ID 原文 译文
38976 理论性能分析表明在噪声较小时，所提算法能够达到克拉美罗下界，且相比于现有定位算法具有更高的定位精度和定位稳健性。 Theoretical analysis showed that the proposed method can reach Cramer-Rao lower bound(CRLB) when the noise is weak, and has higher location accuracy and robustness than the existing localization methods.
38977 仿真结果验证了所提算法具有更好的定位性能。 Simulation results showed that the proposed method has better performance.
38978 传统语音端点检测方法利用语音和噪声在某单一参数特征上的差异进行信号中语音起止点的切分，但不同参数在低信噪比不同噪声环境下表现不稳定，鲁棒性差。 Traditional speech endpoint detection methods make use of the difference between speech and noise in a single parameter to segment the start and end points of speech in the signal. However, the performance of different parameters under different noise environments with low signal-to-noise ratio is unstable and the robustness is poor.
38979 因此，本文提出了基于均匀子带谱方差，能熵比，梅尔倒谱距离，似然比四种参数相融合的语音端点检测方法。 To overcome such problem, this paper proposed a speech endpoint detection method based on the fusion of four parameters: sub-band spectral variance, energy entropy ratio, MFCC cepstrum distance and likelihood ratio.
38980 该方法能自适应地改变各参数阈值，并通过实时监测噪声段能熵比的值确定所采用的投票判决机制，从而进行语音端点判定。 This method could change the threshold of each parameter adaptively, then determined the voting mechanism by real-time detection of the energy entropy ratio of the noise segment, so as to determine the speech endpoint.
38981 实验结果表明，该方法在低信噪比下较常用的端点检测方法有更高的检测正确率及鲁棒性，对语音信号后续处理工作有一定的借鉴意义。 Experimental results show that the proposed method has higher detection accuracy and robustness than the conventional endpoint detection methods in the case of low signal-to-noise ratio. The proposed method has certain reference significance for the follow-up processing of speech signal.
38982 利用分布式传感器网络进行目标跟踪，能够有效增加传感器的覆盖范围，提高对运动目标的检测和跟踪能力，但如何充分利用相邻传感器之间的信息进行有效的融合，仍然是一个难点问题。 Distributed multi-sensor(DMS) network can effectively increase the coverage of the sensors and improve the ability of detection and tracking for moving targets.However, the Generalized Covariance Intersection(GCI) based fusion algorithm is suffer from the problem that the tracking performance will be deteriorated under complex environment.
38983 本文在多伯努利滤波(Multi-Bernoulli，MB)框架下，提出了一种改进的分布式融合跟踪算法用于目标数未知且变化的多目标跟踪。 In this paper, we proposed an improved distributed fusion algorithm under the multi-Bernoulli(MB) filter framework for improving the tracking performance under complex environment.
38984 提出算法包含三种精度提升策略，即特征级融合反馈、决策级融合输出及交互反馈;其中，决策级融合输出策略可以提取更加准确的估计状态，特征级融合反馈策略可以降低错误融合结果对后续滤波过程的不良影响， First, a decision-level fusion strategy is proposed to extract more accurate estimation states, and then a feature-level fusion feedback strategy is proposed to reduce the negative influences of the inaccurate fusion results for the subsequent filtering process.
38985 交互反馈策略可以避免单传感器因漏检而导致的滤波失败。 Moreover, an interactive feedback strategy is proposed to avoid the miss tracking of each single sensor.