Multi-UAV Cooperative Localization for Marine Targets Based on Weighted Subspace Fitting in SAGIN Environment
Multi-UAV Cooperative Localization for Marine Targets Based on Weighted Subspace Fitting in SAGIN Environment
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DOI：
10.1109/jiot.2021.3066504
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发表时间：
2022-04-15
影响因子：
10.6
通讯作者：
Wang, Huafei
中科院分区：
文献类型：
--
作者：
Wang, Xianpeng;Yang, Laurence T.;Wang, Huafei
无人机作为车联网(IoV)的重要组成部分，可以在天空地一体化网络(SAGIN)环境中进行目标定位和导航。海上目标定位对船舶安全航行、水文调查和海洋资源勘探具有重要意义。传统的定位方法大多是利用卫星在沙金环境中对海洋目标进行定位，定位精度已不能满足现代海洋观测任务的要求。为了实现海上目标的定位，本文提出了一种无人机与单基地多输入多输出(MIMO)雷达相结合的系统结构。其主要目的是利用多输入多输出雷达进行波达方向估计。在此，我们考虑了未知相互耦合的一般情况，并提出了一种新的稀疏重建算法。利用互耦合矩阵(MCM)的特殊结构，将数据模型表示为稀疏表示形式。然后构造了两个新的矩阵，一个加权矩阵和一个降维矩阵，分别降低了计算复杂度和提高了稀疏性。然后，利用最优权重子空间拟合(WSF)的概念构建了稀疏约束模型。最后，通过重构块稀疏矩阵的支持度，实现对海上目标的DOA估计。基于波达方向估计结果，利用多架无人机多次交叉定位海上目标，在沙金环境下实现了海上目标的精确定位。数值结果表明，所提出的波达方向估计器是有效的，多无人机协同定位系统能够实现精确的目标定位。
As an indispensable part of the Internet of Vehicles (IoV), unmanned aerial vehicles (UAVs) can be deployed for target positioning and navigation in the space-air-ground-integrated network (SAGIN) environment. Maritime target positioning is very important for the safe navigation of ships, hydrographic surveys, and marine resource exploration. Traditional methods typically exploit satellites to locate marine targets in the SAGIN environment, and the location accuracy does not satisfy the requirements of modern ocean observation missions. In order to localize the marine target, we develop a system architecture in this article, which contains UAVs integrated with monostatic multiple-input-multiple-output (MIMO) radars. The main thrust is to estimate the direction-of-arrival (DOA) via MIMO radar. Herein, we consider a general scenario that unknown mutual coupling exist and a novel sparse reconstruction algorithm is proposed. The mutual coupling matrix (MCM) is adopted with the help of its special structure, we formulate the data model as a sparse representation form. Then, two novel matrices, a weighted matrix, and a reduced-dimensional matrix are constructed to reduce the computational complexity and enhance the sparsity, respectively. Thereafter, a sparse constraint model is constructed using the concept of optimal weighted subspace fitting (WSF). Finally, the DOA estimation of maritime targets can be achieved by reconstructing the support of a block sparse matrix. Based on the DOA estimation results, multiple UAVs are used to cross-locate marine targets multiple times, and an accurate marine target position is achieved in the SAGIN environment. Numerical results are carried out, which demonstrates the effectiveness of the proposed DOA estimator, and the multi-UAV cooperative localization system can realize accurate target localization.