ID 原文 译文
21225 该算法考虑L型阵列，在建立相干分布式非圆信号扩展阵列模型的基础上，首先证明了L阵中两个子阵的广义方向矢量(GSV)均具有近似旋转不变特性， The L-shaped array is considered. Firstly,the extended array manifold model is established by exploiting the noncircularity of the signal, and then it is proved that there are approximate rotational invariance relationships in the Generalized Steering Vectors(GSVs) of two subarrays of the L array.
21226 然后通过阵列输出信号的互相关运算消除了额外噪声， At the same time, the extra noise can be eliminated by the cross-correlation matrix of the array output signals.
21227 最终利用子阵GSV的近似旋转不变关系通过传播算子方法得到中心方位角与俯仰角估计。 Finally, on the basis of the approximate rotational invariance relationships of the sub-arrays, the center azimuth and elevation DOAs can be obtained by propagator method.
21228 理论分析和仿真实验表明，所提算法无须谱峰搜索和协方差矩阵特征分解运算，具有较低的计算复杂度，并且能够实现2维DOA估计的自动匹配； Theoretical analysis and simulation experiments show that without the spectrum searching and eigenvaluedecomposition of the sample covariance matrix, the proposed algorithm has low computational complexity.Moreover, it can automatically pair the estimated central azimuth and central elevation DOAs.
21229 同时，相比于现有的相干分布式非圆信号传播算子算法，所提算法以较小的复杂度代价获得了性能的较大提升。 In addition,compared with the existing propagation method for coherently distributed noncircular sources, the proposedalgorithm can achieve higher estimation accuracy with the small complexity cost.
21230 在室内覆盖的大量的WiFi信号可以用来室内定位。尽管很多WiFi室内定位技术被提出，但其定位精度仍然未达到实际应用的需求。 There are a large number of indoor WiFi signals which can be used for indoor positioning. Although many WiFi indoor positioning technology is proposed, it's positioning accuracy still does not meet the actual application requirements.
21231 针对这个问题，该文提出一种自适应仿射传播聚类(AAPC)算法用以提高WiFi指纹的聚类质量，从而提高定位精度。 For this problem, an Adaptive Affinity Propagation Clustering (AAPC) algorithm isproposed to improve the clustering quality of WiFi fingerprint, thus improving the positioning accuracy.
21232 AAPC算法通过动态调整参数生成不同的聚类结果，然后采用聚类有效性指标筛选出其中最佳的。 TheAAPC algorithm generates different clustering results by dynamically adjusting parameters, then clustervalidity indices are used to select the best ones.
21233 采集大量真实环境数据进行试验，试验结果表明采用AAPC算法产生的聚类结果具有更高的定位精度。 A large number of real environmental data are collected andtested. The experimental results show that the clustering results generated by AAPC algorithm have higherpositioning accuracy.
21234 该文针对低信噪比噪声环境下的声音事件检测问题，提出基于多频带能量分布图离散余弦变换的声音事件检测的方法。 As to the problem of sound event detection in low Signal-Noise-Ratio (SNR) noise environments, a method is proposed based on discrete cosine transform coefficients extracted from multi-band power distribution image.