Noise and vibration measurements in a Viking military vehicle

Noise and whole-body vibration measurements were made in a Viking military vehicle to determine the variation that should be expected during repeat measures, the effect of speed (up to 60 km/h in 5 km/h increments), and during travel over different types of terrain (comprising concrete road, gravel track and rough cross-country). Measurements were made at various crew positions (including the driver and commander) in both the front and the rear cabs in the vehicles. Three translational axes of vibration were measured in each seat. Two speeds were investigated over road (35 km/h and 55–60 km/h) and gravel (20 km/h and 35 km/h) surfaces. The effect of varying speed of the vehicle on the measured noise and vibration magnitudes was also investigated. The highest sound pressure level (L_Aeq) of 104 dB(A) was measured at the commander’s standing position during travel over concrete road at 55 km/h. Higher noise levels occurred for a standing commander compared with when sitting on the seat. A maximum single axis frequency-weighted vibration magnitude of 1.0 m/s² r.m.s. was measured on the driver’s seat during travel over track at 35 km/h. Higher vibration magnitudes occurred during travel over track compared with travel over road. Both noise and vibration exposure of crew within the Viking vehicle increased with increasing speed of the vehicle.     

非高斯噪声下信号盲检测算法*

针对实际甚低频和超低频接收机不仅受非高斯噪声的影响,同时受到接收机内部和外部环境中高斯噪声影响的问题,对噪声采用高斯尺度混合分布和高斯分布的混合模型建模,根据混合模型的性质,设计了一种基于马尔可夫链蒙特卡罗方法的信号盲检测算法。盲检测算法在贝叶斯层次模型下,采用Gibbs抽样和M-H抽样更新参数,同步检测信道衰落系数、噪声模型参数和信号。算法迭代效率快、精度高。通过与最优检测性能比较,盲检测算法性能优异,对甚低频和超低频信号接收具有重要的现实意义。     

基于鲁棒高阶容积滤波的无人机相对导航状态估计方法

由于无人机相对导航系统具有非线性强、噪声非高斯的特点,传统的基于卡尔曼滤波算法设计的相对导航滤波器存在估计失准甚至发散的问题。考虑到高阶容积卡尔曼滤波和最大熵滤波算法分别在解决非线性问题和非高斯问题时的优势,利用最大熵滤波的量测更新方法对高阶容积卡尔曼滤波的测量更新方程进行了改进,将传统的量测更新问题转换成了线性衰退的求解问题,避免了对测量噪声进行高斯假设,同时解决了系统非线性和量测噪声非高斯的问题。进行了相应的数学仿真,仿真结果表明:所提算法的估计精度超过了高阶容积卡尔曼滤波和最大熵滤波算法的,验证了算法的有效性。     

蜂窝网络中基于干扰控制的D2D通信联合资源分配方案

在蜂窝网络中部署D2D(Device-to-Device)通信能够有效提升频谱利用率,降低基站负载,但D2D用户与蜂窝用户共享无线信道时会产生信号干扰。提出了一种联合资源分配算法,通过综合考虑信道分配对网络中已有的蜂窝用户和D2D用户的信号干扰,并在小区范围内寻找具有最小干扰值的信道资源分配给用户,以实现有效的干扰控制。仿真结果显示:联合资源分配能够提升D2D链路、蜂窝链路的信噪比及系统总吞吐量,使得蜂窝网络的整体性能优于独立资源分配。     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

收发同源设备中相位噪声对信号的影响分析

收发同源设备中信号经过下变频、A/D采样、数字信号处理、D/A恢复和上变频等流程,本文给出了相应的信号传输模型,并针对频标相位噪声对信号通过的影响进行了分析,基于上、下变频时刻频标相位噪声发生变化的分析,推导出了频标相噪对信号经过收发同源设备所产生的影响表达式,并得出结论:由于频标相噪的存在,使得信号通过收发同源设备后伪码速率和载波均被引入一个与频标频率变化率相关的因子,可视为引入了多普勒偏移量,并明确给出了该偏移量的表达式。该结论与普遍认为的收发同源可以完全抵消频标相噪的影响有较大区别,实验验证结果较好地吻合了理论分析的结论。     

反辐射导引头对双噪声调频干扰源的角度分选

针对宽频带反辐射导弹导引头,推导出对于两个频谱重叠的噪声调频干扰源的合成相位差公式;仿真验证了当两个调频干扰信号存在一定能量差时,合成相位差的均值偏向能量较大的信号源。当两个噪声干扰源存在一定能量差时,可以跟踪能量较大的干扰源。     

干扰信号的检测技术研究

以噪声调频干扰为例,对干扰信号的检测问题进行了分析,提出直接积累检测和二进制积累的检测方法,并计算了两种方法的检测概率。通过积累检测显著地改善了接收机对噪声干扰类信号的检测性能。     

在非高斯弱相关噪声中弱信号的最佳检测

本文探讨了仅已知噪声一维分布和二阶统计特性的条件下非高斯无穷相关噪声中确知弱信号的最佳检测问题。在假设噪声为一阶AR过程ni=yi+ρn(i-l)的情况下,以最优化检测器的渐近相对效验为准则。并对p取一阶和二阶近似的意义下,分别得到了最佳有记忆和无记忆检测器的闭式解。推证和比较了它们同非高斯白噪声中的最佳检测器在结构上的异同和性能上的改进程度。最后给出了几个典型的实际例子。