基于运动参数估计的雷达高速目标检测方法*

doi:10.7523/j.ucas.2024.011

摘要/Abstract

摘要： 长时间的相干积累一直是提升雷达回波能量的有效手段,对于高速运动目标而言,在一段长的相干处理间隔内,无法忽视其径向速度和径向加速度带来的跨距离单元和多普勒频率扩散现象,目标高速带来的速度模糊问题也需要得到解决。本文提出了一种基于运动参数估计的高速目标检测方法,通过分段相干积累的方式抑制各分段下的跨距离单元现象,将分段下的积累峰值位置作为参数估计输入的样本点,通过搜索获得目标径向加速度并构造滤波器对回波相位中的非线性分量进行补偿,利用Keystone变换结合模糊项补偿校正雷达回波的跨距离单元现象,最后通过方位向FFT实现对高速目标回波信号的相干积累。

关键词: 跨距离单元, 多普勒频率扩散, 长时间相干积累, 高速目标检测, 速度模糊

Abstract: Coherent accumulation over a long period of time has been an effective means to enhance radar echo energy. However, for high-speed moving target, within a long coherent processing interval, across range unit (ARU) and Doppler frequency migration (DFM) caused by their velocity and acceleration in the radar radial direction cannot be ignored. Additionally, the velocity ambiguity problem caused by high speed also needs to be addressed. This paper proposes a high-speed target detection method based on motion parameter estimation. By segmenting coherent accumulation, the ARU under each segment is suppressed. The peak position of the echo after accumulation under each segment is used as a sample point for parameter estimation input. A filter is constructed using the target radial acceleration obtained through searching to compensate for nonlinear components in the echo phase. Finally, Keystone transform is used in conjunction with velocity ambiguity term compensation to correct ARU in radar echoes, and coherent accumulation of the high-speed target echo signal is achieved by performing FFT along the azimuth.

Key words: across range unit, Doppler frequency migration, long-time coherent accumulation, high-speed target detection, velocity ambiguity

中图分类号:

TN957

郭真方, 孙吉利, 王帅. 基于运动参数估计的雷达高速目标检测方法^*[J]. 中国科学院大学学报, DOI: 10.7523/j.ucas.2024.011.

GUO Zhenfang, SUN Jili, WANG Shuai. Radar high-speed target detection method based on motion parameter estimation[J]. Journal of University of Chinese Academy of Sciences, DOI: 10.7523/j.ucas.2024.011.

参考文献

[1] Guo Y F, Zhang Y L, Xue A K.Coherent integration weak target detection algorithm based on short time sliding window[C]//Proceedings of the 10th World Congress on Intelligent Control and Automation. Beijing, China. IEEE, 2012: 4264-4266. DOI: 10.1109/WCICA.2012.6359195.
[2] Cantrell B, de Graaf J, Willwerth F, et al. Development of a digital array radar (DAR)[J]. IEEE Aerospace and Electronic Systems Magazine, 2002, 17(3): 22-27. DOI: 10.1109/62.990350.
[3] Tao R, Zhang N, Wang Y.Analysing and compensating the effects of range and Doppler frequency migrations in linear frequency modulation pulse compression radar[J]. IET Radar, Sonar & Navigation, 2011, 5(1): 12. DOI: 10.1049/iet-rsn.2009.0265.
[4] Carlson B D, Evans E D, Wilson S L.Search radar detection and track with the Hough transform. I. system concept[J]. IEEE Transactions on Aerospace and Electronic Systems, 1994, 30(1): 102-108. DOI: 10.1109/7.250410.
[5] Carlson B D, Evans E D, Wilson S L.Search radar detection and track with the Hough transform. II. detection statistics[J]. IEEE Transactions on Aerospace and Electronic Systems, 1994, 30(1): 109-115. DOI: 10.1109/7.250411.
[6] Carlson B D, Evans E D, Wilson S L.Search radar detection and track with the Hough transform. III. detection statistics[J]. IEEE Transactions on Aerospace and Electronic Systems, 1994, 30(1): 116-125. DOI: 10.1109/7.250412.
[7] Carretero-Moya J, Gismero-Menoyo J, Asensio-Lopez A, et al.Small-target detection in sea clutter based on the Radon Transform[C]//2008 International Conference on Radar. Adelaide, SA, Australia. IEEE, 2008: 610-615. DOI: 10.1109/RADAR.2008.4653995.
[8] Xu J, Yu J, Peng Y N, et al.Radon-fourier transform for radar target detection, I: Generalized Doppler filter bank[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(2): 1186-1202. DOI: 10.1109/TAES.2011.5751251.
[9] Xu J, Yu J, Peng Y N, et al.Radon-fourier transform for radar target detection (II): Blind speed sidelobe suppression[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(4): 2473-2489. DOI: 10.1109/TAES.2011.6034645.
[10] Yu J, Xu J, Peng Y N, et al.Radon-fourier transform for radar target detection (III): Optimality and fast implementations[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(2): 991-1004. DOI: 10.1109/TAES.2012.6178044.
[11] 吴兆平, 符渭波, 苏涛, 等. 基于快速Radon-Fourier 变换的雷达高速目标检测[J]. 电子与信息学报, 2012, 34(8): 1866-1871. DOI: CNKI:SUN:DZYX.0.2012-08-013.
[12] Rao X, Tao H H, Su J, et al.Axis rotation MTD algorithm for weak target detection[J]. Digital Signal Processing, 2014, 26: 81-86. DOI: 10.1016/j.dsp.2013.12.003.
[13] Chen X L, Guan J, Liu N B, et al.Maneuvering target detection via radon-fractional Fourier transform-based long-time coherent integration[J]. IEEE Transactions on Signal Processing, 2014, 62(4): 939-953. DOI: 10.1109/TSP.2013.2297682.
[14] Xu J, Xia X G, Peng S B, et al.Radar maneuvering target motion estimation based on generalized radon-fourier transform[J]. IEEE Transactions on Signal Processing, 2012, 60(12): 6190-6201. DOI: 10.1109/TSP.2012.2217137.
[15] Sun Z, Li X L, Cui G L, et al.A fast approach for detection and parameter estimation of maneuvering target with complex motions in coherent radar system[J]. IEEE Transactions on Vehicular Technology, 2021, 70(10): 10278-10292. DOI: 10.1109/TVT.2021.3104659.
[16] Zhang J C, Su T, Zheng J B, et al.Novel fast coherent detection algorithm for radar maneuvering target with jerk motion[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(5): 1792-1803. DOI: 10.1109/JSTARS.2017.2651156.
[17] Tian J, Cui W, Wu S.A novel method for parameter estimation of space moving targets[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(2): 389-393. DOI: 10.1109/LGRS.2013.2263332.
[18] Li G, Xia X G, Peng Y N.Doppler keystone transform: An approach suitable for parallel implementation of SAR moving target imaging[J]. IEEE Geoscience and Remote Sensing Letters, 2008, 5(4): 573-577. DOI: 10.1109/LGRS.2008.2000621.
[19] Perry R P, DiPietro R C, Fante R L. SAR imaging of moving targets[J]. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(1): 188-200. DOI: 10.1109/7.745691.
[20] Zhang S S, Zeng T, Long T, et al.Dim target detection based on keystone transform[C]//IEEE International Radar Conference. Arlington, VA, USA. IEEE, 2005: 889-894. DOI: 10.1109/RADAR.2005.1435953.
[21] Yuan S J, Wu T, Mao M, et al.Application research of keystone transform in weak high-speed target detection in low-PRF narrowband Chirp radar[C]//2008 9th International Conference on Signal Processing. Beijing, China. IEEE, 2008: 2452-2456. DOI: 10.1109/ICOSP.2008.4697645.
[22] Zhu D Y, Li Y, Zhu Z D.A keystone transform without interpolation for SAR ground moving-target imaging[J]. IEEE Geoscience and Remote Sensing Letters, 2007, 4(1): 18-22. DOI: 10.1109/LGRS.2006.882147.

基于运动参数估计的雷达高速目标检测方法^*

Radar high-speed target detection method based on motion parameter estimation

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

访问统计

联系我们

[1]	郭艺琼, 任明山, 张衡, 岳海霞. 基于多项式模型和方位重采样的中高轨斜视滑动聚束SAR成像方法[J]. 中国科学院大学学报, 0, (): 20240710-20240710.
[2]	许璐, 张红, 王超, 吴樊, 张波, 汤益先. 基于张量表示的多时相极化SAR农作物分类方法^*[J]. 中国科学院大学学报, 2024, (): 99-.
[3]	苏白华宁, 刘畅, 王超. 基于参数估计与子孔径提取的船舶ISAR实时成像算法[J]. 中国科学院大学学报, 2023, 40(5): 647-657.
[4]	王正晟, 李亚林, 张洪群. 基于GAN序列的卫星数据接收系统故障定位[J]. 中国科学院大学学报, 2023, 40(1): 109-118.
[5]	申晓天, 郑明洁. 一种新的基于FrFT的动目标测速和定位方法[J]. 中国科学院大学学报, 2023, 40(1): 84-92.
[6]	邢文继, 金燕, 仇晓兰, 丁赤飚, 周晓. 高分辨率SAR子孔径图像相干性分析及其地物分类应用[J]. 中国科学院大学学报, 2022, 39(6): 764-775.
[7]	尹钟政, 任雨薇, 郑明洁. 一种低秩稀疏矩阵分解联合目标轨迹区域提取的ViSAR-GMTI方法^*[J]. 中国科学院大学学报, 0, (): 75-75.
[8]	郑慧敏, 郑明洁, 张振宁, 申晓天. 基于低秩和一维稀疏矩阵分解的多通道SAR-GMTI方法[J]. 中国科学院大学学报, 2022, 39(2): 208-216.
[9]	林世明, 张毅, 王吉利, 赵爽. 星载双基InSAR系统中的电离层色散效应分析与校正[J]. 中国科学院大学学报, 2021, 38(6): 809-816.
[10]	刘雨洁, 齐向阳. 基于长时间间隔序贯SAR图像的运动舰船跟踪方法[J]. 中国科学院大学学报, 2021, 38(5): 642-648.
[11]	向建冰, 吕孝雷, 付希凯. 基于双曲等效的双星滑动聚束SAR两步成像算法[J]. 中国科学院大学学报, 2021, 38(4): 511-518.
[12]	宋志华, 陈锟山, 曾江源, 许镇. 一种基于FMCW雷达的慢速目标检测自适应滤波器[J]. 中国科学院大学学报, 2021, 38(3): 382-391.
[13]	罗开盛. 基于面向对象技术的旅游用地遥感识别[J]. 中国科学院大学学报, 2020, 37(4): 490-497.
[14]	王泽隆, 徐向辉, 张雷. 基于仿真SAR图像深度迁移学习的自动目标识别[J]. 中国科学院大学学报, 2020, 37(4): 516-524.
[15]	杨牡丹, 魏中浩, 徐志林, 张冰尘, 洪文. 一种基于层次稀疏的全极化SAR层析成像方法[J]. 中国科学院大学学报, 2020, 37(4): 525-531.