ID 原文 译文
22515 计算结果表明，对流层散射双向时间比对中对流层斜延迟呈现出随比对距离增大而增大，随入射角增大而减小的特性，并且四季变化特性也比较明显。 The results show that the tropospheric slant delay in two-way troposphere time transfer increases with the increase of the distance, and decreases with the increase of the angle, and the variation characteristics of the four seasons are obvious.
22516 3 个比对站的对流层散射斜延迟10~35 m 之间，经比对抵消 90%后的时间延迟为 3.5~11.8 ns。 The tropospheric delay of the three stations is between 10~35 m, and the time delay after subtracting 90% is 3.5~11.8 ns.
22517 在数据融合系统中，传感器自身系统误差造成其上报融合中心的目标位置状态出现系统性偏差，若得不到有效估计与补偿，融合系统难以实现预期的性能优势。 In the data fusion system, sensor biases lead to systematic deviation of the position states of targets reported to the fusion center. If sensor biases could not be estimated and compensated correctly, the fusion system will fail to achieve the expected performance superiority.
22518 然而，基于目标关联配对关系而构造的超定方程组是系统误差估计的出发点。 However, the starting point of sensor bias estimation is the overdetermined equations construted on the biasis of data association.
22519 复杂环境下，受随机噪声、系统误差、虚警、漏报等因素的干扰，数据关联模块的输出结果常常包含错误关联。 In the complicated environment, with the presence of interference factors such as random errors, sensor biases, false alarms and missed detections, the data association module outputs some misassociations inevitably.
22520 针对非理想关联下多传感器系统误差的稳健估计问题，该文提出基于最小截平方的系统误差稳健估计方法，并进一步提出剔除异常方程的重加权最小二乘方法。 In view of the multisensor bias estimation problem under nonideal association, the robust estimation approach based on the least trimmed squares is proposed. Furthermore, the reweighted least squares apporach through eliminating abnormal equations is presented.
22521 与最小二乘及最小中值平方相比，所提方法在保证估计器稳健性能的前提下，降低了估计结果对随机噪声的敏感程度。 Compared with the least squares and the least median of squares, the proposed approaches can not only ensure the robust performance on bias estimation, but also are less sensitive to random errors.
22522 仿真实验验证了所提方法的有效性。 Simulation results verify the effectiveness of the proposed methods.
22523 针对目标和杂波先验知识不准确时认知雷达的检测波形设计问题，同时兼顾功率放大器对低峰均比(PAR)波形的需求，该文提出一种信号相关杂波背景下认知雷达低 PAR 稳健波形设计方法。 In view of the detection waveform design for cognitive radar with imprecise prior knowledge of target and clutter, while considering the demand of power amplifier on low Peak-to-Average power Ratio (PAR) waveform, a low-PAR robust waveform design method in presence of signal-dependent clutter is proposed.
22524 首先，在目标和杂波不确定集范围内，基于极大极小化准则构造关于输出信干噪比(SINR)的优化模型； Firstly, the optimization model of radar's output Signal-to-Interference-plus-Noise Ratio (SINR) is established within the uncertainty of target and clutter via Max-Min method.