ID 原文 译文
14075 首先,针对不同侦察任务需求,构建传感器探测、有效持续侦察时间、复杂多边形障碍等数学模型。 Firstly‚several models of sensor detection‚duration time of effective reconnaissance and complex polygonal obstacles are formulated respectively for different reconnaissance missions.
14076 随后,综合考虑持续侦察时间和障碍规避约束,提出了一种面向复杂障碍环境的多机协同侦察规划分层求解方法,通过分层细化有效降低多机协同侦察问题的求解复杂度。 Secondly‚a two-stage framework for mission planning of multi-UAV cooperative reconnaissance in complex environment with polygonal obstacles is established by comprehensively considering the constraints of reconnaissance duration time and obstacle avoidance. The two-stage solution effectively reduces the complexity of solving the cooperative reconnaissance problem.
14077 最后,考虑无人机运动学约束,提出了一种基于贪心策略的启发式路径规划算法,能够在规避障碍物的同时获得尽可能短的可行路径。 Finally‚considering the UAV kinematic constraint‚a heuristic path planning algorithm based on the greedy strategy is designed‚which can obtain a flying path that is as short as possible while avoiding the polygonal obstacles at the same time.
14078 仿真结果证明了提出算法的有效性。 The simulation results demonstrate the effectiveness of the proposed algorithm.
14079 针对遥感船舶检测任务场景中与海面颜色相似船舶显著值低以及海岸线、岛屿等背景干扰问题,提出一种基于显著性候选区域的遥感船舶检测算法。 In order to solve the problems of low saliency value of the ships whose color are similar to sea surface color‚and background interference such as coastlines and islands‚a remote sensing ship detection algorithm based on ship saliency in candidate regions is proposed.
14080 首先,该算法采用脉冲耦合神经网络将根据改进频率调谐显著性检测与Hessian矩阵边缘检测得到的两种显著图相融合得到总显著图,以提高与海面背景颜色相近船舶的显著值,从而提取有效的船舶候选区域切片。 The improved Frequency Tuning(FT) saliency detection and edge detection of Hessian matrix are used to obtain two types of saliency maps‚which are then fused by using Pulse Coupled Neural Network(PCNN) to obtain the comprehensive saliency map‚so as to improve the saliency value of the ships whose color are similar to the color of sea surface background‚thus extracting effective ship slices of candidate regions.
14081 然后,利用迁移VGG16网络提取数据集特征训练SoftMax分类器,以鉴别该候选区域切片,分离候选区域中可能存在的背景干扰,从而实现船舶目标检测。 Then‚the migration VGG16 network is used to extract the features of the dataset and train SoftMax classifier‚so as to identify the slices of the candidate region and separate the possible background interference in the candidate region‚thus realizing ship target detection.
14082 试验结果表明,所提算法具有良好的准确性。 The experimental results show that the proposed algorithm has good accuracy.
14083 针对遥感光学图像和SAR图像在配准过程中存在正确匹配点较少、配准精度低的问题,提出一种结合P-M滤波及改进LSS的光学和SAR图像配准算法。 To solve the problem of few correct matching points and low registration accuracy in the registration process of optical remote-sensing images and SAR images‚an optical and SAR image registration algorithm combining Perona-Malik(P-M) filtering with the improved Local Self Similarity(LSS) is proposed.
14084 首先,利用各向异性方程扩散性滤除SAR图像的斑点噪声。 Firstly‚the anisotropic diffusion equation is used to filter the speckle noise in the SAR image.