基于图像配准的无人机目标精确定位算法

为了满足“察打一体化”无人机精确打击目标的要求, 针对现有目标定位算法的准确率低、实时性差的特点, 本文提出了一种基于图像配准的无人机目标精确定位算法。该算法主要分为两个阶段: 特征点检测阶段和目标精确定位阶段。首先采用基于侧抑制竞争的特征点检测算法, 实现局部图像中目标特征点的检测工作; 然后利用图像局部信息的配准算法, 完成目标所处的局部区域图像的精确配准工作, 最终实现了目标的高精度定位。实验结果显示该算法的定位精度可以达到 0.21 m, 能够满足精确作战时的目标情报保障需求。

Abstract

In order to meet the needs of the integrated reconnaissance/strike UAV precision attack, and to overcome low accuracy and worse real-time performance of these existing target localization algorithms, this paper proposes a UAV accurate positioning algorithm based on image registration, which consists of two parts: feature point detection and target accurate positioning. First, the feature point detection algo-rithm based on lateral inhibition competition is used to detect the local image feature points; and then the image registration algorithm of local information is applied to complete the work of local image precise registration, ultimately achieving the goal of high-precision positioning of the targets. The experiments show that the positioning accuracy of this algorithm can reach 0.21 m, which can meet the target informa-tion security needs during combat.

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