method separating echo by adaptive chirplet signal decomposition based on FRFT[C]//Proc. of the 11th International Symposium on Antennas, Propagation and EM Theory, 2016: 869-872.
19	YANG B Y , YANG Z B , SUN R B , et al. Fast nonlinear Chirplet dictionary-based sparse decomposition for rotating machi-nery fault diagnosis under nonstationary conditions[J]. IEEE Trans.on Instrumentation and Measurement, 2019, 68 (12): 4736- 4745. doi: 10.1109/TIM.2019.2900886
20	PUKHOVA V M, STEPANOVA M S. Up-Chirplet and down-Chirplet transforms of non-stationary signals[C]//Proc. of the IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, 2019: 1221-1225.
21	肖涛, 汤子跃, 黄强辉. 一种基于滑窗相关的回波包络对齐方法[J]. 空军雷达学院学报, 2006, 20 (4): 276- 278.
	XIAO T , TANG Z Y , HUANG Q H . A method of echo range alignment based on sliding-window correlation[J]. Journal of Air Force Radar Academy, 2006, 20 (4): 276- 278.
22	VEHMAS R, JYLHA J. Improving the estimation accuracy and computational efficiency of ISAR range alignment[C]//Proc. of the 14th European Radar Conference, 2017: 13-16.
23	LIU Y, WANG L, BI G A, et al. Novel ISAR range alignment via minimizing the entropy of the sum range profile[C]//Proc. of the 21st International Radar Symposium, 2020: 135-138.
24	王勇, 姜义成. 基于自适应Chirplet分解的舰船目标ISAR成像[J]. 电子与信息学报, 2006, 28 (6): 982- 984.
	WANG Y , JIANG Y C . The ISAR imaging of ships based on adaptive chirplet decomposition[J]. Journal of Electronics and Information Technology, 2006, 28 (6): 982- 984.
25	LU H, ZHANG S S, KONG L K. A new WVD algorithm jointed CLEAN technique in ISAR imaging[C]//Proc. of the 2nd International Conference on Intelligent Systems Design and Engineering Application, 2012: 69-72.
26	LI J , STOICA P . Efficient mixed-spectrum estimation with applications to target feature extraction[J]. IEEE Trans.on Signal Processing, 1996, 44 (2): 281- 295. doi: 10.1109/78.485924
27	YAO Y, WU L N. A new method of velocity measurement based on CRT algorithm in dual-frequency pulse Doppler radar[C]//Proc. of the National Doctoral Academic Forum on Information and Communications Technology, 2013.

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Velocity estimate method based on phase analysis and scatterers association

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