期刊文献+

大距离徙动情况下距离多普勒(RD)算法与后向投影(BP)算法的比较 被引量:8

Comparison of RD Algorithm and BP Algorithm Under Severe Range Migration
下载PDF
导出
摘要 距离多普勒 (Range Doppler,RD)算法是传统窄带 /窄波束SAR的经典成像算法 ,它借助菲涅耳近似 ,只保留了斜距R(t)的线性部分和二次项。但是当距离徙动严重时 ,方位向二次以上的高次相位项不能忽略 ,这会大大降低聚焦精度。后向投影 (Back Projection ,BP)算法是一种基于时域处理的成像算法 ,通过计算双程延时将对应信号进行相干累加 ,获得高分辨率SAR图像。BP算法由于用时延代替了相位的概念 ,故与频率无关 ,不存在距离徙动校正的问题。本文介绍了RD算法和BP算法的原理及算法实现 ,并且利用距离向插值改进了BP算法。最后 ,结合计算机仿真结果详细比较了这两种算法的若干性能指标 。 Range-Doppler(RD)algorithm is a typical imaging algorithm for traditional narrow-band /narrow-beam SAR. It only keeps the linear part and the quadratic term of the slant range distance by using Fresnel approximation. However, the high-order parts of azimuth phase cannot be ignored when range migration is large, which would worsen focusing precision greatly. Back-Projection (BP) algorithm based on time-domain processing, can attain high-resolution SAR image by calculating the two-way propagation delay time and coherently summing up the corresponding signals. BP algorithm replaces the concept of phase with delay time, so it is irrelevant to frequency and the problem of range migration correction does not exist. This paper introduces basic theory and implementation of RD algorithm and BP algorithm, and improves BP algorithm through range interpolation. Comparison of the performance of two algorithms with the computer simulation results proves that BP algorithm is more suitable than RD algorithm for SAR imaging under severe range migration.
出处 《雷达科学与技术》 2004年第6期349-354,共6页 Radar Science and Technology
关键词 距离徙动 距离多普勒(RD)算法 后向投影(BP)算法 插值 range migration Range-Doppler(RD)algorithm Back-Projection(BP) algorithm interpolation
  • 相关文献

同被引文献47

  • 1江志红,赵懿,皇甫堪,万建伟,程翥.调频连续波SAR的研究进展[J].现代雷达,2008,30(2):20-24. 被引量:19
  • 2刘永坦.雷达成像技术[M].哈尔滨:哈尔滨工业大学出版社,2003.
  • 3卡明,洪文,胡东辉,等,译.合成孔径雷达成像-算法与实现[M].北京:电子工业出版社,2007.
  • 4耿淑敏,江志红,程翥,皇甫堪.FM-CW SAR距离-多普勒成像算法研究[J].电子与信息学报,2007,29(10):2346-2349. 被引量:18
  • 5MAHAFZABR,ELSHERBENIAZ.雷达系统设计MATLAB仿真[M].朱富国,黄晓涛,黎向阳,等译.北京:电子工业出版社,2009:156.
  • 6GUHA S. KRISNAN S. VENKATASUBRAMANIAN S. Data Visualization and Mining Using the GPU [C]//Proceedings of SIGKDD. [So 1. J :ACM. 2005: 1310-1319.
  • 7HARTLEY T D R. CATALYUREK U. RUIZ A. et al. Biomedical Image Analysis on a Cooperative Cluster of GPUs and Multicores[CJII 22nd ACM International Conference on Supercomputing. Island of Kos , Greece: ACM. 2008: 15-25.
  • 8CLEMENTE C. BISCEGLIE M D. SANTO MD. et al. Processing of Synthetic Aperture Radar Data with GPGPU[C]// IEEE Workshop on Signal Processing Systems. Tampere , Finlandj s. n. J. 2009:309-314.
  • 9NING x?, YEH Chunrnao , ZHOU Bin. et al. Multiple-GPU Accelerated Range-Doppler Algorithm for Synthetic Aperture Radar Imaging[ CJ II IEEE International Radar Conference. Kansas City. MO. USA: [so n. J. 2011:698-701.
  • 10ANDERSSON L E. On the Determination of a Function from Spherical Averages [J]. SIAM Journal on Mathematical Analysis. 1988. 19(1) :214-232.

引证文献8

二级引证文献24

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部