基于逆系统方法的多输入多输出非高斯驱动信号生成

多输入多输出(MIMO)振动环境试验是振动试验的新方法,该方法比传统的单输入单输出(SISO)方法更真实地模拟了结构在实际工作下的振动环境。传统随机振动试验的频域方法所模拟的是平稳高斯信号,但是实际振动环境往往是超高斯的,且超高斯激励和高斯激励对结构的损害差异很大,因此对MIMO超高斯振动环境试验的研究十分重要。驱动信号的产生是振动环境试验的关键。提出一种基于逆系统的MIMO超高斯驱动信号生成方法。首先,根据给定的响应参考功率谱密度(PSD)和参考峭度值采用相位调节法生成参考响应超高斯伪随机信号;其次,利用逆系统方法生成超高斯伪随机驱动信号;最后,对伪随机驱动信号进行时域随机化处理得到超高斯真随机驱动信号。对一根两输入两输出的悬臂梁模型进行了仿真验证,结果表明,采用本文方法所得到的驱动信号加载在梁上后,其输出响应谱与给定参考谱之间的误差完全满足工程中常用的±3 dB的要求,而且峭度也与给定的参考值十分接近,证实了所提方法的有效性。     

Stationary non-Gaussian random vibration control: A review

This paper presents a review of the various methods for the stationary non-Gaussian random vibration control. Random vibration tests can be divided, according to the number of exciters, in single-shaker tests and multiple-shaker tests. In the stationary non-Gaussian random vibration test, the time and frequency domain characteristics of the responses should be controlled independently and simultaneously. Skewness and kurtosis are usually selected as the non-Gaussian time control references (targets) while power spectral density is the frequency domain control procedure before it recalls the concepts of non-Gaussianity. Then, the generation of a one frame stationary non-Gaussian random signal for both the single and multiple shakers are reviewed. The commonly used methods for the single non-Gaussian random signal generation in the random vibration test are memoryless nonlinear transformation, phase modification and Filtered Poisson process. For the multiple-shaker case, the sequential phase modification and memoryless nonlinear transformation are used to generate one frame coupled multi-channel non-Gaussian random signal. In order to obtain a stationary and consecutive dynamic input, the time domain randomization procedure is introduced with high computational efficiency and its influences on the skewness and kurtosis are analyzed. Finally, two existing problems in the non-Gaussian random vibration control are addressed.     

Analysis of an adaptive CFAR detector in non-Gaussian interference

Coherent signal detection in non-Gaussian interference is presently of interest in adaptive array applications. Conventional array detection algorithms inherently model the interference with a multivariate Gaussian random vector. However, non-Gaussian interference models are also under investigation for applications where the Gaussian assumption may not be appropriate. We analyze the performance of an adaptive array receiver for signal detection in interference modeled with a non-Gaussian distribution referred to as a spherically invariant random vector (SIRV). We first motivate this interference model with results from radar clutter measurements collected in the Mountain Top Program. Then we develop analytical expressions for the probability of false alarm and the probability of detection for the adaptive array receiver. Our analysis shows that the receiver has constant false alarm rate (CFAR) performance with respect to all the interference parameters. Some illustrative examples are included that compare the detection performance of this CFAR receiver with a receiver that has prior knowledge of the interference parameters     

Control method for multi-input multi-output non-Gaussian random vibration test with cross spectra consideration

A control method for Multi-Input Multi-Output(MIMO) non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified references composed of auto spectral densities, cross spectral densities and kurtoses on the test article in the laboratory. It is found that the cross spectral densities will bring intractable coupling problems and induce difficulty for the control of the multioutput kurtoses. Hence, a sequential phase modification method is put forward to solve the coupling problems in multi-input multi-output non-Gaussian random vibration test. To achieve the specified responses, an improved zero memory nonlinear transformation is utilized first to modify the Fourier phases of the signals with sequential phase modification method to obtain one frame reference response signals which satisfy the reference spectra and reference kurtoses. Then, an inverse system method is used in frequency domain to obtain the continuous stationary drive signals. At the same time, the matrix power control algorithm is utilized to control the spectra and kurtoses of the response signals further. At the end of the paper, a simulation example with a cantilever beam and a vibration shaker test are implemented and the results support the proposed method very well.     

液压管路系统随机振动下疲劳分析

民用飞机液压管路系统受到飞机振动环境的影响,可能产生振动引发的管路及安装结构疲劳破坏。为了分析液压管路系统在飞机振动环境下的承受能力,参考RTCA/DO-160G中对于固定翼飞机振动环境的定义及要求,对某民用飞机液压管路进行振动模态和随机振动响应分析。通过有限元分析得出了液压管路及安装结构的随机振动Von Mises均方根应力,采用基于高斯分布和Miner线性累计损伤定律的三区间法,计算管路系统的随机振动疲劳损伤,得到了疲劳薄弱部位及疲劳分析结果,为民用飞机液压管路在随机振动环境下的疲劳分析提供参考。     

基于遗传算法的多振动台随机振动控制方法

 针对多振动台随机振动控制问题中求解补偿矩阵的广义逆算法,提出利用遗传算法对补偿矩阵的初值进行优化,解决了该类非线性、大范围极值求解问题。双振动台随机振动控制的仿真实验研究表明:将基于遗传算法的广义逆求解补偿矩阵方法引入随机振动控制过程,在同等精度条件下,计算时间大为缩短并改善了控制中共振峰处的奇异性,使广义逆算法在多振动台随机振动控制中的在线应用成为可能。     

A nonlinear IMM algorithm for maneuvering target tracking

In target tracking, the measurement noise is usually assumed to be Gaussian. However, the Gaussian modeling of the noise may not be true. Noise can be non-Gaussian. The non-Gaussian noise arising in a radar system is known as glint noise. The distribution of glint noise is long tailed and will seriously affect the tracking performance. We develop a new algorithm that can effectively track a maneuvering target in the glint environment The algorithm incorporates the nonlinear Masreliez filter into the interactive multiple model (IMM) method. Simulations demonstrate the superiority of the new algorithm     

Matched subspace CFAR detection of hovering helicopters

A constant false alarm rate (CFAR) strategy for detecting a Gaussian distributed random signal against correlated non-Gaussian clutter is developed. The proposed algorithm is based on Scharf's matched subspace detector (MSD) and has the CFAR property with respect to the clutter amplitude probability density function (apdf), provided that the clutter distribution belongs to the compound-Gaussian family and the clutter covariance matrix is known to within a scale factor. Analytical expressions of false alarm and detection probabilities are derived. An application to the problem of detecting hovering helicopters against vegetated ground clutter is reported     

CFAR detection of distributed targets in non-Gaussian disturbance

The subject of detection of spatially distributed targets in non-Gaussian noise with unknown statistics is addressed. At the design stage, in order to cope with the a priori uncertainty, we model noise returns as Gaussian vectors with the same structure of the covariance matrix, but possibly different power levels (heterogeneous environment). We also assume that a set of secondary data, free of signal components, is available to estimate the correlation properties of the disturbance The proposed detector assumes no a priori knowledge about the spatial distribution of the target scatterers and ensures the constant false alarm rate (CFAR) property with respect to both the structure of the covariance matrix and the power levels. Finally, the performance assessment, conducted modeling the disturbance as a spherically invariant random process (SIRP), confirms its validity to operate in real radar scenarios     

减振测试振动台及其控制系统

为验证减振器的隔振效果,设计了一套能提供典型振动条件的单自由度垂直往复运动的电液振动台及其计算机控制系统,通过该系统可以在室内模拟定频振动、扫频振动、随机振动及冲击谱等振动条件,完成所测减振器的机械力学性能或产品耐久性寿命测试等试验。系统控制部分采用上下位工控机结构,分别完成数据采集、实时控制,运行参数监控、数据处理的功能,控制策略采用模糊PID复合控制,控制参数可方便调整,能实现典型的波形再现和功率谱再现。系统运行结果表明,无论是时域还是频域均能达到满意的振动模拟。     

Joint parameter and state estimation for stochastic uncertain system with multivariate skew t noises

Due to the pulse interference, measurement outliers and artificial modeling errors, the multivariate skew t noise widely exists in the real environment. However, to date, little attention has been paid to the state estimation for systems in which the process noise and the measurement noise are both modeled as the heavy-tailed and skew non-Gaussian noise. In this paper, the multivariate skew t distribution is utilized to model the heavy-tailed and skew non-Gaussian noise. Then a probabilistic gra...     

基于压缩感知的整体叶盘多模态振动叶尖定时信号重构方法

叶尖定时测量技术是近年来发展的一种非接触式旋转叶片振动监测方法,具有非入侵性的优点,但是该系统测得的振动信号通常是欠采样的。为了能够重构叶尖定时欠采样信号,本文根据压缩感知理论以及叶尖定时采样原理引入了叶尖同步振动信号稀疏模型以及叶尖振动信号重构方法。对整体叶盘有限元模型进行瞬态分析得到叶尖振动信号,使用优化的正交匹配追踪算法以及基追踪对欠采样信号进行重构并和传统方法进行对比。计算结果表明：在信噪比为30dB的噪声环境下,限制频域的正交匹配追踪算法(OMP-RFD)可以准确地识别出叶尖振动信号的主要频率成分。最后使用试验所获得的叶尖振动信号进行重构,验证了OMP-RFD算法有效性。综上可知：压缩感知方法可以很好地应用于叶尖定时测量装置中,能够使用较少传感器识别叶尖同步振动欠采样信号参数,有效提高噪声环境下识别高阶频率的成功率以及准确度。     

Vector subspace detection in compound-Gaussian clutter. Part I: survey and new results

Deals with the problem of detecting subspace random signals against correlated non-Gaussian clutter exploiting different degrees of knowledge on target and clutter statistical characteristics. The clutter process is modeled by the compound-Gaussian distribution. In the first part of the paper, the optimum Neyman-Pearson (NP) detector, the generalized likelihood ratio test (GLRT), and a constant false-alarm rate (CFAR) detector are sequentially derived both for the Gaussian and the compound-Gaussian scenarios. Different interpretations of the various detectors are provided to highlight the relationships and the differences among them. In particular, we show how the GLRT detector may be recast into an estimator-correlator form and into another form, namely a generalized whitening-matched filter (GWMF), which is the GLRT detector against Gaussian disturbance, compared with a data-dependent threshold. In the second part of this paper, the proposed detectors are tested against both simulated data and measured high resolution sea clutter data to investigate the dependence of their performance on the various clutter and signal parameters.     

MIMO随机振动试验控制的逆多步预测模型法

多输入多输出（MIMO）随机振动试验在产品可靠性验证中扮演重要角色。逆系统方法作为一种时域方法，直接由参考信号（即期望得到的响应信号）生成驱动信号，但容易产生不稳定的结果。本文以系统的有限差分模型为基础，推导了逆多步预测模型，并建立了该逆模型与矩阵幂次算法结合的MIMO随机振动试验方法。通过悬臂梁模型进行双输入双输出仿真试验，验证了逆多步预测模型进行MIMO随机振动试验驱动生成的可行性。在三轴振动台上进一步验证该方法进行MIMO随机振动试验控制的能力。     

高斯噪声中非高斯弱信号的双谱检测

传统的能量检测在接收信号为高斯分布下最优,其检测性能最终取决于信噪比。当信噪比下降时,检测性能必然恶化,而且这种恶化是不可避免的和难以改善的。为了改善弱信号的检测性能,本文同时利用了信号的三阶和二阶统计量构造一种双通道信号检测器,在强高斯噪声的背景下,只要弱信号蕴含有足够多的双谱信息,其检测性能将远远超过基于传统的能量检测器的性能。     

SINS/GNSS integrated navigation system based on maximum versoria filter

In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System (SINS/GNSS) integrated navigation system, due to the factors such as the high dynamics, the signal blocking by obstacles, the signal intefereces, etc., there always exist pulse interferences or measurement information interruptions in the satellite receiver, which make nonstationary measurement process. The traditional Kalman Filter (KF) can tackle the state estimation problem under Gaussian white noise, but its performance will be significantly reduced under non-Gaussian noises. In order to deal with the non-Gaussian conditions in the actual missile-borne SINS/GNSS integrated navigation systems, a Maximum Versoria Criterion Extended Kalman Filter (MVC-EKF) algorithm is proposed based on the MVC and the idea of M-estimation, which assigns a smaller weight to the anomalous measurements so as to suppress the influence of anomalous measurements on the state estimation while maintaining a relatively low calculation cost. Finally, the integrated navigation simulation experiments prove the effectiveness and robustness of the proposed algorithm.     

Target racking with glint noise

In tracking targets, there can be an uncertainty associated with the measurements in addition to their inaccuracy, which is usually modeled by aDditive Gaussian noise. However, the Gaussian modeling of the noise may not be true. Noise can be non-Gaussian. The non-Gaussian noise arising in a radar system is known as glint noise. The distribution of glint noise is long tailed and will seriously affect the tracking performance. An algorithm is developed which can significantly improve the tracking performance when glint noise is present     

随机振动校准加速度计方法研究

介绍了随机振动校准加速度计系统的实现.使用随机信号传感器绝对校准方法,得到了较为理想的加速度计频响曲线.与传统的方法相比在保证校准精度的前提下,提高了效率.     

航空发动机振动环境谱统计归纳方法及振动试验台复现

为满足航空发动机及机载产品研制过程贴近使用环境的振动考核试验需求,需根据发动机实测振动数据给出振动考核试验所需的输入谱图。依据GJB/Z 126-99中给出的环境测量数据归纳方法,建立了发动机实测振动环境谱统计归纳方法并通过程序实现。利用发动机多架次实测试飞振动数据统计归纳得到发动机测点位置的振动实测谱。基于能量等效及信号频域特征分布一致原则,将归纳得到的实测谱转化为可用于振动台输入的振动环境谱,并在振动台上进行了振动信号的复现试验。结果表明：振动台输出信号与发动机实测振动信号频域分布特征一致,在统计频率带宽范围内振动总量最大相差5.7%,证明了转化方法是合理的,为航空发动机机载设备贴近使用环境的振动考核试验方法提供了真实的输入谱图。     

Maximum likelihood identification of glint noise

If the non-Gaussian distribution function of radar glint noise is known, the Masreliez filter can be applied to improve target tracking performance. We investigate the glint identification problem using the maximum likelihood (ML) method. Two models for the glint distribution are used, a mixture of two Gaussian distributions and a mixture of a Gaussian and a Laplacian distribution. An efficient initial estimate method based on the QQ-plot is also proposed. Simulations show that the ML estimates converge to truths