一种新的非高斯随机振动信号的模拟方法

传统的环境振动试验常将随机振动信号假设服从高斯分布,且利用功率谱密度（PSD）来作为试验条件。然而实际环境中结构所受到的振动激励很多呈现非高斯性,且PSD只能描述信号的低阶统计量,无法描述非高斯信号的峭度和偏度等高阶统计量。针对此情况,研究了在窗函数幅值调制法（AMT）基础上利用自PSD和峭度生成非高斯信号的方法。针对调制信号的生成,提出了近似模拟方法。通过Weibull和Beta 2种分布构造调制信号,研究分布参数与目标峭度值之间的关系,并分析2种分布合成目标峭度值的范围。案例验证了仿真生成的非高斯信号与实测外场数据具有相同的PSD、概率密度函数（PDF）和峭度值,进而证明了方法的正确性。      

Satellite collision probability estimation using polynomial chaos expansions

This paper presents the application of polynomial chaos (PC) to estimating the probability of collision between two spacecraft. Common methods of quantifying this probability for conjunction assessment use either Monte Carlo analyses or include simplifying assumptions to improve tractability. A PC expansion, or PCE, provides a means for approximating the solution to a large set of stochastic ordinary differential equations, which includes orbit propagation. When compared to Monte Carlo methods, non-intrusive, i.e., sampling-based, PCE generation techniques may greatly reduce the number of orbit propagations required to approximate the possibly non-Gaussian, a posteriori probability density function. The presented PC-based method of computing collision probability requires no fundamental simplifying assumptions, and reduces the computation time compared to Monte Carlo. This paper considers two cases where the common conjunction assessment assumptions are no longer valid. The results indeed demonstrate a reduction in computation time when compared to Monte Carlo, and improved accuracy when compared to simplified techniques.     

非高斯随机振动的模拟方法

随机振动台根据功率谱密度（PSD,Power Spectral Density）生成的信号为高斯信号,而实际振动环境有时是非高斯的,因此随机振动实验常常无法准确模拟产品在真实振动环境下的失效情况。通过两个案例分别对均方根值（RMS,Root Mean Square）不随时间变化和随时间变化的非高斯随机振动进行了模拟方法研究。案例1利用Hermite多项式法对高斯信号进行了转换,在保证功率谱密度不变的同时得到了具有指定峭度的RMS不随时间变化的非高斯信号,但该方法对于输入的峭度有限制,当输入峭度大于10时,误差达到了20%。案例2利用一种新方法对实测的RMS随时间变化的非高斯振动进行了模拟,模拟后得到的非高斯信号和实测信号具有相同的功率谱密度、峭度以及概率分布,验证了新方法的准确性。     

复杂背景下目标散射信号测量与提取技术

在复杂环境条件下的宽带雷达目标散射特性测量中,场地周围环境产生的零多普勒杂波（ZDC）会严重影响目标测量数据的准确性。为了有效地抑制背景杂波、提高目标散射信号的测量精度,提出了一种基于最大概率提取技术。该技术首先通过方位滑窗平均得到每个频点的初始固定背景杂波估计,然后对每个频点的杂波初始估计进行统计直方图处理得到最大概率幅度统计量,并依据该统计量完成门限处理得到最终的杂波估计值,从而消除方位滑窗平均处理中的剩余目标信号分量、实现精确的背景提取与抵消。对典型目标的外场测量数据处理结果验证了本文方法的有效性。      

基于PHD未知杂波密度多机动目标跟踪

基于随机有限集（RFS）的跳变马尔可夫系统（JMS）是多机动目标跟踪的有效方法。但现有的方法假设杂波密度是先验已知的,而实际中杂波密度是未知且可能随着环境的改变而变化。针对这一问题,提出了一种适用于线性高斯模型的未知杂波密度下多机动目标跟踪算法。该算法以未知杂波密度高斯混合概率假设密度（λ-GMPHD）滤波为基础建模杂波和真实目标,采用线性高斯JMS模型描述目标机动,推导了未知杂波密度下多机动目标跟踪的GMPHD迭代解析表达式。仿真结果表明,所提算法可实现对于杂波密度以及目标数和目标状态的准确估计。      

Multiple-site investigation of the properties of an HF radio channel and the ionosphere using Digital Radio Mondiale broadcasting

The Digital Radio Mondiale (DRM), one of the new digital radio broadcasting standards, has been designed to overcome typical short wave radio channel difficulties, such as the multipath propagation and fast temporal changes of the received signal level, both related to the properties of the ionosphere along the path of propagation. In particular, some of the RF carriers used in the applied COFDM transmission technique serve to estimate the current state of the radio channel to enable the proper demodulation of the received signal.We have been detecting such RF carriers on select frequency channels (standard DRM broadcast) using a network of recording stations located in different parts of Poland in order to collect data on the HF radio channel. We have been also evaluating the usefulness of this procedure in providing information on the current state of the ionosphere in the refraction region between the transmitter and receivers. When the DRM system becomes more widespread, this method can supplement data that comes from the ionosondes, since it does not require much financial resources and the receivers can be easily scattered over a large area. This paper presents a set of experimental data and its analysis.     

Fault detection and isolation in GPS receiver autonomous integrity monitoring based on chaos particle swarm optimization-particle filter algorithm

The receiver autonomous integrity monitoring (RAIM) is one of the most important parts in an avionic navigation system. Two problems need to be addressed to improve this system, namely, the degeneracy phenomenon and lack of samples for the standard particle filter (PF). However, the number of samples cannot adequately express the real distribution of the probability density function (i.e., sample impoverishment). This study presents a GPS receiver autonomous integrity monitoring (RAIM) method based on a chaos particle swarm optimization particle filter (CPSO-PF) algorithm with a log likelihood ratio. The chaos sequence generates a set of chaotic variables, which are mapped to the interval of optimization variables to improve particle quality. This chaos perturbation overcomes the potential for the search to become trapped in a local optimum in the particle swarm optimization (PSO) algorithm. Test statistics are configured based on a likelihood ratio, and satellite fault detection is then conducted by checking the consistency between the state estimate of the main PF and those of the auxiliary PFs. Based on GPS data, the experimental results demonstrate that the proposed algorithm can effectively detect and isolate satellite faults under conditions of non-Gaussian measurement noise. Moreover, the performance of the proposed novel method is better than that of RAIM based on the PF or PSO-PF algorithm.     

基于杂波量测集约束的改进MS-MeMBer滤波器

针对高杂波密度场景下,传统多传感器多目标多伯努利(MS-MeMBer)滤波器存在的量测划分假设质量下降、势估计结果出现偏差等问题,提出了一种基于杂波量测集约束的改进MS-MeMBer滤波器。首先,通过将杂波量测集的影响引入到更新过程中,优化了目标量测集的权重,并给出了杂波场景下的单目标多传感器似然函数。然后,通过两步贪婪划分机制,得到了改进的多传感器量测划分假设。通过仿真将所提方法与传统MS-MeMBer滤波器进行了比较,实验结果表明:在高杂波密度场景下,改进MS-MeMBer滤波器具有更优的多目标跟踪性能。      

扩频信号声光相关解调技术

声光相关技术在检测宽带微弱信号中有很大的潜力，提出在射频上用声光相关器对扩频信号做相关运算的方案，给出扩频信号的快速捕获、精密跟踪和信息解调的方法，并设计了实验系统，结果得到了验证。     

The adaptive Gaussian mixtures unscented Kalman filter for attitude determination using light curves

The Adaptive Gaussian Mixtures Unscented Kalman Filter (AGMUKF) is introduced to estimate the attitude of a Resident Space Object using light curves. This filter models the state probability density function as a Gaussian Mixture. This enables to capture the non-linearities of the light-curve measurement model. A non-linearity index is used to refine the mixture when necessary, and individual Gaussian kernels are merged back together when their relative distance is below a certain threshold. A conventional attitude Unscented Kalman Filter (UKF) is used to propagate and update each kernel. The AGMUKF efficiently maintains the mixture population as low as possible, while still being able to represent non-symmetric, multimodal, arbitrarily complex distributions. Therefore, it is presented as a promising alternative to Particle-Filter-based implementations, the current state of the art used in sequential attitude estimation from light curves. The non-linearity index has been used to show that the measurement model is the main contributor to the system non-linearity. Results have demonstrated the superiority of the AGMUKF w.r.t. the UKF for attitude determination, and that it can converge for high initial state uncertainty cases, successfully capturing the non-Gaussian probability distribution of the state.     

基于β似然函数的参数估计方法

分布参数估计是可靠性数据分析的手段,用于研究产品可靠性的变化规律及评估产品的可靠性水平。使用寿命试验中产品可靠度所服从的β分布评价可靠度估计值的合理程度,认为可靠度估计值在β分布中概率密度较大的更合理,给出了一种评价可靠度函数估计好坏的β似然函数,探讨了使用该函数进行分布参数估计的β似然估计方法,通过仿真验证了该方法在指数分布和威布尔分布下的适用性,并给出了应用实例。本参数估计方法理论依据充分,适用于各种分布类型,估计结果合理可信。极大似然估计方法以样本在待估分布中的概率密度作为评价准则,与之不同,本方法以累积发生比例的估计值作为评价准则,更适用于可靠性、生存率等关注事件累积发生比例的场合。      

基于起爆概率的无线电引信抗箔条干扰能力的量化表征方法

针对现有量化无线电引信抗箔条干扰方法的缺少,以防空导弹引信为例,结合箔条云运动轨迹模型和概率统计手段,提出基于起爆概率的无线电引信抗箔条干扰能力的量化表征方法。首先,在对单根箔条丝的螺旋下降运动进行分析的基础上,结合6-DOF非线性差分方程迭代计算得到箔条云的运动轨迹。其次,通过拟蒙特卡罗算法推导出箔条云的动态体密度函数,以箔条云的运动模型和动态体密度函数分别计算引信在箔条云近区干扰和远区干扰2种干扰作用下的不起爆概率。基于MATLAB构建箔条云轨迹模型,详细分析后得到箔条云动态的点分布模型,在此基础上利用拟蒙特卡罗方法得到箔条云的动态体密度函数,利用八叉树算法及最小二乘曲面法得到箔条云体积。最后,根据概率定义公式计算出箔条云干扰引信起爆概率。结果表明:所提方法客观、合理,为今后设计无线电引信抗箔条云干扰算法的启动条件提供了理论依据。      

空间目标碰撞预警的协方差计算与应用

碰撞概率是碰撞预警工程中空间目标危险交会的重要判据之一,其计算精度会受到预报协方差计算精度的影响. 本文统计计算了两种形式的预报协方差. 一是利用精密数值预报模型对卫星精密根数进行预报,将预报根数与精密根数的差作为样本,统计得出1～7天不同预报期的预报协方差;二是采用 SGP4/SDP4预报模型对TLE数据进行预报,将预报根数与TLE根数的差作为样本,统计得出1～7d不同预报期的预报协方差. 分别分析两种方法中包含变轨过程和无变轨情况下的轨道预报精度. 结合2012年某低轨道卫星的危险交会,分析了采用不同协方差时,协方差精度对碰撞预警精度的影响. 协方差计算可为实际碰撞预警工程提供参考.      

基于ML背景参数估计的CDKF-CPHD多目标跟踪算法

针对低信杂比环境下的多机动目标跟踪问题,提出了一种基于极大似然(ML)背景参数估计的中心差分卡尔曼-势概率假设密度滤波(BE-CDKF-CPHD)算法。算法采用ML法实时估计重尾分布模型参数,计算检测概率和虚警概率。运用极大似然-恒虚警(MLCFAR)算法对信号进行处理,提取有效量测值,将幅值似然函数与势概率假设密度滤波器(CPHD)中的目标位置似然函数相结合,通过中心差分法递归更新得到后验均值与协方差,达到对多机动目标进行跟踪的目的。仿真结果表明,在低信杂比环境中,所提算法提高了跟踪精度与目标数目估计准确度。     

基于探鸟雷达的机场周边鸟类目标数量估计

针对雷达探鸟中的飞鸟目标数量统计问题,提出了一种多目标航迹自动起始跟踪算法,实现了对机场周边鸟类活动热点区域内鸟类目标数量的统计分析。通过数据关联估计量测与所有可能事件的关联概率,包括目标的新生、延续和消亡,以及杂波的剔除,并通过卡尔曼滤波与平滑方法给出每个目标的平滑轨迹,实现了对目标的全生命周期管理。仿真结果表明:所提算法能很好地实现杂波环境中的多目标航迹自动起始跟踪,正确估计每个目标的起始和消亡时间,统计目标数量的变化情况,且在目标起始的及时性方面明显优于传统的逻辑法。将所提算法应用于机场探鸟雷达实测数据,估计机场周边鸟类数量,可指导机场开展有针对性的鸟击防范工作。      

A method to test HF ray tracing algorithm in the ionosphere by means of the virtual time delay

It is well known that a 3D ray tracing algorithm furnishes the ray’s coordinates, the three components of the wave vector and the calculated group time delay of the wave along the path. The latter quantity can be compared with the measured group time delay to check the performance of the algorithm. Simulating a perfect reflector at an altitude equal to the virtual height of reflection, the virtual time delay is assumed as a real time delay. For a monotonic electronic density profile we find a very small relative difference between the calculated and the virtual delay for both analytic and numerical 3D electronic density models.     

瑞利激光雷达反演中层大气温度算法

瑞利激光雷达是探测中层大气温度的重要设备,具有高时空分辨率且不存在探测盲区的优点.为充分利用激光雷达探测到的原始数据,改进了传统的Chanin-Haunchecorne方法,采用由均匀搜索生成温度初值的方式反演大气温度.位于北京延庆（40.3°N,116.2°E）的瑞利激光雷达具有589nm和532nm两个通道,将589nm通道用于计算,532nm通道作为参考.在150~250K区间等间隔选取多个温度初值,利用589nm通道反演60~70km高度范围内的大气温度廓线和大气密度廓线,利用参考密度廓线选取准确的温度初值,反演得到准确的大气温度廓线.将589nm通道和532nm通道反演的温度廓线相比较,发现二者具有较高的一致性.改进后的方法有效利用了信噪比较差的光信号,使589nm通道的温度探测上限从60km提高到70km.