ROBUST ADAPTIVE BEAMFORMING BASED ON PAR- TICLE FILTER WITH NOISE UNKNOWN
ROBUST ADAPTIVE BEAMFORMING BASED ON PAR- TICLE FILTER WITH NOISE UNKNOWN
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DOI：
10.2528/pier09010302
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
Y. Li;East China;Y. Gu;Z. Shi;K. S. Chen
中科院分区：
文献类型：
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作者：
Y. Li;East China;Y. Gu;Z. Shi;K. S. Chen
自适应波束形成使用一个权重向量来最大化信干噪比，通常对估计误差和参数的不确定性很敏感，如波达方向(DOA)、方向向量和协方差矩阵。稳健波束形成试图降低这种敏感性，而样本协方差矩阵中的对角加载可以提高稳健性。提出了一种基于粒子滤波的波束形成器，通过优化样本协方差矩阵中的对角加载因子来提高波束形成器的稳健性。在该方法中，将对角线载荷水平视为一组粒子，并使用粒子群优化算法进行优化。为了在不知道噪声的情况下计算粒子的投射概率，首先推导了一个简化的代价函数。在此基础上，建立了确定斜向荷载水平的统计方法。最后，对几种常见的估计误差类型进行了仿真。结果表明，该波束形成器比其他典型的对角加载波束形成器具有更好的性能。特别是，该方法的突出优点是即使在导引矢量中的噪声和误差未知的情况下也能很好地执行。
Adaptive beamforming, which uses a weight vector to maximize the signal-to-interference-plus-noise ratio (SINR), is often sensitive to estimation error and uncertainty in the parameters, such as direction of arrival (DOA), steering vector and covariance matrix. Robust beamforming attempts to mitigate this sensitivity and diagonal loading in sample covariance matrix can improve the robustness. In this paper, beamformer based on particle fllter (PF) is proposed to improve the robustness by optimizing the diagonal loading factor in sample covariance matrix. In the proposed approach, the level of diagonal loading is regarded as a group of particles and optimized using PF. In order to compute the post probability of particles beyond the knowledge of noise, a simplifled cost function is derived flrst. Then, a statistical approach is developed to decide the level of diagonal loading. Finally, simulations with several frequently encountered types of estimation error are conducted. Results show a better performance of the proposed beamformer than other typical beamformers using diagonal loading. In particular, the prominent advantage of the proposed approach is that it can perform well even noise and error in the steering vector are unknown.