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| 1 | 线性电磁矢量阵列的空时极化平滑算法及相干源多参数估计显示文摘该文提出了一种基于线性电磁矢量阵列的空时极化平滑算法(STPSA),解决了相干信源的频率,2维波达方向和极化参数的联合估计问题。该算法通过对不同子阵和矢量传感器不同传感单元的测量数据及其相应延迟数据进行平滑,实现解相干预处理并抑制噪声干扰,然后利用传播算子方法得到相应的参数估计。与目前的算法相比,该文提出的算法能够同时实现相干信源的多个参数联合估计;无需通过奇异值或特征值分解提取信号/噪声子空间,也无须进行参数搜索,有较低的运算量;另外,算法能够通过增加相邻阵元的间隔来扩展阵列的有效孔径,改善估计性能,且无须进行参数去模糊处理。仿真结果验证了算法的有效性。 | 刘兆霆 何劲 刘中 | 2010 | 电子与信息学报2010，32，12： | 5 |
| 2 | Numerically stable method of signal subspace estimation based on multistage Wiener filter显示文摘In this paper,a numerically stable method of signal subspace estimation based on Householder multistage Wiener filter(HMSWF) is proposed.Numerical stability of the method lies on the fact that the Householder matrix in HMSWF ensures the unitary blocking operation and significantly strengthens the orthogonality of basis vectors,especially in the finite-precision implementation.In the following,we analyze the numerical stability of HMSWF and MSWF based on the correlation subtractive structure(CSS-MSWF) by establishing the equivalence between the forward recursion of MSWF and the Arnoldi algorithm in numerical linear algebra.Besides,the equivalence between HMSWF and the Householder QR decomposition(QRD) on the Krylov matrix underlying in MSWF is directly established.Based on the relationship,two theoretical upper bounds of the orthogonality error of basis vectors in signal subspace are obtained and it is demonstrated that the orthogonality of basis vectors based on HMSWF is perfectly preserved by the numerically well-behaved Householder matrix,and the corresponding signal subspace estimation is much more numerically stable than that based on CSS-MSWF.Simulations show the numerical stability of the proposed method of signal subspace estimation by HMSWF. | ZHUANG XueBin CUI XiaoWei LU MingQuan FENG ZhenMing | 2010 | Science China(Information Sciences)2010，53，12： | 4 |
| 3 | 稀疏均匀非同心电磁矢量阵列的2D-DOA与极化联合估计显示文摘本文提出了一种稀疏均匀非同心电磁矢量传感器矩形阵列,针对该阵列提出了一种二维波达方向(2D-DOA)和极化参数的联合估计算法.首先利用稀疏均匀矩形阵列的旋转不变性得到周期性模糊的2D-DOA估计,然后提出一种简易的非同心电磁矢量传感器的2D-DOA估计算法来解模糊,再通过一些三角变换得到高精度无模糊的2D-DOA和极化参数估计,最后推导了该阵列多参量估计的闭式克拉美罗界.本文所提阵列的稀疏配置使得在不增加阵元数和硬件复杂度情况下有效扩展了阵列物理孔径,且由于矢量传感器的使用获得了极化分集,使得2D-DOA的估计精度大大增加.此外本文方法能得到2D-DOA和极化参数之间的自动配对,更为重要的是该阵列使用非同心电磁矢量传感器构成,解决了同心电磁矢量传感器互耦严重、硬件设计困难的问题.仿真结果证明了本文多参量估计算法的有效性. | 郑桂妹 陈伯孝 杨明磊 郭维娜 | 2014 | 中国科学:信息科学2014，44，9： | 2 |
| 4 | Cramér-Rao bound for multiple parameters estimation using a polarization sensitive array显示文摘In this paper, new Cramér-Rao lower bounds (CRB) of the estimates of frequencies, two-dimensional arrival angles and polarization parameters of multiple incident signals are derived for a polarization sensitive array. The incident sources have distinct carrier-frequencies, in contrast to the modeling of all sources to be at the same known carrier-frequency, which has been investigated in the existing research literature on the Cramér-Rao bounds (CRB) for polarization sensitive direction finding. The derived CRBs are compact closed-form expressions and applicable to an arbitrary array geometry. Numerical examples and analysis of some special cases provide insights into the fact that the estimation accuracy of all parameters is enhanced with the increasing signal-to-noise ratio (SNR) and number of snapshots. In addition, they are hardly influenced by the sampling frequency and independent of the initial phase of incident sources. These insights offer guidelines to the system engineer on how to improve parameters' estimation accuracy. | ZHENG Gui-mei CHEN Bai-xiao YANG Ming-lei | 2012 | The Journal of China Universities of Posts and Telecommunications2012，19，3： | 0 |
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