基于环境动态感知的空时自适应处理

方明; 刘宏伟; 戴奉周; 王小谟

doi:10.11999/JEIT141505

基于环境动态感知的空时自适应处理

doi: 10.11999/JEIT141505

2.
(西安电子科技大学雷达信号处理国家重点实验室西安 710071) ②(中国电子科学研究院北京 100041)

基金项目:

国家自然科学基金(61271291, 61201285)，新世纪优秀人才支持计划(NCET-09-0630)，全国优秀博士学位论文作者专项资金(FANEDD- 201156)和中央高校基本科研业务费专项资金

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- 被引次数: 0
出版历程
- 收稿日期: 2014-11-27
- 修回日期: 2015-05-11
- 刊出日期: 2015-08-19

Space-time Adaptive Processing via Dynamic Environment Sensing

1.
(National Laboratory of Radar Signal Processing, Xidian University, Xi&rsquo
2.
(National Laboratory of Radar Signal Processing, Xidian University, Xi&rsquo

摘要

摘要: 在非均匀环境中，缺乏独立同分布的训练样本会使空时自适应处理(Space-Time Adaptive Processing, STAP)算法性能严重下降。针对这个问题，该文提出一种基于环境动态感知的空时自适应处理方法。该方法首先通过发射一组正交信号感知观测场景获取杂波信息；然后利用杂波信息结合平台参数及系统参数预测未来一段时间内杂波的协方差矩阵；最后将预测的协方差矩阵与样本协方差矩阵进行组合以构造空时滤波器。仿真结果表明，与传统的知识辅助类STAP算法相比，该方法在缺乏准确先验知识的情况下依然可以有效地抑制非均匀环境中的杂波。
- 机载雷达 /
- 杂波抑制 /
- 空时自适应处理 /
- 感知 /
- 正交信号
Abstract: In heterogeneous clutter environments, Space-Time Adaptive Processing (STAP) shows notable performance degradation for lacking sufficient Independent Identically Distributed (IID) training samples. To solve this problem, a STAP approach is proposed based on dynamic environment sensing. With transmitted signal being orthogonal waveform, the clutter information is achieved. Then the clutter information and platform parameters are used and a clutter covariance matrix at future time is obtained incorporating system parameters. Finally, the space-time processor can be built based on the combination of the predicted clutter covariance matrix and the sample covariance matrix. The simulation results demonstrate that the new approach still can achieve better clutter suppression performance under circumstance of inaccurate environmental knowledge.
- Airborne radar /
- Clutter suppression /
- Space-Time Adaptive Processing (STAP) /
- Sensing /
- Orthogonal signal

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参考文献(18)

Ward J. Space-time adaptive processing for airborne radar[R]. MASS: Lincoln Lab, 1994.

范西昆, 曲毅. 知识辅助机载雷达杂波抑制方法研究进展[J]. 电子学报, 2012, 40(6): 1199-1206.

Fan Xi-kun and Qu Yi. An overview of knowledge-aided clutter mitigation methods for airborne radar[J]. Acta Electronica Sinica, 2012, 40(6): 1199-1206.

Wang P, Wang Z, Li H, et al.. Knowledge-aided parametric adaptive matched filter with automatic combining for covariance estimation[J]. IEEE Transactions on Signal Processing, 2014, 62(18): 4713-4722.

He M and Cao J. Recursive KA-STAP algorithm based on QR decomposition[C]. International Workshop on Microwave and Millimeter Wave Circuits and System Technology, Chengdu, China, 2013: 391-394.

阳召成, 黎湘, 王宏强. 基于空时功率谱稀疏性的空时自适应处理技术研究进展[J]. 电子学报, 2014, 42(6): 1194-1204.

Yang Zhao-cheng, Li Xiang, and Wang Hong-qiang. An overview of space-time adaptive processing technology based on sparsity of space-time power spectrum[J]. Acta Electronica Sinica, 2014, 42(6): 1194-1204.

Melvin W and Showman G. An approach to knowledge-aided covariance estimation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(3): 1021-1042.

Capraro C, Capraro G, Bradaric Ivan, et al.. Implementing digital terrain data in knowledge-aided space-time adaptive processing[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(3): 1080-1099.

王旭, 纠博, 刘宏伟, 等. 一种基于先验信息的MIMO雷达发射方向图设计方法[J]. 电子与信息学报, 2013, 35(12): 2802-2808.

Wang Xu, Jiu Bo, Liu Hong-wei, et al.. A beampattern design method for MIMO radar based on a priori information[J]. Journal of Electronics Information Technology, 2013, 35(12): 2802-2808.

Hua G and Abeysekera S. Receiver design for range and doppler sidelobe suppression using MIMO and phased-array radar[J]. IEEE Transactions on Signal Processing, 2013, 61(6): 1315-1326.

Khan W, Qureshi I, and Sultan K. Ambiguity function of Phased-MIMO radar with colocated antennas and its properties[J]. IEEE Transactions on Signal Processing, 2014, 11(7): 1220-1224.

Chen X, Zhou P, Hou Q, et al.. Design of 2-D MIMO antenna arrays for high resolution burden surface[C]. The 11th IEEE International Conference on Electronic Measurement Instruments, Harbin, China, 2013: 895-900.

Wu Y, Tang J, and Peng Y. On the essence of knowledge- aided clutter covariance estimate and its convergence[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(1): 569-585.

Zhu X and Bamler R. Super-resolution power and robustness of compressive sensing for spectral estimation with application to spaceborne tomographic SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(1): 247-258.

Fishler E, Haimovich A, Blum R, et al.. Spatial diversity in radars-models and detection performance[J]. IEEE Transactions on Signal Processing, 2006, 54(3): 823-838.

Skolnik M. 周万幸, 马林, 胡明春, 等. 雷达手册[M]. 第3版, 北京: 电子工业出版社, 2010: 644-655.

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