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Proceedings Paper

Spatial correlation characteristic analysis of land clutter for PRC_cw radar at x-band
Author(s): Zhiguo Cao; Zhiyong Zhang; Tianxu Zhang
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Paper Abstract

Pseudo-random code continuous wave (PRC_CW) radar, which is low probability of intercept and has good ability of target detection in clutter, is widely used in fields of target detection, tracking, guiding, detecting underground, and so on. Temporal distribution function of land clutter was always studied and the backscatter from land was supposed spatially homogeneous. In fact, the backscatter from various resolution cells is obviously different, especially under complicated land background, since the number of clutter sources is too great. So it is very important for spatial correlation characteristic analysis of land clutter. In this paper, spatial correlation characteristic of land clutter for PRC_CW radar at X-band was analyzed. The time spread of radar echo exists while the radar works at low grazing angle. To PRC_CW radar, the time spread of radar echo results in that the receiving signal amplitude at a certain time is the sum of many spread codes. In this paper, spatial amplitude distribution and spatial correlation function of some typical land clutter under the condition of single code were firstly discussed. Then, we point out the problem of time spread of echo signal at low grazing angle and proposed a superposition method to simulate real clutter echo of PRC_CW radar. Finally we analyzed the spatial correlation characteristics of some typical land clutter.

Paper Details

Date Published: 25 September 1998
PDF: 4 pages
Proc. SPIE 3545, International Symposium on Multispectral Image Processing (ISMIP'98), (25 September 1998); doi: 10.1117/12.323630
Show Author Affiliations
Zhiguo Cao, Huazhong Univ. of Science and Technology (China)
Zhiyong Zhang, Huazhong Univ. of Science and Technology (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 3545:
International Symposium on Multispectral Image Processing (ISMIP'98)
Ji Zhou; Anil K. Jain; Tianxu Zhang; Yaoting Zhu; Mingyue Ding; Jianguo Liu, Editor(s)

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