基于卷积神经网络的5G蜂窝网络无线定位方法

5G蜂窝网络发展迅猛，其覆盖面积将逐渐增大，因此使用5G蜂窝网络进行定位是有研究潜力的研究方向。本文提出一种新的深度学习技术来实现高效、高精度和低占用的定位，以代替传统指纹定位过程中繁重的指纹库生成以及距离计算。该方法建立了一个特殊的卷积神经网络，并根据5G天线信号的接收信号强度指示、相位和到达角等特征量，选择合适的输入数据格式构造样本组建训练集，对该卷积神经网络进行训练。训练得到的卷积神经网络可以替代指纹定位中的庞大指纹库，非常有利于直接在5G移动设备端实现定位。虽然卷积神经网络在训练过程中需要大量时间，但在训练完毕后直接进行分类定位的速度非常快，可以保障定位实现的实时性。本文所实现的卷积神经网络权重与偏置所占内存不到0.5 MB，且能够在实际应用环境中以95%的定位准确率以及0.1 m的平均定位精度实现高精度定位。     

Nonuniform linear array DOA estimation using EM criterion

In this letter, we address the problem of Direction of Arrival (DOA) estimation with nonuniform linear array in the context of sparse Bayesian learning (SBL) framework. The nonuniform array output is deemed as an incomplete-data observation, and a hypothetical uniform linear array output is treated as an unavailable complete-data observation. Then the Expectation-Maximization (EM) criterion is directly utilized to iteratively maximize the expected value of the complete-data log likelihood under the posterior distribution of the latent variable. The novelties of the proposed method lie in its capability of interpolating the actual received data to a virtual uniform linear array, therefore extending the achievable array aperture. Simulation results manifests the superiority of the proposed method over off-the-shelf algorithms, specially on circumstances such as low SNR, insufficient snapshots, and spatially adjacent sources.     

Effect of health status evaluated at arrival on growth in milk-fed veal calves: A prospective single cohort study

The objective of this prospective single cohort study was to determine the effect of health status at arrival on growth in milk-fed veal calves. Upon arrival at the veal facility, calves were evaluated using a standardized health scoring system and weighed, and the supplier of the calf was recorded. The calves were followed until slaughter, when the hot carcass weight (HCW) was reported. To calculate average daily gain (ADG), the HCW was transformed into an estimated live weight, weight at arrival was subtracted, and this value was divided by the number of days on feed. A mixed linear regression model was created to evaluate the association of health status on arrival with the ADG throughout the production period. A total of 4,825 calves were evaluated at arrival; however, due to inconsistent HCW data from one slaughter plant, and 357 calves dying during the production period, 2,283 calves were used for analysis. In the final model, 7 variables were significantly associated with ADG. Housing location within the farm, method of calf procurement (drover or auction-derived calves versus direct delivery from local farms) and having a higher body weight at arrival were associated with a higher ADG. The season of arrival (summer or fall compared with winter) and being dehydrated at arrival were associated with a lower ADG. Days on feed was also significant in the multivariable model and had a quadratic relationship with ADG. The associations identified suggest that there may be value in scoring dehydration and body weight at arrival to a veal facility.     

Q值正演模拟约束下的零偏移距VSP资料Q值估算

随着油气勘探目的层逐步走向深部,球面扩散、透射损失、环境噪声等使得VSP资料的初至子波发生改变,导致常规的Q值估算方法质量难以得到保证。为此,利用塔里木盆地托甫台地区TP327井零偏移距VSP资料,综合考虑透射损失和球面扩散的影响,提出一种Q值正演模拟约束下的零偏移距VSP资料Q值估算方法。该方法通过研究区的纵波速度、横波速度和密度建立层状地质模型,利用射线追踪的方法,用大地吸收介质模型的Q值正演模拟结果,对频谱比法和经验公式估算的初始Q值进行修正,使得Q值正演模拟结果与实际地震波的衰减记录在频谱特征上吻合,从而得到更为精确的Q模型。TP327井Q值估算结果表明,该方法与李庆忠经验公式得到的结果在浅层比较接近,但在中层和深层,两者差异较大;Q值正演模拟结果约束的子波与实际VSP资料子波的频谱比较吻合,证实用Q值正演模拟约束得到的层间Q值更为可靠。利用Q值正演模拟约束方法得到的Q模型对研究区地震资料进行反Q滤波能显著提高地震资料分辨率,有助于提高碳酸盐岩地层中缝洞的识别精度。     

柴达木盆地三湖坳陷横波勘探中的低幅异常消除技术

近年来,在柴达木盆地三湖坳陷开展了横波地震勘探,但是由于该区低幅度构造发育,横波静校正引起的"低幅"异常与上述低幅度构造相互混杂,难以区分。为此,针对该区横波表层调查难以控制表层横波速度模型的变化、横波近偏移距初至污染严重、横波折射层发育导致高速界面难以确定等问题,首先采用曲线拟合技术预测污染区横波初至时间确保初至完整性,然后采用面波模型与多层折射分层联合约束反演横波表层速度,最后通过基于速度谱分析的层位匹配建模技术确定合理的横波速度界面,形成了横波表层"低幅"异常消除技术,并进行了现场应用及效果评价。研究结果表明:①曲线拟合技术可以弥补近道污染区横波初至空白,保证层析反演模型的完整性;②基于瑞雷波的频散特性反演建模可以为确定该区浅层横波速度提供可靠的资料,提高浅层模型精度;③面波模型与多层折射分层联合约束反演能够更准确的反演该区表层横波速度场,较好地建立横波速度模型,消除横波剖面上"低幅"异常现象。结论认为,所形成的横波地震勘探低幅异常消除技术消除了横波静校正引起的"低幅"异常现象,提高了横波地震资料的成像品质。     

Off‐grid DoA estimation method of wideband signals

In this paper, an off‐grid direction of arrival (DoA) estimation method is proposed for wideband signals. This method is based on the sparse representation (SR) of the array covariance matrix. Similar to the time domain DoA estimation methods, the correlation function of the sources was assumed to be the same and known. A new measurement vector is obtained using the lower‐left triangular elements of the covariance matrix. The DoAs are estimated by quantizing the entire range of continuous angle space into discrete grid points. However, the exact DoAs may be located between two grid points; therefore, this estimation has errors. The accuracy of DoA estimation is improved by the minimization of the difference between the new measurement vector and its estimated values. Simulation results revealed that the proposed method can enhance the DoA estimation accuracy of wideband signals.     

Joint Estimation of 2-D DOA and Polarization by Using the Linear Array with Diverse Polarizations

Antenna arrays with diverse polarizations havesome inherent advantages over the conventional uni-formly polarized array,for instance,higher accuracyof direction-of-arrival(DOA)esti mation,capabilityof resolving or separating signals based ontheir polar-ization characteristics as well as DOAs[1-7].Thepresence of polarization diversity,complicates themeasurement model which introduces a relativelyhigher computational requirement[8,9].Moreover,many existing algorithms proposed in the literature…     

基于粒子群TOA室内定位的系统误差修正

到达时间（time of arrival,TOA）的测距易受多径干扰的影响而产生较大的系统误差,造成室内定位时精度变差。针对上述问题,首先分析了TOA定位中系统误差的产生及特点,而后提出一种基于粒子群优化的定位算法。算法利用测距值与所求解位置的空间约束关系建立求解域,而后应用粒子群算法求解,并通过建立关于系统误差的罚函数和适应度函数实现误差修正,并减小粒子搜索空间,加快算法收敛速度。实验表明,利用本文描述的定位算法,可以有效抑制室内定位中测距产生的系统误差,定位精度得到明显提高。     

基于IGS观测数据的智利Mw8.2级地震分析

利用2014年智利Mw8.2级地震前后各3d的震中周边40个IGS站的连续观测数据和IGS精密星历,计算获得远场同震地表位移,结果显示,智利地震同震水平位移影响范围达1 500 km~2 000 km;经过对其中2个IGS站的高频观测数据进行解算,获得地震发生瞬时测站动态运动轨迹,在此基础上,使用S变换,过滤背景噪声,有效拾取P波初至时刻,反演出P波在地壳中的传播速度,并与IRIS提供的参考值进行对比和分析,说明结果的可靠性。     

三维模型中的多普勒功率谱分析

多普勒效应是移动通信中最常见的现象,研究多普勒功率谱密度的分布,对建立更准确并贴合实际的无线信道模型具有重大意义。分析了两种不同几何模型中的多普勒功率谱,重点讨论了三维模型中入射波到达角度对多普勒功率谱的影响,仿真结果表明,方位角和高度角的分布及最大角取值范围共同决定了多普勒功率谱的分布特性。