Emitter number estimation from pulse trains using the GIC

An information theoretic criterion based approach for estimating the number of emitters from a set of interleaved pulse trains is proposed. In the approach, a new pulse signal model is formulated to handle large number of pulses. The approach is based on the application of the general information criteria (GIC) and has the advantage of not requiring any threshold setting procedures. When compared with classical information theoretic criterion based approaches, the GIC-based approach is more flexible, and it does not involve any computationally sophisticated maximum likelihood estimator. Computer simulations are used to demonstrate the effectiveness of the proposed approach.     

Moving Emitter Classification

One of the problems that plague emitter location systems is the presence of data from emitters that are in motion. If this motion is not detected, erroneous location estimates and filled data files result. An algorithm to classify an emitter as moving or stationary is presented along with extensive illustrations and results based upon simulated data.     

基于慢特征密度聚类的气路异常检测方法

在结合核技巧、慢特征分析算法与密度聚类方法的基础上,提出了基于混合核慢特征分析和密度聚类的慢特征密度聚类算法,实现了基于民航发动机气路参数原始值的异常检测。核技巧的引入克服了慢特征分析法处理复杂数据时可能存在的维度爆炸问题,充分利用不同核函数的特点和慢特征分析的优势从气路参数原始值中提取出随时间变化最缓慢的特征作为密度聚类算法的输入,最终筛选出异常值。经实验对比发现,该方法针对某些异常拥有最好的聚类效果和最低的虚警率,尤其是检测可调放气活门系统异常时虚警数量不到样本总数量的0.5%,是一种有效的方法。      

Accuracy of source localization using multipath delays

The depth and range of underwater source can be estimated from measurements of propagation delay differences along multiple propagation paths. The accuracy of depth and range estimation using the Cramer-Rao lower bound is studied. The formulas derived can be used in conjunction with a propagation medium (nonconstant velocity profile). Explicit formulas for the bounds are derived for the case of homogeneous medium (constant velocity profile). Numerical examples are presented to illustrate the behavior of these bounds     

Passive localization of moving emitters using out-of-planemultipath

The purpose of this work is to establish how a moving emitter, such as a jammer, can be localized by a passive receiver through the use of out-of-plane multipath signals reflected by the terrain. This is a novel localization technique that assumes no a priori knowledge of the localization of the multipath sources. The emitter parameters of range, heading, velocity, and altitude are estimated by exploiting the correlation between the direct-path signal and the delayed and Doppler modulated signals. Two basis assumptions about the scattering properties of the terrain lead to different maximum likelihood estimators (MLEs). The Cramer-Rao lower bounds (CRLB) are used to study estimator performance versus emitter velocity for each case. The proposed estimators are successfully demonstrated using field data collected at White Sands Missile Range (WSMR) during the DARPA/Navy Mountaintop program     

Fast data association using multidimensional assignment withclustering

We present a fast data association technique based on clustering and multidimensional assignment algorithms for multisensor-multitarget tracking Assignment-based methods have been shown to be very effective for data association. Multidimensional assignment for data association is an NP-hard problem and various near-optimal modifications with (pseudo-)polynomial complexity have been proposed. In multidimensional assignment, candidate assignment tree building consumes about 95% of the time. We present the development of a fast data association algorithm, which partitions the problem into smaller sub-problems. A clustering approach, which attempts to group measurements before forming the candidate tree, is developed for various target-sensor configurations. Simulation results show significant computational savings over the standard multidimensional assignment approach without clustering     

一种新的干扰源定位算法

在强压制性干扰条件下,三坐标雷达不能测得目标的斜距。由于量测误差的存在,通常情况下两部三坐标雷达所得到的方向矢量在空间不能相交。为了得到干扰源(或目标)的位置,文中提出了广义三角测量交叉定位算法。通过对广义三角测量交叉定位得到的两个定位点在最小均方误差准则(MMSE)下进行融合,最终得到目标的估计位置。MonteCarlo仿真结果表明该算法有较高的定位精度。     

带有编码解码系统的气象报警发射机

本文提出了一种新的气象报警系统，此系统采用数字编码和锁相频率合成技术，使传送信息由原来的１６种提高到４０９６种，实现了异频传送，并具有单呼和群呼功能，可适用于海洋气象报警、森林火灾报警、仓库遇险报警及单独信息交流。     

融合双谱特征的雷达辐射源个体识别方法

双谱以其独特的抑制高斯有色噪声的优势,被广泛应用于雷达辐射源识别分析。采用双谱对角线作为雷达辐射源识别特征可以很大程度上减少计算量,但是使用双谱对角线作为唯一识别特征,会损失信号的部分幅度和分布特征。针对上述问题,提出了 1种基于辐射源信号双谱提取二次特征的方法。取双谱作为二次特征提取对象,根据信息熵概念定义双谱奇异值全局熵和双谱对角线的幅度分散熵,联合双谱对角线及其积分结果作为特征向量,将其送入神经网络进行识别。实验表明,相比双谱对角线法,该方法对辐射源识别的正确率平均提高约 3.3%。     

基于两步最小二乘定位的偏差改进算法

针对传统最小二乘(LS)定位算法在噪声较大时会出现有偏估计的问题。首先详细推导了传统两步最小二乘算法在时差角度联合定位场景下的理论偏差,给出了出现偏差的原因;其次对误差均值加入二次约束条件,提出一种基于时差角度联合定位的改进算法,并详细推导新算法的理论偏差以及均方误差。相比于其他加限制条件的方法,新算法能有效降低估计偏差,另外由于其不需要进行特征值分解且能得到闭式解,计算复杂度较小。仿真结果表明,新算法在保持原有均方误差(MSE)的前提下能显著降低估计偏差,其定位偏差与最大似然估计器相当。     

基于相对方位信息和单间距测量的多智能体编队协同控制

由多个载体组成的多智能体系统对复杂环境具有更高的适应性,能够完成传统单个载体无法完成的任务。针对多智能体编队集结与队形移动跟踪问题,提出了一种改进的多智能体编队协同控制新算法。首先,以拒止环境下跟随智能体仅能通过光学传感器测量相对方位信息为任务背景,针对"领导者——第一跟随者"结构的多智能体编队,提出了基于相对方位信息与单间距测量的控制器,使得第一跟随者智能体可以追随移动的领导者智能体,并且可以通过改变与领导者智能体的间距对编队整体队形进行缩放控制。其次,提出一种了改进的分布式控制律,使得其他跟随者智能体可以仅通过两个相对方位信息完成编队飞行。然后,根据Lyapunov第二方法,构建了系统的能量函数,验证了所提出算法的稳定性。最后,通过数值仿真实验对所提算法进行了验证。仿真结果表明,基于该控制律多智能体系统能够完成编队集结、队形缩放和编队飞行的任务。     

Emitter Location Accuracy Using TDOA and Differential Doppler

Two methods for locating a radio or sonar transmitter are briefly described: time difference of arrival (TDOA). d differential Doppler. Two formulas are derived which relate the accuracy of the time and frequency measurements the ?one-sigma widths? of the lines of constant TDOA onstant differential Doppler on the surface of the FDOA.     

复杂电磁条件下的辐射源信号分离方法

针对复杂电磁环境下的辐射源信号分离问题,提出了一种基于数字信道化的分离方法。该方法首先基于滑动离散傅里叶变换设计了二级信道化结构,该结构可将不同类型的同时到达信号划分至不同信道;随后,设计跟踪滤波器对各信道输出峰值进行跟踪,利用跟踪结果完成时域交叠信号在时频域的分离,并在此基础上通过反变换获得不同信号的时域波形;仿真实验验证了文中所提算法的有效性。     

基于压缩协作表示的辐射源识别算法

针对低信噪比（SNR）条件下传统辐射源识别算法性能下降的问题,提出了基于压缩协作表示的识别算法,分别从特征提取和分类器设计两方面进行描述。首先将时域辐射源信号变换到二维时频域,通过图像处理方法提取高维特征列向量。经随机矩阵压缩到一定维度后,输入到提出的压缩协作表示分类器中得到识别结果。进而,对协作表示系数进行非负约束,提出了更符合实际应用场景的算法。仿真结果验证了所提算法的可行性与有效性,且在低信噪比条件下稳健性强、抗噪声干扰性能好、计算量较小、易于工程实现。     

滚动轴承摩擦力矩的乏信息模糊预报

滚动轴承摩擦力矩的波动具有不确定性,属于概率分布与趋势规律都未知的乏信息系统.这阻碍了对轴承摩擦力矩的小样本分析与总体把握.为此,以模糊集合理论为基础,从小样本入手,建立了航天轴承摩擦力矩参数的经验概率密度函数及其模糊预报模型,并对摩擦力矩的均值上界和最大值上界进行预报.对HKTA和HKTB两种轴承摩擦力矩参数的试验研究表明,在99%～100%置信水平下,预报结果与试验结果之间的误差很小,最大绝对误差仅为0.081 1个设定单位,最大相对误差仅为10.165%,可以满足航天工程的要求.      

基于模糊条件证据理论的雷达辐射源识别

基于不确定证据与不确定先验知识和谐的思想,利用模糊条件证据理论,给出一种融合模糊先验知识的新的雷达辐射源识别方法。首先,把雷达辐射源模糊观测数据表示为Dempster-Shafer（D—S）证据的随机集形式;然后,计算观测证据与模糊先验知识之间的和谐度;最后,利用模糊条件证据理论把需要融合的证据进行组合。这种方法可充分利用各种不同来源的信息,从而提高雷达识别的可靠性。     

Emitter Location Independent of Systematic Errors in Direction Finders

A scheme is suggested for the passive location of radio emitter position by using a mobile direction finder. The vehicle carrying the direction finder is made to maneuver such that the apparent direction of arrival is held constant. The resulting trajectory of the vehicle is a logarithmic spiral. The true direction of arrival can be obtained by monitoring the parameters of the spiral trajectory without using the value of the direction fimder reading. Two specific algorithms to eliminate direction finder bias are presented and their sensitivity to random errors in measurement assessed.     

改进 K-均值算法在雷达辐射源信号预分选中的应用

雷达辐射源信号分选是电子对抗领域一个关键技术,随着电子技术的发展,电磁环境日趋复杂,信号分选的难度越来越大,在这样的条件下,我们应该寻求新的解决问题的方法.本文首先概述了雷达辐射源信号分选意义、系统组成和分选流程,然后介绍了改进 K-均值算法.为了有效实现信号分选,提出了基于改进K-均值算法的信号分选方法,该方法可对到达角、载频和脉宽参数进行分选.最后进行了仿真实验,结果表明该方法实现简单,分选效果较好     

磁阻型电磁发射系统的发射体形态优化研究

根据磁阻型电磁发射原理及驱动线圈内部磁场分布情况,推导了基于线性化电感的发射体运动模型,给出了一个用于计算发射体在线圈中的受力和加速情况的简化方法,并归纳了部分影响因素。使用ANSYS Maxwell仿真软件对不同形状发射体在线圈中的受力变化进行仿真分析。研究结果为实际磁阻型电磁发射中应用的发射体形状设计提供了参考。     

一种新的基于TDOA与GROA的无源定位算法

针对基于到达时间差(TDOA)与到达增益比(GROA)的辐射源无源定位问题,提出了一种新的定位算法。首先通过引入一个中间变量,根据TDOA和GROA测量模型,构造一个约束加权最小二乘(CWLS)估计。由于这个CWLS问题是非凸的优化问题,现有的方法不能很好地求解。为此,提出了一种有效的方法可以求解到其全局最优解。最后,所提算法被推广到观测站存在自定位误差时的定位求解。计算机仿真结果验证了所提算法能够获得优于传统两步加权最小二乘法(2WLS)的定位性能,能够在更大的噪声条件下达到克拉美罗下界(CRLB)。