Submit Manuscript
Peer Review
Editor Work
| Citation: | LI Yueli, MA Meng’en, ZHAO Chonghui, et al. Forward-looking Imaging via Doppler estimates of sum-difference measurements in scanning monopulse radar[J].Journal of Radars, 2021, 10(1): 131–142. doi: 10.12000/JR20111
|
Forward-looking Imaging via Doppler Estimates of Sum-difference Measurements in Scanning Monopulse Radar（in English）
DOI: 10.12000/JR20111
More Information-
Abstract
Monopulse technique is used in scanning radar systems to improve image quality in the forward-looking area. However, monopulse measurements fail to resolve multiple targets in the same resolution cell because of angular glint which often results to image blurring. In response to this, we propose a monopulse forward-looking imaging method utilizing Doppler estimates of sum-difference measurements. First, target multiplicity is resolved by exploiting the different Doppler shifts caused by the relative motion between the platform and the targets at different directions. High azimuthal angle measurement accuracy of the Doppler estimates is then obtained using the Sum-Difference Amplitude-Comparison (SDAC) monopulse technique. Subsequently, the intensity of the sum channel estimates is projected onto the image plane according to the range and angle measurements. To further improve the precision of angle measurements, a Chirp-Z Transform (CZT)-based algorithm is proposed for the reconstruction of the Doppler estimates of the sum-difference channels. Simulation results demonstrate the capability of the proposed methods in resolving multiple targets at high squint angles in a large scanning field. Real data experiments show significant improvement of image profiles using the CZT-based algorithm compared to that of the conventional monopulse imaging method. -
-
References
[1] 杨建宇. 雷达对地成像技术多向演化趋势与规律分析[J]. 雷达学报, 2019, 8(6): 669–692. doi: 10.12000/JR19099YANG Jianyu. Multi-directional evolution trend and law analysis of radar ground imaging technology[J]. Journal of Radars, 2019, 8(6): 669–692. doi: 10.12000/JR19099[2] ZHANG Yongchao, ZHANG Yin, HUANG Yulin, et al. Angular superresolution for scanning radar with improved regularized iterative adaptive approach[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(6): 846–850. doi: 10.1109/LGRS.2016.2550491[3] 吴迪, 朱岱寅, 朱兆达. 机载雷达单脉冲前视成像算法[J]. 中国图象图形学报, 2010, 15(3): 462–469. doi: 10.11834/jig.20100317WU Di, ZHU Daiyin, and ZHU Zhaoda. Research on nomopulse forward-looking imaging algorithm for airborne radar[J]. Journal of Image and Graphics, 2010, 15(3): 462–469. doi: 10.11834/jig.20100317[4] 吴迪, 朱岱寅, 田斌, 等. 单脉冲成像算法性能分析[J]. 航空学报, 2012, 33(10): 1905–1914.WU Di, ZHU Daiyin, TIAN Bin, et al. Performance evaluation for monopulse imaging algorithm[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(10): 1905–1914.[5] 吴迪, 杨成杰, 朱岱寅, 等. 一种用于单脉冲成像的自聚焦算法[J]. 电子学报, 2016, 44(8): 1962–1968. doi: 10.3969/j.issn.0372-2112.2016.08.027WU Di, YANG Chengjie, ZHU Daiyin, et al. An autofocusing algorithm for monopulse imaging[J]. Acta Electronica Sinica, 2016, 44(8): 1962–1968. doi: 10.3969/j.issn.0372-2112.2016.08.027[6] 李悦丽, 梁甸农, 黄晓涛. 一种单脉冲雷达多通道解卷积前视成像方法[J]. 信号处理, 2007, 23(5): 699–703. doi: 10.3969/j.issn.1003-0530.2007.05.013LI Yueli, LIANG Diannong, and HUANG Xiaotao. A multi-channel deconvolution based on forword-looking imaging method in monopulse radar[J]. Signal Processing, 2007, 23(5): 699–703. doi: 10.3969/j.issn.1003-0530.2007.05.013[7] 唐琳, 焦淑红, 齐欢, 等. 一种单脉冲雷达多通道L1正则化波束锐化方法[J]. 电子与信息学报, 2014, 36(9): 2201–2206. doi: 10.3724/SP.J.1146.2013.01792TANG Lin, JIAO Shuhong, QI Huan, et al. A new mono-pulse radar beam sharpening method with multichannel L1 regularization[J]. Journal of Electronics&Information Technology, 2014, 36(9): 2201–2206. doi: 10.3724/SP.J.1146.2013.01792[8] SHERMAN S M, BARTON D K, 周颖, 陈远征, 赵锋, 等译. 单脉冲测向原理与技术[M]. 2版. 北京: 国防工业出版社, 2013: 172–197.SHERMAN S M, BARTON D K, ZHOU Ying, CHEN Yuanzheng, ZHAO Feng, et al. translation. Monopulse Principles and Techniques[M]. 2nd ed. Beijing: National Defense Industry Press, 2013: 172–197.[9] ZHANG Xin, WILLETT P K, and BAR-SHALOM Y. Monopulse radar detection and localization of multiple unresolved targets via joint bin processing[J]. IEEE Transactions on Signal Processing, 2005, 53(4): 1225–1236. doi: 10.1109/TSP.2005.843732[10] 杨洋, 李悦丽. 单脉冲前视成像多目标分辨算法[J]. 信号处理, 2016, 32(9): 1055–1064. doi: 10.16798/j.issn.1003-0530.2016.09.07YANG Yang and LI Yueli. Multi-targets discrimination algorithm in monopulse forward-looking imaging[J]. Journal of Signal Processing, 2016, 32(9): 1055–1064. doi: 10.16798/j.issn.1003-0530.2016.09.07[11] LONG Teng, LU Zheng, DING Zegang, et al. A DBS Doppler centroid estimation algorithm based on entropy minimization[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10): 3703–3712. doi: 10.1109/TGRS.2011.2142316[12] ZHANG Shouhong, MA Changzheng, and CHEN Baixiao. Monopulse radar three-dimensional imaging of maneuvering targets[C]. SPIE 3545, International Symposium on Multispectral Image Processing, Wuhan, China, 1998: 193–196. doi: 10.1117/12.323634.[13] LI Jian and STOICA P. An adaptive filtering approach to spectral estimation and SAR imaging[J]. IEEE Transactions on Signal Processing, 1996, 44(6): 1469–1484. doi: 10.1109/78.506612[14] 马长征, 张守宏. 超分辨在单脉冲雷达三维成像中的应用[J]. 西安电子科技大学学报, 1999, 26(3): 379–382. doi: 10.3969/j.issn.1001-2400.1999.03.027MA Changzheng and ZHANG Shouhong. Applications of super-resolution signal processing on monopulse radar three dimensional imaging[J]. Journal of Xidian University, 1999, 26(3): 379–382. doi: 10.3969/j.issn.1001-2400.1999.03.027[15] LIU Xiaocong and LI Yueli. Parameter estimation of narrowband radio frequency interference based on local refinement search in frequency domain[C]. 2015 IEEE International Conference on Communication Problem-Solving, Guilin, China, 2015: 145–148. doi: 10.1109/ICCPS.2015.7454112.[16] CHEN Hongmeng, LI Ming, ZHANG Peng, et al. Resolution enhancement for Doppler beam sharpening imaging[J]. IET Radar,Sonar&Navigation, 2015, 9(7): 843–851. doi: 10.1049/iet-rsn.2014.0384[17] 孙泓波, 顾红, 苏卫民, 等. 机载脉冲多普勒雷达DBS成像实验研究[J]. 数据采集与处理, 2001, 16(4): 423–427. doi: 10.3969/j.issn.1004-9037.2001.04.007SUN Hongbo, GU Hong, SU Weimin, et al. Experimental research of DBS imaging based on airborne pulse Doppler radar[J]. Journal of Data Acquisition&Processing, 2001, 16(4): 423–427. doi: 10.3969/j.issn.1004-9037.2001.04.007[18] 毛士艺, 李少洪, 黄永红, 等. 机载PD雷达DBS实时成像研究[J]. 电子学报, 2000, 28(3): 32–34. doi: 10.3321/j.issn:0372-2112.2000.03.009MAO Shiyi, LI Shaohong, HUANG Yonghong, et al. Study of real-time image by DBS on airborne PD radar[J]. Acta Electronica Sinica, 2000, 28(3): 32–34. doi: 10.3321/j.issn:0372-2112.2000.03.009[19] 王娟, 赵永波. Keystone变换实现方法研究[J]. 火控雷达技术, 2011, 40(1): 45–51. doi: 10.3969/j.issn.1008-8652.2011.01.010WANG Juan and ZHAO Yongbo. Research on implementation of Keystone transform[J]. Fire Control Radar Technology, 2011, 40(1): 45–51. doi: 10.3969/j.issn.1008-8652.2011.01.010 -
Proportional views
- Publishing Ethics
- Journal Insights
- Abstracting & Indexing
- Peer Review Policies
- Guide for Authors
- Conference
- ISSN 2095-283X (Print)ISSN 2097-339X (Online)
- CN 10-1030/TN
- CODEN LXEUAO
About Journal
- Sponsor: China Radio Detection and Ranging Industry Association (CRIA)
- Phone: 010-58887062
- Email：radars@aircas.ac.cn
- Publisher: Leida Xuebao Bianjibu (Editorial office of the Journal of Radars)
Contacts Us
京ICP备20021838号-8
Supported by: Beijing Renhe Information Technology Co. Ltd
Export File
Citation
Format
Content
DownLoad:
- Figure 1. Geometry for forward-looking imaging of a scanning radar
- Figure 2. Flowchart of mono pulse forward-looking imagination based on Doppler estimates
- Figure 3. Flowchart of monopulse forward-looking imaging based on the reconstructed Doppler estimates
- Figure 4. Comparison of forward-looking imaging performance (SNR=20 dB)
- Figure 5. Azimuthal contour plots for point targets at the range cell 1730 m (SNR=20 dB)
- Figure 6. Comparison of experimental results in forward looking imaging
- Figure 7.
- Figure 7. Comparison of experimental results in forward-looking imaging
- Figure 1.
- Figure 2.
- Figure 3.
- Figure 4.
- Figure 5.
- Figure 6.
- Figure 7.
- Figure 7.