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.     

Maximum likelihood azimuth estimation applied to SSR/IFF systems

A conventional (nonmonopulse) secondary surveillance radar (SSR) is significantly cheaper than a monopulse SSR but exhibits much greater azimuthal error, especially when some of the replies are missing. Estimation techniques and their performance are discussed with special reference to SSR applications, and a novel estimator for conventional SSR is described. The proposed technique is a close approximation of the maximum-likelihood estimator (MLE), taking into account the receiver characteristics as well as the missed replies. Estimator performance obtained by analysis and computer simulation is compared with that of conventional estimators that are based on the leading and trailing edges of binary sequences and shows significantly improved accuracy     

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。     

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     

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     

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.     

Separation of SSR Signals by Array Processing in Multilateration Systems

Location and identification of cooperating aircraft in the airport area (and beyond) may be implemented by multilateration (MLAT) systems using the secondary surveillance radar (SSR) mode S signals. Most of these signals, spontaneously emitted from on-board mode S transponders at a fixed carrier frequency, arrive randomly at the receiving station, as well as many mode A/C replies from legacy transponders still in use. Several SSR signals are, then, overlapped in multiple aircraft situations. Therefore, the aim of this work is the separation of overlapped SSR signals, i.e., signals superimposed in time at receiving stations. We improve the MLAT receiving station by replacing the single antenna by an array of m elements and using array signal processing techniques. In the literature, several algorithms address the general source separation problem, but a very few of them are specifically designed for a mixture of overlapping SSR replies. Unfortunately, all of them have either some shortcomings, or an expensive computational cost, or no simple practical implementation. In this paper, we use the time sparsity property of the sources to propose more reliable, simpler, and more effective algorithms based on projection techniques to separate multiple SSR signals. Real recorded signals in a live environment are used to demonstrate the effectiveness of our method.     

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.     

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。     

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.     

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.<>     

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。     

Computation of aircraft geometric height under radar surveillance

A radar system for geometric height estimation of civil aircraft is described. The system consists of one standard or mode S secondary surveillance radar (SSR) and one omnidirectional antenna sited away from SSR under an airplane. The geometric height is derived by trilateration. Systematic errors are compensated for by deriving the profile of the effect on height measurements of the bias in range measurements. A curve-fitting technique is then used, which estimates both the geometric height and any non-zero systematic errors     

Track-to-track fusion with dissimilar sensors

An analysis is described of a kinematic state vector fusion algorithm when tracks are obtained from dissimilar sensors. For the sake of simplicity, it is assumed that two dissimilar sensors are equipped with nonidentical two-dimensional optimal linear Kalman filters. It is shown that the performance of such a track-to-track fusion algorithm can be improved if the cross-correlation matrix between candidate tracks is positive. This cross-correlation is introduced by noise associated with target maneuver that is common to the tracking filters in both sensors and is often neglected. An expression for the steady state cross-correlation matrix in closed form is derived and conditions for positivity of the cross-correlation matrix are obtained. The effect of positivity on performance of kinematic track-to-track fusion is also discussed     

Tracking Multiple Targets Simultaneously with a Phased Array Radar

A new technique is described by which radar tracks can be established and maintained in a dense multitarget environment. These targets may fly in formation, maneuver relative to each other, or be on crossing paths. They may fade and reappear, lose their resolution, or become resolved. If the formation members move apart, the formation track is split into separate tracks. Typical requirements for a formation tracking system are stated, followed by a discussion of the principles on which this design is based. The same logic applies both to single targets and to forma. tions. Finally, results from field tests are presented.     

地球资源技术卫星地面轨迹控制原理及调轨周期的选择

1.引言 在整个任务执行期间,要求资源卫星在一个复盖周期里的地面轨迹中心线与另一个复     

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.