实验室王咸鹏教授在SCI期刊《IEEE Transactions on Vehicular Technology》（工程技术2区，IF=5.339）发表文章。

Professor Wang Xianpeng from the MRU published a paper in the SCI journal IEEE Transactions on Vehicular Technology (Engineering and Technology Ranking Q 2, IF=5.339).

本文着眼于智能交通系统中的通信系统的信道估计问题，主要对虚拟MIMO通信系统中圆形和非圆形信号的低复杂度信道估计进行了研究。在智能交通系统（ITS）中，基站（BS）与车辆之间的通信可以形成虚拟的多输入多输出（VMIMO）通信系统。而对于VMIMO通信系统来说，DOA和极化估计至关重要。如图1所示，针对智能天线（SA）中的虚拟MIMO系统信道估计问题，文章首先基于四元数理论提出了一种新的四元数非圆形MUSIC算法（QNC-MUSIC），以解决圆形和非圆形信号共存情况下的波达方向（DOA）估计问题。然后，通过使用频谱函数相对于非圆形相位的偏导数来对参数搜索进行降维处理。基于此，进一步提出了一种新型的降维非圆信号MUSIC（DRNC-MUSIC）算法，该算法具有较低的计算复杂度，可用于同时实现圆形信号和非圆形信号的DOA和极化估计。

The paper focuses on the communications channel estimation of intelligent transportation system, mainly studying the low-complexity channel estimation of circular and non-circular signals in virtual MIMO communications systems. In the intelligent transportation systems (ITS), the communication between base stations (BS) and vehicles can form a VMIMO communication system. And for the VMIMO communication systems, DOA and polarization estimation are crucial. As shown in Fig. 1, for the channel estimation problem of VMIMO system in SA, the paper firstly proposes a new quaternion non-circular MUSIC (QNC-MUSIC) algorithm based on quaternion theory to solve the problem of DOA estimation in the case of coexistence of circular and non-circular signals. Then, the parameter search is downscaled by using the partial derivatives of the spectral function with respect to the non-circular phase. Then a novel DRNC-MUSIC algorithm with low computational complexity is further proposed for the simultaneous implementation of DOA and polarization estimation of circular and non-circular signals.

图1智能天线(SA)系统

另一方面，基于DOA估计和信道估计的特点，文章同研究了利用DOA估计和信道估计实现辅助定位的方法。基于构造的VMIMO通信系统，还提出了一种两级辅助车辆定位方法。在实际应用中，视线（LOS）路径的信号强度比NLOS路径要强得多；因此，LOS路径可以很容易地与NLOS路径进行区分。首先基于简单的TOA技术，粗略地对车辆与BS之间的距离进行测量，即对LOS路径进行测量。如图2所示，通过利用三个不同的BS获得三个距离后，利用所提出的DOA估计算法利用三个BS对测量的移动终端进行高精度的DOA估计，从而精确定位目标，最终通过三角测量确定移动终端的位置。利用极化参数估计则可以进一步区分不同的移动终端,相关成果可用于陆地或海上运载器间的相互定位。

The paper investigates the method of using DOA estimation and channel estimation to assist localization based on their characteristics. And according to the constructed VMIMO communication system, a two-level assisted vehicle localization method is also proposed. In practice, the signal strength of the LOS path is much stronger than that of the NLOS path, which can make it easy to distinguish the LOS path from the NLOS path. Firstly, the distance between the vehicle and the BS which is also called the LOS path is measured roughly based on a simple TOA technique. Secondly, as shown in Fig. 2, after obtaining three distances by using three different BSs, the DOA estimation algorithm is used to perform high-precision DOA estimation of the measured mobile terminal so as to precisely locate the target. Finally, the location of the mobile terminal is determined by triangulation. The polarization parameter estimation can further distinguish different mobile terminals, and the related results can be used for mutual positioning between land or sea carriers.

图2三个基站对两个移动终端的定位场景示例