机载火控雷达距离拖引目标的交互式多模型跟踪方法

针对机载火控雷达中可能出现的距离门拖引欺骗,给出了一种基于交互式多模型的目标跟踪方法。把该方法和常规的单目标跟踪方法进行了仿真比较。结果表明,该方法能充分利用欺骗回波测量,对释放距离拖引欺骗干扰的目标维持较稳定地跟踪,并能获得较高的目标跟踪精度。     

基于重构算法的一种微弱目标检测后处理方法

 重点研究了形态学重构算法在微弱目标检测和跟踪中的应用，主要体现在对原始图像的背景估计过程和检测后处理过程。对于经过背景估计和二值化后的图像，若直接进行跟踪算法，由于虚警点数目太多，会严重影响跟踪算法的效率，同时也给跟踪结果造成了负面效应。因此，考虑在二值化之后，跟踪之前，引进后处理过程，以消除虚警点。在已知目标大致尺寸的情况下，选用不同的两个标记重构，同时消除小于目标的虚警点和大于目标的虚假目标。     

单天基平台测向的空间非合作目标跟踪

针对仅含角度测量信息的单个天基平台可观测性较弱的问题,提出了一种含脉冲机动检测的空间非合作目标跟踪算法,并设计了非合作目标实时跟踪数据处理流程.该算法利用抗差估计技术和UKF（Unscented Kalman Filter,无迹卡尔曼滤波）算法构造目标跟踪滤波器,并综合残差多项式拟合和新息分布特征等方法实现目标机动检测,在天基平台观测信息类型有限和观测几何较差的情况下,可以同时排除孤立野值和成片测量野值的影响,实现非合作机动目标的连续稳定跟踪.数值实验验证了算法的可行性和有效性,也表明了跟踪精度和可靠性与测量精度密切相关.     

基于Doppler估计的弹载接收机抗欺骗干扰研究

GNSS接收机在军用方面尤其是高精度制导武器中的应用日益增强.针对卫星信号易受敌方欺骗信号干扰的问题,设计一种基于Doppler频率估计的弹载接收机抗欺骗干扰的方法.首先分析了欺骗干扰和真实信号的Doppler变化特点;然后在捕获阶段利用残留信号检测存在欺骗干扰的卫星编号;最后根据弹载的高动态特性,在跟踪阶段采取扩展 Kalman 滤波器(EKF)进行载波Doppler频率估计,并根据Doppler变化的相似性提取出欺骗信号.通过仿真实验验证,该方法可以有效排除欺骗信号的干扰.     

基于STFRFT的LFM引信抗欺骗干扰方法

针对线性调频脉冲压缩引信易受转发式假目标欺骗干扰问题,提出了基于短时分数阶傅立叶变换(STFRFT)的抗欺骗干扰方法。首先,通过分数阶傅立叶变换将回波信号与欺骗干扰各分量信号进行分离;再利用相同调频率的LFM信号经短时分数阶傅立叶变换后最大幅值与窗函数宽度成线性关系,而不同调频率的最大幅值不随窗函数宽度变化的特点,有效分辨假目标欺骗干扰,正确检测目标回波信号;最后,通过仿真证明了方法的正确性,并验证所提方法具有良好的抗欺骗干扰效果。     

复杂环境下一种基于改进核相关滤波的视觉鲁棒目标跟踪方法

目标跟踪在自动驾驶和智能监控系统等实时视觉应用中发挥着重要作用。在遮挡、相似干扰等情况下，传统的基于相关滤波的跟踪算法容易发生漂移，鲁棒性有待进一步提高。基于此，提出了一种扩展特征描述的检测辅助核相关滤波目标跟踪架构。首先，在传统的核相关滤波目标跟踪算法的基础上，通过目标检测辅助对跟踪结果进行质量判断，实现对遮挡以及目标丢失的判别；然后通过拓展特征模板的构建与匹配，实现抗干扰相似目标判断及目标重定位；最终，以行人跟踪为例进行了试验，分别通过OTB数据及验证试验和移动机器人平台视觉跟踪验证试验，验证了算法的可行性，并对算法的跟踪性能进行了测试。试验结果表明，所提方法能够稳定地跟踪移动目标，对遮挡、相似干扰具有较强的鲁棒性。     

高测量频率条件下采用IMM方法跟踪机动目标

利用雷达系统跟踪机动目标,当测量频率很高时,测量噪声将显著相关。本文提出一种简单的去相关方法来改良互作用多模型算法(IMM),用于测量噪声相关情况下的机动目标跟踪。我们发现这种去相关法可以明显提高系统性能,特别是对于速度和加速度的估计。     

北斗卫星导航欺骗与抗欺骗技术现状探讨

作为全球四大卫星导航系统之一,北斗也容易遭受恶意欺骗干扰.在北斗赋能各行各业的时代,守护北斗就是守护我们的家园.对欺骗技术和抗欺骗技术原理分别进行了介绍,讨论了不同的欺骗手段对接收机的影响,从接收机捕获通道和跟踪通道的欺骗特征详细介绍了几种抗欺骗技术,并重点阐述了当前欺骗和抗欺骗技术的现状,最后展望了未来的欺骗技术和欺骗防御技术,希望对卫星导航接收机的抗欺骗干扰技术工程化应用提供思路.     

T／R－R型双基地系统分段跟踪技术的研究

根据Ｔ／Ｒ－Ｒ型双基地系统在受到由弱到强的干扰影响时,其可用的测量量不同,有必要研究各种干扰模式下应采用的跟踪算法,提出了分段跟踪技术,充分利用了不同干扰强度时Ｔ／Ｒ站和Ｒ站的测量数据,提高了对三维运动目标的跟踪精度。通过典型目标航迹的计算机仿真,对算法性能做了评估。     

面向目标的概率多假设跟踪算法

 概率多假设跟踪(PMHT)算法由于其计算量与目标和量测的个数成线性关系而成为一种重要的数据关联方法,但该算法采用的是一种面向量测的参数模型,容易受到杂波的干扰。针对这个问题,提出一种面向目标的PMHT（TO/PMHT）算法,将量测与目标的距离作为权重,使计算出的后验关联概率能够真实地反映量测和目标的关联可能性。通过多种典型环境的仿真计算表明：TO/PMHT算法和面向量测的PMHT算法相比,跟踪性能有了明显的提高;与多假设跟踪(MHT)算法相比,在保持跟踪性能的同时,极大地提高了计算效率。     

Fence vibrations [intruder detection]

Many Perimeter Intrusion Detection Systems (PIDS) use microphonic sensors mounted on fences to detect intruder attacks. Vibrations in the fence are detected and analysed to determine whether they represent an intrusion attempt. The signals from the fence are processed to filter out as many false alarms as possible. It is important that the output from the sensors is linear along the fence, to ensure that there is no point on the perimeter less sensitive to intruder attack. The investigation reported in this paper aims to discover whether the performance of acoustic detection systems could be improved through research into fence acoustics. Using models of fence vibrations, sensors could be positioned to obtain a more linear response. In addition, through knowledge of the fence vibrations produced by both real attacks and the typical causes of false alarms, a system could be designed which could better distinguish between them, giving a lower false alarm rate and increased detection performance. Characteristic profiles were found for the different forms of attack to the fence. Although the investigation is still in its early stages, these attack profiles suggest that a new type of detection system could be designed based on profile recognition     

False alarm effects on estimation in multitarget trackers

An analysis of false alarm effects on tracking filter performance in multitarget track-while-scan radars, using variable correlation gates, is presented. The false alarms considered originate from noise, clutter, and crossing targets. The dimensions of the correlation gates are determined by filter prediction and measurement error variances. Track association is implanted either by means of a distance weighted average of the observations or by the nearest neighbor rule. State estimation is performed by means of a second-order discrete Kalman filter, taking into consideration random target maneuvers. Measurements are made in polar coordinates, while target dynamics are estimated in Cartesian coordinates, resulting in coupled linear filter equations. the effect of false alarms on the observation noise covariance matrix, and hence on state estimation errors, is analyzed. A computer simulation example, implementing radar target tracking with a variable correlation gate in the presence of false alarms, is discussed     

残差滤波及其在密集多回波环境下机动多目标跟踪中的应用

 修正概率数据关联滤波（MPDAF）是目前解决密集多回波环境下机动多目标跟踪较为有效的方法,但当回波密度增高时,该方法容易失跟。本文针对此特点,在MPDAF基础上,提出了残差滤波（RF）方法,分别从理论和Monte carlo仿真两方面揭示了RF与数据关联的内在机理,结果表明该方法能大幅度提高跟踪滤波器捕捉目标和剔除关联域内多余回波的能力以及跟踪的性能,是一种解决高密集多回波环境下机动多目标跟踪的有效方法。     

Tracking considerations in selection of radar waveform for rangeand range-rate measurements

The conventional approach for tracking system design is to treat the detection and tracking subsystems as completely independent units. However, the two subsystems can be designed jointly to improve system (tracking) performance. It is known that different radar signal waveforms result in very different resolution cell shapes (for example, a rectangle versus an eccentric parallelogram) in the range/range-rate space, and that there are corresponding differences in overall tracking performance. We develop a framework for the analysis of this performance. An imperfect detection process, false alarms, target dynamics, and the matched filter sampling grid are all accounted for, using the Markov chain approach of Li and Bar-Shalom. The role of the grid is stressed, and it is seen that the measurement-extraction process from contiguous radar "hits" is very important. A number of conclusions are given, perhaps the most interesting of which is the corroboration in the new measurement space of Fitzgerald's result for delay-only (i.e., range) measurements, that a linear FM upsweep offers very good tracking performance     

Knowledge-based system for multi-target tracking in a littoral environment

The paper addresses how to efficiently exploit the knowledge-base (KB), e.g. environmental maps and characteristics of the targets, in order to gain improved performance in the tracking of multiple targets via measurements provided by a ship-borne radar operating in a littoral environment. In this scenario, the nonhomogeneity of the surveillance region makes the conventional tracking systems (not using the KB) very sensitive to false alarms and/or missed detections. It is demonstrated that an effective use of the KB can be exploited at various levels of the tracking algorithms so as to significantly reduce the number of false alarms, missed detections, and false tracks and improve true target track life. The KB is exploited at two different levels. First, some key parameters of the tracking system are made dependent upon the track location, e.g., sea, land, coast, meteo zones (i.e., zones affected by meteorological phenomena) etc. Second, modifications are introduced to cope with a priori identified regions nit hi high clutter density (e.g. littoral areas, roads, meteo zones etc.). To evaluate the behavior of the proposed knowledge-based tracking systems, extensive results are presented using both simulated and real radar data     

Determination of Failure Thresholds in Hybrid Navigation

A systematic approach for the determination of failure thresholds for hybrid navigation systems is described. Cost functions which reflect the importance assigned to the consequences of false and missed alarms are minimized. The false alarm probability is obtained as a function of the threshold magnitude by observing the statistical behavior of the instrument outputs in the normal operating mode. The missed alarm probability is obtained by determining the sensitivity of navigation error performance to instrument error sources. Two cost functions are considered. To illustrate this method, failure detection and identification (FDI) thresholds are determined for the Space Shuttle Approach and Landing Test flight.     

A robust exponential mixture detector applied to radar

Exponential mixture probability density functions (pdfs) are shown to be useful models of radar sea clutter. The variability of certain parameters leads to estimation error and degradation in the performance of detection algorithms derived from this model. Robust implementations are introduced by assuming that parameters are known within certain intervals and selecting values to prevent an excessive number of false alarms. An empirical study demonstrates an average 6-9 dB gain in comparison with a constant false-alarm rate (CFAR) processor     

Track formation with bearing and frequency measurements in clutter

Target motion analysis from a narrowband passive sonar that yields bearing and frequency measurements in the presence of false detections (clutter) in a low-SNR (low signal-to-noise ratio) environment is discussed. The likelihood function used to compute the maximum likelihood estimation of the track parameters (localization and frequency) incorporates the false alarms via the probabilistic data association technique. The Cramer-Rao lower bound is calculated and results obtained from simulations are shown to be compatible with it. A test of track acceptance is also presented     

Radio Interference in Helicopter-Borne Pulse Doppler Radars

Radio interference generated in a helicopter-borne pulse Doppler radar system due to rotating blades is analyzed for the case that blades are located in the far field region of the radar antenna. A first-order estimate of the blade interference power spectrum is obtained as a function of antenna depression angle and radar (helicopter) altitude and speed. Numerical calculations show that blade interference is very weak compared with the direct ground clutter. It extends, however, into the clutter-free region which causes false alarms and degrades the radar performance.