| ID | 原文 | 译文 |
| 54097 | 结果显示LMCF-Staple算法的跟踪稳定性有一定提高，目标的漂移情况明显减少，并且其跟踪的精确度、成功率均优于目前主流的几种算法。 | The results show that the tracking stability of the LMCF-Staple algorithm is greatly improved, the target drift is significantly reduced, and its tracking accuracy and success rate are better than the current mainstream algorithms. |
| 54098 | 合成孔径雷达(Synthetic Aperture Radar，SAR)对地观测具有覆盖面积广、多极化、多分辨率、全天时全天候观测的特点，被广泛应用于智能化监测系统。 | Synthetic aperture radar for earth observation has the characters of wide coverage, multi-polarization, multi-resolution, all time and all weather, which have been widely used in intelligent monitoring systems. |
| 54099 | 随着SAR遥感图像分辨率的提升，目标型谱级识别成为了一项挑战。 | With the improvement of SAR remote sensing image resolution, the fine-grained target classification becomes a challenge task. |
| 54100 | 本文使用聚束成像模式下10种型号车辆的0. 3 m分辨率、HH极化、多方位角的观测数据，针对型号类间差异小而导致的传统分类算法性能较差的问题，提出了多尺度特征提取残差结构，并结合高阶特征表示提升了深度卷积网络的分类性能，实现了高精度的SAR遥感图像车辆型谱级识别。 | In this paper, we use the observation data of 10 types of vehicles with 0. 3 m resolution, HH polarization, and multi-azimuth angle under spotlight imaging mode, aiming at traditional classifiers' feature generalization ability limited by low intra-class variance problem for fine-grained vehicle type recognition of SAR remote sensing images, the multi-scale residual convolution neural network with high order feature representation is proposed, which can improve the feature extraction ability corresponding to remote sensing scenes and enhance accurate and robustness of vehicle recognition. |
| 54101 | 所提出的方法在公开的MSTAR数据集上开展了详细的实验验证，结果表明本文提出的方法优于现有的智能化分类算法，对10种型号车辆目标识别的总体精度(Overall Accuracy，OA)达到了99. 88%。 | Extensive experiments carried on MSTAR dataset show that proposed method performs the remarkable result comparing with the state-of-the-art intelligence classification methods, whose OA(Overall Accuracy) can reach 99. 88% for vehicle recognition over 10 classes. |
| 54102 | 窄带干扰(Narrowband Interference，NBI)，作为一种敌意的频域干扰，会严重地恶化最小频移键控(Minimum Shift Keying，MSK)非相干检测的误码率(Bit Error Rate，BER)性能。 | Narrowband interference(NBI), as kind of hostile frequency-domain interference, can seriously impair the bit error rate(BER) performance of minimum shift keying(MSK) noncoherent detection. |
| 54103 | 为降低窄带干扰对BER性能的影响，MSK非相干接收机一般首先对接收信号进行干扰抑制。 | To reduce the impact of narrowband interference on BER performance, MSK noncoherent receivers generally first perform interference suppression on received signals. |
| 54104 | 然而现有MSK非相干检测算法并未考虑干扰抑制对MSK信号造成的畸变，这制约了窄带干扰下非相干检测的MSK通信系统的BER性能。 | However, existing MSK noncoherent detection algorithms do not consider the distortion of MSK signals caused by interference suppression, which limits the BER performance of the MSK communication system with noncoherent detection under narrowband interference. |
| 54105 | 为了解决这个问题，本文提出了一种基于深度学习的MSK非相干接收机(Deep Learning-Based MSK Noncoherent Receiver，DL-MSKNCR)。 | In order to solve this problem, a deep learning-based MSK noncoherent receiver(DL-MSKNCR) is proposed in this paper. |
| 54106 | 该接收机包含一个干扰抑制子网络和一个MSK非相干检测子网络。 | This receiver contains an interference suppression subnetwork and an MSK noncoherent detection subnetwork. |