基于随机文法的多功能雷达识别方法

 针对多功能雷达采用复杂体制而造成的辐射源不能正确识别问题,提出了一种基于随机文法(SG)的辐射源识别算法。该算法基于多功能雷达的句法模型,将威胁数据库中的多功能雷达文法分为随机正则文法(SRG)和随机上下文无关文法(SCFG)两种情况,并分别构造随机有限自动机(SFA)和随机下推自动机(SPDA)对测量辐射源进行识别。仿真实验表明,该方法不仅能识别出多功能雷达辐射源的型号及模式,而且能识别出雷达辐射源的功能状态,并进而推断出雷达辐射源的威胁等级。     

利用幅值信息的超视距雷达多路径概率数据互联算法

天波超视距雷达是通过电离层反射实现超视距广域监视的,其地理坐标系下的量测方程存在强非线性,同时由于电离层的不同分层,造成了多路径传播的严重问题,即同时存在多个量测模型。多路径概率数据互联(MPDA)滤波器将坐标配准与概率数据互联相结合,解决了超视距目标跟踪中的多路径传播问题,但在杂波环境下滤波跟踪精度不高。文中提出了一种基于信号幅值特征信息的MPDA算法(A-MPDA),当跟踪单一的、存在4种可能非线性量测的非机动目标时,仿真结果表明所提出的算法比标准MPDA有更好的跟踪精度。     

一种宽带阵列幅相与互耦误差联合校正算法

宽带数字阵列雷达接收通道中存在随频率变化的幅相误差和互耦误差,会严重影响雷达性能。针对这一问题,提出了一种宽带数字阵列幅相与互耦误差联合校正算法。首先选取通带内多个离散频点,对于每个频点,将幅相误差和互耦误差作为一个整体,采用基于子空间原理的窄带校正算法估计其阵列失真参数,并计算校正矩阵;然后将其组合起来,构成频域离散校正矩阵;最后基于最小二乘准则,设计了宽带有限长脉冲响应(FIR)校正滤波器矩阵。利用该矩阵,可实现通带范围内任意带宽入射信号的校正。计算机仿真实验验证了该算法的有效性。对实测数据的处理结果表明该算法在宽带数字阵列雷达系统中具有实用价值。     

P向量实现快速星图识别的方法

 提出了一种快速的星图识别方法。该方法识别时提取出描述观测三角形的一维特征量P,根据该值快速检索到对应的导航三角形,减少了计算过程。由于获得星点位置的时候存在误差,所以将一定误差范围内的三角形均作为待选三角形考虑。上述识别后引入了验证识别环节,保证识别的准确性。随机实验统计表明,同等星点位置噪声方差下,该方法和栅格算法相比识别率提高约1%,识别时间约为后者的1/5。     

基于低可探测性的参考航迹规划

根据分层规划思想,确定参考航迹是进行航迹规划时首先要解决的问题。在充分考虑雷达探测的各种环境因素及飞行器RCS方位分布特性的基础上,将雷达对目标发现概率作为参考航迹的一个重要评价指标,基于自适应进化算法,采用新的遗传算子,最终生成综合考虑雷达威胁和飞行距离的参考航迹。结果表明,该航迹规划模型能根据对低可探测性和航程的不...     

液体火箭发动机启动过程实时在线故障检测算法

利用神经网络技术实现了液体火箭发动机启动过程的非线性辩识；提出并实现了一种基于辩识误差检验的故障检测策略。经大量实际发动机热试车数据验证表明，所提出的检测算法十分有效。由于算法所利用的监测参数均系实际发动机地面试车中所测量的参数，且检测算法在线工作时计算量十分小，因而所提出并实现的检测算法可以直接应用于工程实际。     

Estimation of radar detection and false alarm probability

The accuracy with which detection and false alarm probabilities can be estimated with a limited amount of measured radar data is addressed. A simple simulation method for estimating the statistical performance of a radar detection system is presented. Confidence limits and a rule of thumb for accuracy for the estimated probabilities are presented along with procedures for calculating them. It is concluded that the minimum value of N used in a detection radar signal simulation should be 10/P_FA when the simple simulation method is used, where P_FA is the probability of false alarm, and that a value closer to 100/P _FA is preferable     

Multiple model particle flter track-before-detect for range ambiguous radar

The middle pulse repetition frequency（MPRF）and high pulse repetition frequency（HPRF）modes are widely adopted in airborne pulse Doppler（PD）radar systems,which results in the problem that the range measurement of targets is ambiguous.The existing data processing based range ambiguity resolving methods work well on the condition that the signal-to-noise ratio（SNR）is high enough.In this paper,a multiple model particle flter（MMPF）based track-beforedetect（TBD）method is proposed to address the problem of target detection and tracking with range ambiguous radar in low-SNR environment.By introducing a discrete variable that denotes whether a target is present or not and the discrete pulse interval number（PIN）as components of the target state vector,and modeling the incremental variable of the PIN as a three-state Markov chain,the proposed algorithm converts the problem of range ambiguity resolving into a hybrid state fltering problem.At last,the hybrid fltering problem is implemented by a MMPF-based TBD method in the Bayesian framework.Simulation results demonstrate that the proposed Bayesian approach can estimate target state as well as the PIN simultaneously,and succeeds in detecting and tracking weak targets with the range ambiguous radar.Simulation results also show that the performance of the proposed method is superior to that of the multiple hypothesis（MH）method in low-SNR environment.     

基于MISG算法的风力发电机液压变桨系统故障诊断

针对受状态延时影响的风机变桨系统故障诊断,提出了一种基于多新息随机梯度(MISG)的故障诊断方法。该方法将复杂系统转化为状态空间模型,并建立系统辨识模型。将新息标量扩展成新息向量改善算法精度,利用系统发生故障引起参数改变的特征,算法对风机状态延时变桨系统完成参数估计,将系统故障诊断问题转换为系统辨识问题。仿真所得结果验证该方法可以达到诊断风机状态延时变桨系统故障的目的。     

A multipath data association tracker for over-the-horizon radar

A new algorithm, multipath probabilistic data association (MPDA), for initiation and tracking in over-the-horizon radar (OTHR) is described. MPDA is capable of exploiting multipath target signatures arising from discrete propagation modes that are resolvable by the radar. Nonlinear measurement models exhibiting multipath target signatures in azimuth, slant range, and Doppler are used. Tracking is performed in ground coordinates and therefore depends on the provision of estimates of virtual ionospheric heights to achieve coordinate registration. Although the propagation mode characteristics are assumed to be known, their correspondence with the detections is not required to be known. A target existence model is included for automatic track maintenance. Numerical simulations for four resolvable propagation modes are presented that demonstrate the ability of the technique to initiate and maintain track at probabilities of detection of 0.4 per mode in clutter densities for which conventional probabilistic data association (PDA) has a high probability of track loss, and suffers from track bias. A nearest neighbor version of MPDA is also presented     

基于FRFT和相位差分算法的信号特征提取

基于分数阶傅里叶变换(Fractional Fourier Transform,FRFT)算法的信号识别方法已广泛应用于雷达信号处理领域,相位差分算法对于检测相位编码信号尤为高效。基于 FRFT和相位差分法的信号检测算法已被提出,但在较低的信噪比下该算法并不能准确识别 LFM、LFM-BPSK信号。针对低信噪比背景下该算法性能较差的问题,给出 1种改进的算法,并通过加入多相编码信号的识别,扩大其适用范围。仿真验证结果表明,提出的算法不仅较原有算法能在较低信噪比条件下有效检测 LFM、BPSK、Frank3种单一调制方式的信号,还能检测出复杂调制的 LFM-BPSK信号。     

Behavior pattern mining based on spatiotemporal trajectory multidimensional information fusion

Trajectory data mining is widely used in military and civil applications, such as early warning and surveillance system, intelligent traffic system and so on. Through trajectory similarity measurement and clustering, target behavior patterns can be found from massive spatiotemporal trajectory data. In order to mine frequent behaviors of targets from complex historical trajectory data, a behavior pattern mining algorithm based on spatiotemporal trajectory multidimensional information fusion is proposed in this paper. Firstly, spatial–temporal Hausdorff distance is proposed to measure multidimensional information differences of spatiotemporal trajectories, which can distinguish the behaviors with similar location but different course and velocity. On this basis, by combining the idea of k-nearest neighbor and density peak clustering, a new trajectory clustering algorithm is proposed to mine behavior patterns from trajectory data with uneven density distribution. Finally, we implement the proposed algorithm in simulated and radar measured trajectory data respectively. The experimental results show that the proposed algorithm can mine target behavior patterns from different complex application scenarios more quickly and accurately compared to the existing methods, which has a good application prospect in intelligent monitoring tasks.     

基于多级维纳滤波的双基地MIMO雷达多目标定位方法

为了降低双基地多输入多输出(MIMO)雷达目标定位过程中的计算复杂度,避免进行占主要计算量的协方差矩阵特征值分解或奇异值分解和二维空间谱的峰值搜索,将多级维纳滤波(MSWF)应用于双基地MIMO雷达多目标定位的研究中。利用MSWF的前向递推原理,得到信号子空间;然后利用ESPRIT算法估计发射角(DOD)和接收角(DOA),且DOD和DOA自动配对,实现了多目标交叉定位。分析了本文算法和ESPRIT算法的计算复杂度,并通过仿真实验及性能分析验证本文算法的有效性。理论分析和实验结果表明:本文算法在保证二维方位角估计性能的基础上,显著地降低了计算复杂度,缩短了运算时间,更加符合MIMO雷达信号实时处理的要求。     

非正侧视阵列机载雷达多空间角补偿算法

 非正侧阵列机载雷达的杂波分布随距离变化而变化,各距离单元的杂波分布不再满足独立同分布条件,造成统计型空时自适应处理(STAP)处理器性能下降。本文提出了一种多空间角补偿(MSAC)的非正侧视机载雷达杂波抑制方法,该方法先通过角度-多普勒补偿(ADC)预处理以消除在谱中心处的杂波非均匀,然后采用MSAC法在多个多普勒方向使参考单元和待检测单元的杂波谱保持一致,从而进一步消除在其余方位的杂波非均匀。仿真结果表明了该方法的性能明显优于ADC法,且运算量增加不多。     

Fault diagnosis based on measurement reconstruction of HPT exit pressure for turbofan engine

Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.     

基于S变换的时频特征提取与目标识别

目标的时间-频率联合分布能够很好地反映目标物理结构特征,可以作为雷达目标识别的一个有效手段。针对现有时频分析方法存在的识别率低和抗噪性能差等问题,提出一种基于S变换的空间目标回波信号电磁特征提取与识别方法。首先对目标的雷达回波进行时频分析,得出在较大方位角变化范围内和不同信噪比情况下,目标S变换的时频分布具有相对不变性的结论;然后基于这种稳定的时频分布特征,采用最小贴近度的方法进行分类识别。针对不同目标模型的仿真结果表明,该方法的识别率高于其他时频分析方法并且具有很好的鲁棒性。     

基于TD-RLS算法的四旋翼飞行器系统参数辨识

在对飞行器气动参数进行辨识的过程中,常需要对获得的数据求微分或二次微分,而利用差分法求微分会放大噪声的影响,引入滤波器抑制噪声又会产生相位延迟.针对这一问题,提出了一种跟踪微分器-递推最小二乘(TD-RLS)辨识算法.首先,建立了悬停条件下四旋翼飞行器的系统模型;然后,基于实验室四旋翼平台飞行试验实测数据,将TD-RLS算法应用于飞行器参数辨识.最终的辨识结果表明,在四旋翼飞行器悬停或者小角度飞行条件下,该方法可以实时获得比较精确的系统模型.     

PARAMETER IDENTIFICATION METHOD OF NONLINEAR JOINTS

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Sliding Window Detection Probabilities

A method is proposed for computing sliding window detection probabilities which have applications in track-while-scan acquisition logic and radar detection theory. The sliding window probability is the probability of achieving m successes out of n consecutive events at least once by the Nth opportunity. Expressions are derived for these probabilities as a function of N and p (the per-event success probability) for 1 ? n ? 4 and m ? n. Tabulated results are presented for the mean and standard deviation of the detection delay associated with each m/n logic.