一种基于新三维随机Hough变换的航迹起始算法

针对雷达跟踪多目标时,目标点迹受杂波、噪声等因素影响,航迹起始难度大的问题,利用三维空间直线表示方法提出了一种4参数三维Hough变换算法.该算法是对传统二维Hough变换的拓展,它结合了传统的二维随机Hough变换理论,是一种新的三维随机Hough变换算法.通过该算法对理论数据和实测数据进行验证,结果表明,对于航迹区别较大的目标,该算法的航迹起始成功概率为98.5％;对于空间航迹相近的目标,该算法可成功将目标航迹从杂波中提取出来,虽然可能会出现航迹混淆,但利用目标先验信息可解决该问题,实现航迹起始.     

交叉航路碰撞风险研究

航路上航班的碰撞风险问题是目前空域规划的主要研究问题之一,就交叉航线的碰撞风险问题进行了研究.首先推导出交叉航路碰撞概率计算公式,然后结合概率论和划设保护区的方法对交叉航线的碰撞风险问题进行了研究,最后用自主开发的"空域安全评估方法的研究与应用"软件对上海区域内的某交叉航线的碰撞风险进行了仿真计算.为交叉航路的碰撞风险计算提供了简单易行的方法.     

基于高斯混合模型的航迹抗差关联算法

针对雷达系统误差时变、上报目标不完全一致等复杂场景下目标航迹关联问题,采用高斯混合模型（GMM）与航迹间拓扑信息相结合的方法实现航迹抗差关联。将航迹关联问题转化为图像匹配中的非刚性点集匹配问题,建立对非同源航迹具有鲁棒性的高斯混合模型,根据航迹间的邻域拓扑信息决定高斯混合模型中各高斯组成部分的权重,利用期望最大值（EM）算法求解高斯混合模型的最优闭合解,在期望步（E-step）阶段求解航迹的对应关系,在最大化步（M-step）阶段求解非同源航迹比例,最后进行航迹关联判决以获得关联结果。仿真结果表明,该算法在不同系统误差、目标分布密度、探测概率等环境下具有较好有效性和鲁棒性。     

Association of tracks from over the horizon radar

In Over-The-Horizon Radar (OTHR), multiple ionospheric layers cause several tracks per target to be observed. This effect causes ambiguities in target identification and track coordinate registration. A pattern classification approach is proposed for associating tracks. Neural networks and statistical methods are applied to combine track affinities and associate pairs of tracks. The proposed approach provides a practical and efficient way of dealing with multiple track association when the number of targets is large and optimal. Bayesian hypothesis testing is not practical     

Track monitoring when tracking with multiple 2D passive sensors

A fast method of track monitoring is presented which determines what tracks are good and what tracks have had data association problems and should be eliminated. The philosophy of tracking in a dense target environment with limited central processing unit (CPU) time is to acquire the targets, track them with as simple a filter as will meet requirements, and monitor the tracks to determine if they are still tracking a target or are tracking incorrect returns and should be terminated. After termination the true targets are reacquired. However, it is difficult to determine from simple track monitoring the correct interpretation of a poor track. Poor tracks can be a result of a sensor failure, target maneuver, or incorrect data association. The author describes track monitoring and provides a solution to this dilemma when tracking with multiple two-dimensional passive sensors. The method is much faster than other monitoring methods.<>     

基于航迹分割的航空器噪声预测模型

根据航空器的航迹来预测其影响区域的噪声情况,基于航迹的几何特性,将航迹分成直线段航迹和曲线段航迹两个基本航迹元素;确定了直线段和曲线段的各自影响范围之后,分别计算各航迹段对它们影响区域的噪声值贡献情况;统计了各个航迹段对监测点的噪声影响之后,综合得出整个航迹段对监测点的噪声影响,从而建立了航空器航迹噪声预测的模型。将该模型计算的结果分别和软件模拟数据、实际监测数据进行对比分析,发现该模型在航迹段内对监测点噪声均值的预测较为准确,监测点噪声峰值预测结果更接近实测数据。     

民用飞机飘降总轨迹计算分析

飘降分析是民用飞机性能计算中的重要内容,目前波音飞机性能手册中只提供飞机的飘降净轨迹,本研究用计算机FORTRAN90语言编制程序实现了积分计算,以B757—200／RB211-535E4为算例对飘降总轨迹做了计算,并分析了温度、飞机重量、初始巡航高度等因素对飞机飘降总轨迹的影响。     

Software Techniques for Detecting False SSR Tracks

The problem of detecting false secondary surveillance radar (SSR) tracks due to electromagnetic reflections is discussed. An approach via software is considered and some algorithms for the SSR tracks detection are proposed. Some experimental results are reported.     

Architectures and algorithms for track association and fusion

Target tracking using multiple sensors can provide better performance than using a single sensor. One approach to multiple target tracking with multiple sensors is to first perform single sensor tracking and then fuse the tracks from the different sensors. Two processing architectures for track fusion are presented: sensor to sensor track fusion, and sensor to system track fusion. Technical issues related to the statistical correlation between track estimation errors are discussed. Approaches for associating the tracks and combining the track state estimates of associated tracks that account for this correlation are described and compared by both theoretical analysis and Monte Carlo simulations     

基于傅里叶变换的航迹对准关联算法

研究了在组网雷达存在系统误差情况下的目标航迹关联问题,理论分析了雷达系统误差对目标航迹的影响,并将该影响表示为目标航迹的旋转和平移量。在此基础上,提出了一种基于傅里叶变换的系统误差配准前航迹对准关联算法,该算法将组网雷达的航迹数据看做为一种整体信息,采用傅里叶变换理论来估计和补偿组网雷达目标航迹数据到融合中心航迹数据的相对旋转量和平移量,将雷达网中雷达上报的目标航迹数据对准到融合中心,从而不依赖于估计雷达网系统误差,实现了误差配准前的航迹准确关联,能够为后端的系统误差配准提供可靠的关联目标航迹数据。     

Joint integrated probabilistic data association: JIPDA

A new recursive filter for multi-target tracking in clutter is presented. Multiple tracks may share the same measurement(s). Joint events are formed by creating all possible combinations of track-measurement assignments and the probabilities for these joint events are calculated. The expressions for the joint event probabilities incorporate the probabilities of target existence of individual tracks, an efficient approximation for the cluster volume and a priori probability of the number of clutter measurements in each cluster. From these probabilities the data association and target existence probabilities of individual tracks are obtained, which allows track state update and false track discrimination. A simulation study is presented to show the effectiveness of this approach.     

Effectiveness of track monitoring with multiple 2D passive sensors

An analytical technique is presented which can be used to evaluate the effectiveness of the track monitoring scheme presented by J.A. Roecker (see ibid., vol.27, no.6, p.872-6, Nov. 1991) in detecting false track-to-track (ghost track) assignments without the use of simulations. It is shown that when two tracks are traveling in parallel and in the direction of the inclination angle, it is impossible to determine which tracks to associate. However, track monitoring is effective under all other circumstances. A tracking algorithm designer can use this technique to determine the length of time before track-to-track initiation for good ghost track rejection. This technique also determines the probability of accepting ghost tracks during mature track monitoring.<>     

Low-Level Signal Detection Using a New Transform Class

A system is developed to detect tracks crossing two-dimensional noise fields. This is accomplished by filtering and integration of signal power in the frequency domain of a new class of generalized transforms which include the FFT and FBT as limiting forms. If the track is essentially parallel to a transform axis and if filters are derived from hard-limited linear approximations to tracks, the FBT offers considerable hardware economy over the FFT in the mechanization algorithm.     

Multi-Target/Multi-Sensor Tracking using Only Range and Doppler Measurements

A new approach is described for combining range and Doppler data from multiple radar platforms to perform multi-target detection and tracking. In particular, azimuthal measurements are assumed to be either coarse or unavailable, so that multiple sensors are required to triangulate target tracks using range and Doppler measurements only. Increasing the number of sensors can cause data association by conventional means to become impractical due to combinatorial complexity, i.e., an exponential increase in the number of mappings between signatures and target models. When the azimuthal resolution is coarse, this problem will be exacerbated by the resulting overlap between signatures from multiple targets and clutter. In the new approach, the data association is performed probabilistically, using a variation of expectation-maximization (EM). Combinatorial complexity is avoided by performing an efficient optimization in the space of all target tracks and mappings between tracks and data. The full, multi-sensor, version of the algorithm is tested on simulated data. The results demonstrate that accurate tracks can be estimated by exploiting spatial diversity in the sensor locations. Also, as a proof-of-concept, a simplified, single-sensor range-only version of the algorithm is tested on experimental radar data acquired with a stretch radar receiver. These results are promising, and demonstrate robustness in the presence of nonhomogeneous clutter.     

空基多雷达航迹抗差关联算法

基于高斯随机矢量统计特性,推导出一种适用于探测距离较远、系统误差时变、雷达上报目标不一致等复杂环境的空基多雷达航迹抗差关联算法。分解航迹距离矢量,对消系统误差矢量得出适用于3个及3个以上雷达的航迹抗差关联条件和流程。分别设置了目标密集程度、随机误差和系统误差适应性实验验证算法性能。仿真结果表明所提算法的关联准确性和复杂环境适应性相比现有的基于参照拓扑特征的航迹关联算法（RET算法）和基于距离检测的可信关联算法（confidential算法）有较大幅度的提升。     

Detection of weak, subpixel targets using mesh-connected cellularautomata

Effective use of military cellular automata such as military data array processor (MilDAP) and geometric arithmetic parallel processor (GAPP), in weak, subpixel target detection is shown to be possible by using new signal processing regimes based on binary ranking filter theory. By using binary ranking filters, the MilDAP can furnish 6 dB of processing gain against white Gaussian noise while monitoring from one to four million potential target tracks at 10-40 frames/s. GAPP is shown to be capable of monitoring 3.7 million tracks over 216×384 detectors at 14000 frames/s and, in a time sharing mode, 15 million tracks over 432×768 detectors at 24 frames/s. The special case of threatening targets is discussed, as well as alternate cellular architectures which use multidimensional binary ranking filters in multidimensional coordinate systems     

基于区实混合序列相似度的异步不等速率航迹关联算法

在分布式多目标跟踪系统中,由于局部传感器开机时间、采样频率以及通信延迟不同等原因,导致来自各传感器的局部航迹往往是异步不等速率的。目前一般的方法是先进行时域配准再进行航迹关联,但是在同步化的过程中,航迹估计值的误差会发生传播,影响航迹关联的性能。针对此问题,提出了一种基于区实混合序列相似度的异步不等速率航迹关联算法。算法首先通过区间数-实数混合序列变换(IRST)得到等长度的航迹行为序列,然后定义一种新的序列差异信息度量,得到混合序列的相似度,以此进行航迹关联判定。仿真实验表明,该算法可以有效地解决异步不等速率航迹关联问题,并且通信延迟和数据乱序对算法性能的影响不明显。     

Bayesian tracking of two possibly unresolved maneuvering targets

The paper studies the problem of maintaining tracks of two targets that may maneuver in and out formation flight, whereas the sensor and measurement extraction chain produces false and possibly unresolved or missing measurements. If the possibility of unresolved measurements is not modelled then it is quite likely that either the two tracks coalesce or that one of the two tracks diverges on false measurements. In literature a robust measurement resolution model has been incorporated within an interacting multiple model/multiple hypothesis tracking (IMM/MHT) track maintenance setting. A straightforward incorporation of the same model within an IMM and probabilistic data association (PDA)-like hypothesis merging approach suffers from track coalescence. In order to improve this situation, the paper develops a track-coalescence avoiding hypotheses merging version for the two target problem considered. Through Monte Carlo simulations, the novel filters are compared with applying hypotheses merging approaches that ignore the possibility of unresolved measurements or track-coalescence.     

Association of DF Bearing Measurements with Radar Tracks

The problem of associating direction finding (DF) bearingmeasurements with radar tracks is formulated as a multiplehypothesis testing problem. A simple decision rule for associating aset of DF bearing measurements with no radar track or one of mpossible radar tracks was developed using a combination of Bayesian and Neyman-Pearson approaches. The decision algorithmwas checked using both computer simulations and experimentaldata. Finally, a multiplatform algorithm was formulated and tested,using a combination of real and synthetic data.     

海上目标雷达与 AIS航迹时空匹配方法

针对海上目标的雷达与船舶自动识别系统(Automatic Identification System,AIS)中,航迹之间存在的时空不匹配现象,提出了在空间对准之后结合海上航迹运动特点,对 AIS航迹数据进行插值对准雷达目标航迹的方法,在解决雷达与 AIS航迹之间时空不匹配问题的同时,最大程度减小插值误差。该方法根据船舶航向变化率,结合航速航向法和内插外推法的优势,针对不同航迹特点自动选择最佳的插值配准方法,实现海上目标的雷达与 AIS航迹点的自动插值和时空对齐。仿真实验结果表明,所提方法针对海上目标复杂运动,可以自动匹配选择最佳插值方法,有效降低误差,实现雷达与 AIS航迹之间的时空匹配。