基于功率中值和归一化采样协方差矩阵的自适应匹配滤波检测器

刘明; 水鹏朗

doi:10.11999/JEIT140900

基于功率中值和归一化采样协方差矩阵的自适应匹配滤波检测器

doi: 10.11999/JEIT140900

刘明¹,
水鹏朗¹

基金项目:

国家自然科学基金(61271295)资助课题

计量
- 文章访问数: 1743
- HTML全文浏览量: 138
- PDF下载量: 628
- 被引次数: 0
出版历程
- 收稿日期: 2014-07-09
- 修回日期: 2014-10-08
- 刊出日期: 2015-06-19

Adaptive Matched Filter Detector Based on Power Median and Normalized Sample Covariance Matrix

Liu Ming¹,
Shui Peng-lang¹

摘要

摘要: 在非均匀海杂波环境中，参考单元中的异常单元限制了采样协方差矩阵(SCM)的估计性能，从而影响了传统自适应匹配滤波(AMF)检测器的检测性能。而考虑删除异常单元的方法在参考单元数目有限时可能导致矩阵的奇异性。鉴于此，在保持参考单元数目不变条件下，该文设计一种基于功率中值与归一化采样协方差矩阵(MNSCM)的估计方法，并将其与匹配滤波器(MF)相结合，构造一种新型的自适应匹配滤波检测器。与传统的自适应匹配滤波相比，该文设计的检测器在实测和仿真海杂波数据条件下均具有明显的性能优势。
- 目标检测 /
- 海杂波 /
- 自适应匹配滤波器 /
- 采样协方差矩阵 /
- 功率中值和归一化采样协方差矩阵
Abstract: In nonhomogeneous sea clutter, abnormal cells included reference cells constrain the performance of the Sample Covariance Matrix (SCM), and then influence the detection performance of the traditional Adaptive Matched Filter (AMF) detector, while censoring abnormal cells may cause singularity of the covariance matrix in the case of limited reference cells. Without changing number of the reference cells, this paper devises the median and normalized covariance matrix estimator and uses in the detection scheme of the AMF. Compared with the traditional AMF, the newly devised AMF obtains better performance in both measured and simulated clutter.
- Target detection /
- Sea clutter /
- Adaptive Matched Filter (AMF) /
- Sample Covariance Matrix (SCM) /
- Median and Normalized Sample Covariance Matrix (MNSCM)

HTML全文

参考文献(19)

Javier M C, Javier M G, Alvaro?B D C, et al.. Small target detection in high-resolution heterogeneous sea-clutter: an empirical analysis[J]. IEEE Transactions on Aerospace and

Electronic Systems, 2011, 47(3): 1880-1898.

Chen Xiao-long, Cai Yong, and Cai Fu-qing. Application of the sparse decomposition to micro-motion target detection embedded in sea clutter[C]. Proceedings of the 2013 International Conference on Radar, Adelaide, Canada, 2013: 163-166.

Chen Si-jia, Kong Ling-jiang, and Yang Jian-yu. Adaptive detection in compound-Gaussian clutter with partially correlated texture[C]. Proceedings of the 2013 IEEE Radar Conference, Ottawa, Canada, 2013: 1-5.

Chen Xiao-long, Guan Jian, He You, et al.. Detection and extraction of target with micro-motion in spiky sea clutter via short-time fractional fourier transform[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(2), 1002-1018.

Maria G, Fulvio G, and Muralidhar R. Statistical analysis of measured polarimetric clutter data at different resolutions [J]. IEE Proceedings-Radar, Sonar and Navigation, 2006, 153(6): 473-481.

Maria G, Fulvio G, Muralidhar R, et al.. Impact of the sea clutter nonstationarity on disturbance covariance matrix estimation and CFAR detector performance[J]. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(6): 1502-1513.

Frank R C, Daniel F R, Edward K J, et al.. A CFAR adaptive matched filter detector[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(1): 208-216.

Chan H C, Radar sea-clutter at low grazing angles[J]. IEE Proceedings F Radar and Signal Processing, 1990, 137(2): 102-112.

Ward, K D, Baker, C J, and Watts S. Maritime surveillance radar. part I: radar scattering from the ocean surface[J]. IEE Proceedings, F Radar and Signal Processing, 1990, 137(2): 51-62.

Fulvio G and James H M. Performance analysis of two covariance matrix estimators in compound-Gaussian clutter [J]. IEE Proceedings-Radar, Sonar and Navigation, 1999, 146(3): 133-140.

张玉石, 许心瑜, 尹雅磊, 等. L波段小擦地角海杂波幅度统计特性研究[J]. 电子与信息学报, 2014, 36(5): 1044-1048.

Zhang Yu-shi, Xu Xin-yu, Yin Ya-lei, et al.. Research on amplitude statistics of L-band low grazing angle sea clutter [J]. Journal of Electronics Information Technology, 2014, 36(5): 1044-1048.

Wei Na. Sea clutter covariance estimation with data-adaptive selection[C]. Proceedings of the IET International Radar Conference, Xian, China, 2013: 1-5.

Aghaabdellahian N and Hashemi M M. Improving performance of adaptive detectors in nonhomogeneous environment[C]. Proceedings of the 21st Iranian Conference on Electrical Engineering, Mashhad, Iran, 2013: 1-5.

Moya J C, Menoyo J G, Lopez A A, et al.. Statistical analysis of a high-resolution sea-clutter database[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(4): 2024-2037.

Fulvio G and Maria G. Texture modeling, estimation, and validation using measured sea clutter data[J]. IEE Proceedings-Radar, Sonar and Navigation, 2002, 149(3): 115-124.

Maria G, Federica B, and Fulvio G. X-band sea-clutter non-stationarity: influence of long waves[J]. IEEE Journal of Oceanic Engineering, 2004, 28(2): 269-283.

Haykin S. Adaptive Radar Signal Processing[M]. Hoboken, NJ: John Wiley and Sons, Inc., 2007: 159-192.

施引文献

资源附件(0)

访问统计