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一种面向稀疏场景视觉匹配应急定位方法
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TP391.4

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陕西省自然科学基础研究计划(2023-JC-QN-0720)


An Emergency Positioning Method Using Visual Matching Technology for Sparse Scenarios
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    摘要:

    针对卫星导航易受干扰、惯导依赖控制点以及传统交会测量方法效率低难以满足应急需求的问题,同时为解决传统视觉匹配方法在深山、戈壁等特征稀疏场景中受光照与角度影响大、鲁棒性差的缺陷,提出一种适用于特征稀疏场景的应急定位方法。首先通过语义分割模型提取山脊轮廓线,经边缘提取与特征点抽稀预处理,解决特征稀疏场景下有效信息不足的问题;随后将图像匹配转化为特征点匹配,结合车载运动约束与远距离拍摄约束,构建融合“局部+全局”空间上下文的描述子以实现工程级旋转鲁棒性,同时引入稳定参考点构建全局描述子,通过相对位置向量缓解局部结构相似导致的匹配歧义;最终基于对极几何原理求解基础矩阵与本质矩阵,结合 PnP 算法、三角测量及光束法平差(BA)优化相机位姿,推算精确地理坐标。在秦岭山区与定边周湾镇等特征稀疏场景的实验表明:所提方法平均定位精度达 2.5~2.8 m,较经典方法提升约 2~3 m;虽计算时间略长于其他经典方法,但仍维持秒级响应,较传统交会测量效率大幅提升。方法在精度与效率间实现最佳平衡,适用于中远距离山脊线主导且无剧烈视角旋转的公路应急定位等场景,具备显著的工程应用推广价值。

    Abstract:

    Being aimed at the problems that satellite navigation is vulnerable to interference,inertial navigation relies on control points,and traditional intersection measurement methods are inefficient and are difficult to meet the emergency needs,simultaneously,traditional visual matching methods are deeply affected by illumination and viewing angles,and robustness is poor at feature-sparse scenes of deep mountains and gobi deserts,this paper proposes an emergency positioning method suitable for featuresparse scenes.First,the method is to extract ridge contours by a semantic segmentation model,and perform preprocessing including edge extraction and feature point down-sampling to solve the problem ofinsufficient discriminative information in feature-sparse scenes.And then,image matching is converted into feature point matching.In combination of in-vehicle motion constraints with long-distance imaging constraints,a descriptor integrating“local + global”spatial contexts is constructed to achieve rotation-invariant properties.At the same time,stable anchor points are introduced to build a global descriptor,and matching ambiguities caused by locally similar structures are mitigated through relative displacement vectors.Finally,based on polar geometry,the fundamental matrix and essential matrix are solved.In combination of the Perspective-n-Point (PnP) algorithm with triangulation and bundle adjustment (BA),the camera pose is optimized to derive geodetic coordinates.The experiments in feature-sparse scenes such as the Qinling Mountains and Zhouwan Town,Dingbian County demonstrate that the average positioning accuracy reaches 2.5~2.8 meters by the method,surpassing classical methods by 2~3 meters.Thoughcomputation time is moderately longer than that of the other classical methods,the method still maintains real-time capability (second-level response).The measurement efficiency is higher than that of the traditional intersection.This method achieves an optimal accuracy-efficiency balance for highway emergency positioning in mid-to-long-range ridge-dominated scenes without severe perspective rotation,exhibiting substantial engineering applicability.

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胡 俊,王 崴,张熙亚,瞿 珏,王庆力.一种面向稀疏场景视觉匹配应急定位方法[J].空军工程大学学报,2026,27(2):101-109

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  • 在线发布日期: 2026-04-27
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