In this paper, we have proposed a new strategy of using the landmark anchor node instead of a radio-based anchor node to obtain the virtual coordinates (landmarkID, DISTANCE) of moving troops or defense forces that will help in tracking and maneuvering the troops along a safe path within a GPS-denied battlefield environment. The proposed strategy implements landmark recognition using the Yolov5 model and landmark distance estimation using an efficient Stereo Matching Algorithm. We consider that a moving node carrying a low-power mobile device facilitated with a calibrated stereo vision camera that captures stereo images of a scene containing landmarks within the battlefield region whose locations are stored in an offline server residing within the device itself. We created a custom landmark image dataset called MSTLandmarkv1 with 34 landmark classes and another landmark stereo dataset of those 34 landmark instances called MSTLandmarkStereov1. We trained the YOLOv5 model with MSTLandmarkv1 dataset and achieved 0.95 mAP @ 0.5 IoU and 0.767 mAP @ [0.5: 0.95] IoU. We calculated the distance from a node to the landmark utilizing the bounding box coordinates and the depth map generated by the improved SGM algorithm using MSTLandmarkStereov1. The tuple of landmark IDs obtained from the detection result and the distances calculated by the SGM algorithm are stored as the virtual coordinates of a node. In future work, we will use these virtual coordinates to obtain the location of a node using an efficient trilateration algorithm and optimize the node position using the appropriate optimization method.

翻译：本文提出了一种新策略，在无GPS战场环境中，利用地标锚节点替代基于无线电的锚节点，获取移动部队或防御部队的虚拟坐标（地标ID, 距离），以辅助部队沿安全路径跟踪与机动。该策略采用YOLOv5模型实现地标识别，并通过高效立体匹配算法估计地标距离。我们假设移动节点搭载低功耗移动设备，配备已校准的立体视觉摄像头，可捕获战场区域内地标的立体图像，而这些地标的位置信息预先存储于设备本地的离线服务器中。我们构建了包含34个地标类别的专用地标图像数据集MSTLandmarkv1，以及基于这34个地标实例的立体数据集MSTLandmarkStereov1。使用MSTLandmarkv1数据集训练YOLOv5模型后，在0.5 IoU阈值下达到0.95 mAP，在[0.5: 0.95] IoU范围内达到0.767 mAP。基于MSTLandmarkStereov1数据集，利用改进的SGM算法生成的深度图及边界框坐标，计算节点到地标的距离。检测结果中的地标ID序列与SGM算法计算的距离值共同存储为节点的虚拟坐标。未来工作中，我们将利用这些虚拟坐标，通过高效三边定位算法获取节点位置，并采用适当优化方法进行位置优化。