ID 原文 译文
20395 传统的波形畸变评估方法主要针对传统相移键控(PSK)调制信号的波形幅度和宽度开展研究，而忽视了波形不对称对跟踪误差和测距误差带来的影响。 These traditional methods for evaluating evil waveforms mainly deal withthe amplitude and width of simple modulated signals such as Phase Shift Keying (PSK) signals. However, noresearch is done on the influences of waveform asymmetry on tracking errors and ranging errors.
20396 该文在国际民航组织(ICAO)所采用的传统测距码波形分析模型TMA/TMB/TMC基础上，给出了适用于各种新型二进制偏置载波(BOC)调制的波形畸变分析扩展模型。 Based on the traditional thread models, such as Thread Model A (TMA), Thread Model B (TMB) and Thread Model C(TMC), adopted by International Civil Aviation Organization (ICAO), this paper provides a new extended general thread model suitable for new Binary Offset Carrier (BOC) modulated signals.
20397 接着提出能够精细分析波形上升下降沿对称特性(WRaFES)分析模型，并从时域波形、相关函数、S曲线过零点偏差3个方面，深入仿真分析了WRaFES模型的性能特点。 Then a new evil waveform analysis method, Waveform Rising and Falling Edge Symmetry (WRaFES) Method, is proposed. The effects of WRaFES model are analyzed in detail in terms of time domain, correlation peak and S curve bias.
20398 最后，以北斗试验卫星M1-S B1Cd信号为例，给出了基于WRaFES模型及相关曲线特性的实测分析结果。 Finally, by taking the B1Cd signal of the first modernized BeiDou navigation satellite System (BDS)experimental satellite named M1-S as an example, tested results of WRaFES model and correlation curves are shown in detail.
20399 研究表明：该方法能够精确分析导航信号波形不对称性及对用户带来的影响， Results show that the proposed methods could be able to analyze the asymmetry of signal deformation and its impact on ranging performance with high accuracy.
20400 研究成果可为新型卫星导航信号评估提供一种新方法和新思路，同时还可为GNSS用户接收机相关器间隔参数的合理选取提供建议和技术支撑。 The research brings about a newreference for new satellite navigation signal evaluation and signal system optimized design. In addition, it can provide valuable suggestions and technical supports for GNSS users to choose reasonable receivers’ correlatorspacing.
20401 针对当前基于人工神经网络的垂直切换算法(ANN-VHO)，存在业务自适应性差和计算复杂度高的问题，该文提出一种基于人工神经网络的自适应垂直切换算法。 Current research on Vertical HandOver algorithm based on Artificial Neural Network (ANN-VHO)has a poor service adaptability and high computational complexity. Considering this problem, an adaptivevertical handover algorithm based on artificial neural network is proposed.
20402 首先，根据终端获取到的接收信号强度(RSS)，采用阈值判断的方法，遴选出候选网络集； Firstly, according to the ReceivedSignal Strength (RSS) obtained by the terminal, a method of thresholding is used to select a candidate networkset.
20403 其次，根据该文划分的不同业务类型，对参数进行自适应选择和归一化； Secondly, in terms of the different types of services classified in this paper, the parameters are normalizedand adaptively selected;
20404 再次，把选择的参数输入人工神经网络，判决出候选网络集中最佳的接入网络。 Thirdly, the selected parameters are input into the artificial neural network to choosethe best access network from the candidate network.