Highly Robust Adaptive Beamforming Algorithm in Satellite Communications
-
摘要:
在卫星通信中，采用自适应波束赋形技术能极大提升导航接收机的抗干扰性能，然而，传统自适应波束赋形算法对模型失配极为敏感. 针对传统自适应波束赋形算法在期望信号导向矢量和协方差矩阵失配时，输出性能急剧下降的问题，本文提出了一种高鲁棒性自适应波束赋形算法. 该算法首先估计期望信号的输入信噪比（SNR），再根据SNR构造投影矩阵来估计期望信号导向矢量和干扰信号导向矢量；接着，基于不确定集优化方法再次校正期望信号导向矢量和干扰信号导向矢量；最后，估计信号功率并重构干扰加噪声协方差矩阵. 仿真结果表明，相比于协方差矩阵重构波束赋形算法，本文算法具有更优异的输出信干噪比（SINR）性能，当SNR为10.0 dB并存在期望信号波达方向（DOA）估计失配时，本文算法的输出SINR增益可达1.9 dB；当存在波前扰动失真时，输出SINR增益约1.5 dB；当存在局部相干散射时，输出SINR增益约1.6 dB.
Abstract:In satellite communications, leveraging adaptive beamforming technology can significantly improve the anti-jamming ability of navigation receivers. However, conventional adaptive beamforming algorithms are sensitive to model mismatch. In order to overcome the performance degradation of conventional adaptive beamforming algorithms arising from both the steering vector mismatch of the desired signal and the covariance matrix mismatch, a new robust adaptive beamforming algorithm is proposed. Firstly, the signal-to-noise ratio (SNR) of the desired signal is estimated. Then, the projection matrix is constructed with the estimated SNR to further predict the steering vectors of the desired signal and those of the interferences. Next, the steering vectors of the desired signal and the interferences are corrected by using the uncertainty-set optimization method. Finally, the signal power is estimated and the interference-plus-noise covariance matrix is reconstructed. The simulation results show that, compared with the beamforming algorithm that requires covariance matrix reconstruction, the proposed algorithm achieves a better output signal to interference and noise ratio (SINR) performance. When SNR is 10.0 dB and signal direction of arrival (DOA) mismatch occurs, the output SINR gain is about 1.9 dB; when wavefront distortion arises, the output SINR gain is about 1.5 dB; when coherent local scattering happens, the output SINR gain is about 1.6 dB.
-
图 2 存在信号DOA估计误差时各算法的输出性能
Figure 2. Output performances of algorithms with signal DOA mismatch
图 3 存在波前扰动失真时各算法输出性能
Figure 3. Output performances of algorithms with wavefront distortion
图 4 存在局部相干散射时各算法输出性能
Figure 4. Output performances of algorithms with coherent local scattering
-
[1] 卢丹. 稳健的全球卫星导航系统抗干扰技术研究[D]. 西安: 西安电子科技大学,2013. [2] 朱亮. 北斗卫星导航系统干扰识别与测向技术的研究与实现[D]. 北京: 北京交通大学,2019. [3] 刘江波. 稳健的收/发波束形成方法研究[D]. 成都: 电子科技大学,2018. [4] 黄磊. 非理想条件下的自适应波束形成算法研究[D]. 合肥: 中国科学技术大学,2016. [5] COX H, ZESKIND R, OWEN M. Robust adaptive beamforming[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1987, 35(10): 1365-1376. doi: 10.1109/TASSP.1987.1165054 [6] FELDMAN D D, GRIFFITHS L J. A projection approach for robust adaptive beamforming[J]. IEEE Transactions on Signal Processing, 1994, 42(4): 867-876. doi: 10.1109/78.285650 [7] LI J, STOICA P, WANG Z. Doubly constrained robust Capon beamformer[C]//The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers. Pacific Grove: IEEE, 2004: 1335-1339. [8] JIAN L, STOICA P, WANG Z S. On robust Capon beamforming and diagonal loading[J]. IEEE Transactions on Signal Processing, 2003, 51(7): 1702-1715. doi: 10.1109/TSP.2003.812831 [9] GU Y J, LESHEM A. Robust adaptive beamforming based on interference covariance matrix reconstruction and steering vector estimation[J]. IEEE Transactions on Signal Processing, 2012, 60(7): 3881-3885. doi: 10.1109/TSP.2012.2194289 [10] HUANG L, ZHANG J, XU X, et al. Robust adaptive beamforming with a novel interference-plus-noise covariance matrix reconstruction method[J]. IEEE Transactions on Signal Processing, 2015, 63(7): 1643-1650. doi: 10.1109/TSP.2015.2396002 [11] HUANG Y W, ZHOU M K, VOROBYOV S A. New designs on MVDR robust adaptive beamforming based on optimal steering vector estimation[J]. IEEE Transactions on Signal Processing, 2019, 67(14): 3624-3638. doi: 10.1109/TSP.2019.2918997 [12] 毛晓军. 高性能阵列天线稳健自适应波束形成技术研究[D]. 哈尔滨: 哈尔滨工程大学,2017. [13] SHEN F, CHEN F F, SONG J Y. Robust adaptive beamforming based on steering vector estimation and covariance matrix reconstruction[J]. IEEE Communications Letters, 2015, 19(9): 1636-1639. doi: 10.1109/LCOMM.2015.2455503 [14] 毛英. 北斗空时自适应抗干扰子空间投影方法研究[D]. 哈尔滨: 哈尔滨工程大学,2017. [15] ZHENG Z, ZHENG Y, WANG W Q, et al. Covariance matrix reconstruction with interference steering vector and power estimation for robust adaptive beamforming[J]. IEEE Transactions on Vehicular Technology, 2018, 67(9): 8495-8503. doi: 10.1109/TVT.2018.2849646 [16] ZHOU C W, GU Y J, HE S B, et al. A robust and efficient algorithm for coprime array adaptive beamforming[J]. IEEE Transactions on Vehicular Technology, 2018, 67(2): 1099-1112. doi: 10.1109/TVT.2017.2704610 [17] 鲁郁. 北斗/GPS双模软件接收机原理与实现技术[M]. 北京: 电子工业出版社,2016:82-85. [18] KHABBAZIBASMENJ A, VOROBYOV S A, HASSANIEN A. Robust adaptive beamforming based on steering vector estimation with as little as possible prior information[J]. IEEE Transactions on Signal Processing, 2012, 60(6): 2974-2987. doi: 10.1109/TSP.2012.2189389 -
下载:
点击查看大图
计量
- 文章访问数: 515
- HTML全文浏览量: 141
- PDF下载量: 32
- 被引次数: 0