ID 原文 译文
19995 基于微机电系统(MEMS)的惯性器件和全球定位系统(GPS)的组合导航系统在卫星信号失锁时存在误差发散的问题，该文提出一种基于人工蜂群算法(ABC)改进的径向基函数(RBF)神经网络增强改进的自适应无迹卡尔曼滤波算法(AUKF)。 In order to solve the problem of speed and position error divergence in the integrated navigation system based on MicroElectro Mechanical Systems (MEMS) inertial device and GPS system combined positioning, an improved Adaptive Unsecnted Kalman Filter (AUKF) enhanced by the Radial BasisFunction(RBF) neural network based on Artificial Bee Colony(ABC) algorithm is proposed.
19996 在GPS信号失锁的情况下利用训练好的神经网络输出预测信息来对捷联惯导系统进行误差校正。 When the GPSsignal is out of lock, the trained network outputs predictied information to perform error correction on theStrapdown Inertial Navigation System(SINS).
19997 最后通过车载半实物仿真实验验证该方法的性能。 Finally, the performance of the method is verified by vehicle-mounted semi-physical simulation experiments.
19998 实验结果表明该方法在失锁情况下对于捷联惯导系统的误差发散有较为明显的抑制效果。 The experimental results show that the proposed method has asignificant inhibitory effect on the error divergence of the strapdown inertial navigation system in the case ofloss of lock.
19999 针对复杂背景下目标容易发生漂移的问题，该文提出一种基于空间可靠性约束的目标跟踪算法。 Because of the problem that the target is prone to drift in complex background, a robust tracking algorithm based on spatial reliability constraint is proposed.
20000 首先通过预训练卷积神经网络(CNN)模型提取目标的多层深度特征，并在各层上分别训练相关滤波器，然后对得到的响应图进行加权融合。 Firstly, the pre-trained Convolutional Neural Network (CNN) model is used to extract the multi-layer deep features of the target, and the correlation filters are respectively trained on each layer to perform weighted fusion of the obtained response maps.
20001 接着通过高层特征图提取目标的可靠性区域信息，得到一个二值注意力矩阵， Then, the reliability region information of the target is extracted through the high-level feature map, a binary matrix is obtained.
20002 最后将得到的二值矩阵用于约束融合后响应图的搜索范围，范围内的最大响应值即为目标的中心位置。 Finally, the obtained binary matrix is used to constrain the search area of the response map, and the maximum response value in the area is the target position.
20003 为了处理长时遮挡问题，该文提出一种基于首帧模板信息的随机选择更新策略。 In addition, in order to deal with the long-termocclusion problem, a random selection model update strategy with the first frame template information isproposed.
20004 实验结果表明，该算法在应对相似背景干扰、遮挡、超出视野等多种场景均有良好的性能表现。 The experimental results show that the proposed algorithm has good performance in dealing with similar background interference, occlusion, and other scenes.