基于PAST处理的机载双基雷达自适应角度-多普勒补偿算法

赵军; 田斌; 朱岱寅

doi:10.12000/JR17053

基于PAST处理的机载双基雷达自适应角度-多普勒补偿算法

DOI: 10.12000/JR17053

赵军^1,2, ,,
田斌^3,,
朱岱寅^1,

①.
南京航空航天大学电子信息工程学院南京 210016
②.
空军第一航空学院信阳 464000
③.
西安电子工程研究所西安 710100

基金项目: 国家自然科学基金（61671240）

详细信息

作者简介:
赵　军(1974–)，男，河南新蔡人，现为南京航空航天大学博士后，副教授，主要研究方向为空时自适应处理。E-mail: happyzj112@163.com

田　斌(1983–)，男，陕西周至人，现为西安电子工程研究所高级工程师，主要研究方向为雷达系统设计。E-mail: tianbin218@163.com

朱岱寅(1974–)，男，江苏无锡人，现为南京航空航天大学电子信息工程学院教授，博士生导师，IEEE会员，主要研究方向为雷达成像和信号处理。E-mail: zhudy@nuaa.edu.cn

通讯作者:
赵军 happyzj112@163.com

计量
- 文章访问数: 3149
- HTML全文浏览量: 463
- PDF下载量: 381
- 被引次数: 0
出版历程
- 收稿日期: 2017-05-17
- 修回日期: 2017-06-21
- 网络出版日期: 2017-12-28

Adaptive Angle-Doppler Compensation Method for Airborne Bistatic Radar Based on PAST

Zhao Jun^{1,2
, ,},
Tian Bin^3
,,
Zhu Daiyin^1
,

①.
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
②.
The First Aeronautical Institute of Air force, Xinyang 464000, China
③.
Xi’an Electronic Engineering Research Institute, Xi’an 710100, China

Funds: The National Natural Science Foundation of China (61671240)

摘要

摘要:
自适应角度-多普勒补偿算法根据样本数据本身来自适应地估计补偿参数，从而避免惯导系统误差造成的补偿性能下降问题，但该算法必须对杂波协方差矩阵进行估计和特征分解，运算量巨大。针对这一问题，该文研究了基于近似投影子空间跟踪(PAST)处理的自适应角度-多普勒补偿算法，该方法先采用循环迭代处理快速估计出各距离单元主特征向量谱中心的位置参数，避免了矩阵特征分解带来的运算负担，然后通过补偿使得各单元的谱中心重合。仿真结果表明，该方法能有效解决机载双基雷达杂波非均匀问题，其性能与基于特征分解算法相当，但运算量显著降低，便于工程实现。
- 机载双基雷达 /
- 近似投影子空间跟踪 /
- 自适应角度多普勒补偿 /
- 空时自适应处理
Abstract:
The adaptive angle-Doppler compensation method adaptively extracts requisite information based on the data itself, thereby avoiding the problem of performance degradation due to inertial system error. However, this method requires the estimation and eigen decomposition of a sample covariance matrix, which has high computational complexity and limits its real-time application. In this paper, we investigate an adaptive angle-Doppler compensation method based on Projection Approximation Subspace Tracking (PAST). This method uses cyclic iterative processing to quickly estimate the positions of the spectral center of the maximum eigenvector in each range cell, thereby avoiding the computational burden of matrix estimation and eigen decompositon. Then, the spectral centers of all range cells are overlapped by two-dimensional compensation. Our simulation results demonstrate that the proposed method can effectively reduce the nonhomogeneity of airborne bistatic radar, with a performance is similar to that of eigen-decomposition algorithms, but with a reduced computational load and easy implementation.
- Airborne bistatic radar /
- Projection Approximation Subspace Tracking (PAST) /
- Adaptive angle-Doppler compensation /
- Space Time Adaptive Processing (STAP)

HTML全文

图 1 机载双基雷达几何结构图

Figure 1. Geometry of airborne bistatic radar

下载: 全尺寸图片幻灯片

图 2 机载双基雷达典型几何配置图

Figure 2. Typical cases of airborne bistatic radar geometry

下载: 全尺寸图片幻灯片

图 3 典型几何配置下机载双基雷达杂波功率谱

Figure 3. Clutter power spectrum of airborne bistatic radar geometry in typical cases

下载: 全尺寸图片幻灯片

图 4 PA²DC算法流程图

Figure 4. Flow chart of PA²DC method

下载: 全尺寸图片幻灯片

图 5 PA²DC算法主特征矢量杂波谱中心估计

Figure 5. Clutter spectrum peak estimation of PA²DC method

下载: 全尺寸图片幻灯片

图 6 PA²DC算法谱中心估计的均方根误差

Figure 6. RMS of clutter spectrum peak estimation based on PA²DC method

下载: 全尺寸图片幻灯片

图 7 PA²DC算法杂波功率谱比较

Figure 7. Clutter power spectrum comparison

下载: 全尺寸图片幻灯片

图 8 PA²DC算法改善因子比较

Figure 8. Improve factor comparison

下载: 全尺寸图片幻灯片

表 1 雷达仿真参数

Table 1. Simulation parameters for radar

参数名称	参数数值
接收阵元数	N=10
相干处理脉冲数	K=10
脉冲重复频率(Hz)	f_r=2234
基线距离(km)	L=100
双基距离和(km)	R_s=153
发射平台高度(km)	H_T=8
接收平台高度(km)	H_R=6
发射机速度(m/s)	v_T=140
接收机速度(m/s)	v_R=140
雷达工作波长(m)	λ=0.23
阵元间距	d=λ/2
单元输入杂噪比(dB)	CNR=50

下载: 导出CSV

参考文献(14)

[1]	张良, 徐艳国. 机载预警雷达技术发展展望[J]. 现代雷达, 2015, 37(1): 1–7 Zhang Liang and Xu Yan-guo. Prospect for technology of airborne early warning radar[J]. Modern Radar, 2015, 37(1): 1–7
[2]	张永顺, 冯为可, 赵杰, 等. 时变加权的机载双基雷达降维空时自适应处理[J]. 电波科学学报, 2015, 30(1): 194–200. DOI: 10.13443/j.cjors.2014040701 Zhang Yong-shun, Feng Wei-ke, Zhao Jie, et al. A dimension-reduced STAP method for airborne bistatic radar based on time-varying weighting techniques[J]. Chinese Journal of Radio Science, 2015, 30(1): 194–200. DOI: 10.13443/j.cjors.2014040701
[3]	Greve S, Ries P, Lapierre F, et al. Framework and taxonomy for radar space-time adaptive processing (STAP) methods[J]. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(3): 1084–1099. DOI: 10.1109/TAES.2007.4383596
[4]	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. DOI: 10.3969/j.issn.0372-2112.2014.06.024 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. DOI: 10.3969/j.issn.0372-2112.2014.06.024
[5]	Borsari G K. Mitigating effects on STAP processing caused by an inclined array[C]. Proceedings of the 1998 IEEE National Radar Conference, Dallas, TX, USA, 1998: 135–140.
[6]	冯坤菊, 王春阳, 段垣丽, 等. 机载双基地STAP的OP-DW预处理算法及其性能研究[J]. 电子学报, 2011, 39(3): 700–704 Feng Kun-ju, Wang Chun-yang, Duan Yuan-li, et al. Research on the OP-DW algorithm of bistatic radar and its performance[J]. Acta Electronica Sinica, 2011, 39(3): 700–704
[7]	Himed B, Zhang Y, and Hajjari A. STAP with angle-Doppler compensation for bistatic airborne radars[C]. Proceedings of the IEEE National Radar Conference, Long Beach, CA, USA, 2002: 311–317.
[8]	Himed B. Effects of bistatic clutter dispersion on STAP systems[J]. IEE Proceedings-Radar,Sonar and Navigation, 2003, 150(1): 28–32. DOI: 10.1049/ip-rsn:20030100
[9]	Fallah A and Bakhshi H. Extension of adaptive angle-Doppler compensation (AADC) in STAP to increase homogeneity of data in airborne bistatic radar[C]. Proceedings of the 2012 6th International Symposium on Telecommunications (IST), Tehran, Iran, 2012: 367–372.
[10]	Melvin M L and Davis M E. Adaptive cancellation method for geometry-induced nonstationary bistatic clutter environments[J]. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(2): 651–672. DOI: 10.1109/TAES.2007.4285360
[11]	王杰, 沈明威, 吴迪, 等. 基于主瓣杂波高效配准的机载非正侧视阵雷达STAP算法研究[J]. 雷达学报, 2014, 3(2): 235–240. DOI: 10.3724/SP.J.1300.2014.13122 Wang Jie, Shen Ming-wei, Wu Di, et al. An efficient STAP algorithm for nonsidelooking airborne radar based on mainlobe clutter compensation[J]. Journal of Radars, 2014, 3(2): 235–240. DOI: 10.3724/SP.J.1300.2014.13122
[12]	马泽强, 王希勤, 刘一民, 等. 基于稀疏恢复的空时二维自适应处理技术研究现状[J]. 雷达学报, 2014, 3(2): 217–228. DOI: 10.3724/SP.J.1300.2014.14002 Ma Ze-qiang, Wang Xi-qin, Liu Yi-min, et al. An overview on sparse recovery-based STAP[J]. Journal of Radars, 2014, 3(2): 217–228. DOI: 10.3724/SP.J.1300.2014.14002
[13]	Yang Bin. Projection approximation subspace tracking[J]. IEEE Transactions on Signal Processing, 1995, 43(1): 95–107. DOI: 10.1109/78.365290
[14]	Belkacemi H and Marcos S. Fast iterative subspace algorithms for airborne STAP radar[J]. EURASIP Journal on Applied Signal Processing, 2006, 2006: 037296.