共查询到20条相似文献,搜索用时 31 毫秒
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Jointprobabillsticdataassociation(JPDA)isanalgorithmusedinsinglesensormultipletargettrackingsystems.Itemploysthenon-uniqueassignmentof"allneighbor"strategytoadaptforthedensemultitargettrackingenvironments[1].Becauseofitswideapplications,itisnecessarytoextendJPDAintosomemultiplesensortrackingsystems.Suchamultisensorsystem,forexample,canbeformedbycollocatingradarandinfraredsearchandtrack(IRST)whichcantakeadvantagesofboththesensorsbodatafusion.Undertheconditionofthesamesensors,acommonmeasure… 相似文献
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Covariance control for multisensor systems 总被引:5,自引:0,他引:5
As the profusion of different sensors improves the capabilities of tracking platforms, tracking objectives can move from simply trying to achieve the most with a limited sensor suite to developing the ability to achieve more specific tracking goals, such as reducing the uncertainty in a target estimate enough to accurately fire a weapon at a target or to ensure that a mobile robot does not collide with an obstacle. Multisensor manager systems that balance tracking performance with system resources have traditionally been ill-suited for achieving such specific control objectives. This work extends the methods developed in single-sensor management schemes to a multisensor application using an approach known as covariance control, which selects sensor combinations based on the difference between the desired covariance matrix and that of the predicted covariance of each target. 相似文献
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针对高杂波、电子干扰环境,在量测驱动的多目标滤波框架下提出了一种基于决策不确定性的传感器管理方法。首先,根据部分可观测马尔科夫决策过程的理论,给出了基于Rényi信息增量的传感器管理一般方法。其次,综合考虑决策过程的信息完整性、信息质量、信息的内涵等因素,在量测驱动的自适应滤波框架下,基于目标运动态势评估多目标决策不确定性水平,并选取最大决策不确定性目标。最后,以最大决策不确定性目标的信息增量最大化为准则进行传感器分配方案的求解。仿真实验表明所提方法能够有效抑制电子干扰、杂波对多目标跟踪及传感器分配的影响,与基于威胁的传感器管理方法相比,所提方法的平均最优子模式分配(OSPA)距离及平均计算时长均显著降低,且在高杂波、电子干扰情形下具有较高的可靠性。 相似文献
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Kirubarajan T. Wang H. Bar-Shalom Y. Pattipati K.R. 《IEEE transactions on aerospace and electronic systems》2001,37(2):386-400
We present the development of a multisensor fusion algorithm using multidimensional data association for multitarget tracking. The work is motivated by a large scale surveillance problem, where observations from multiple asynchronous sensors with time-varying sampling intervals (electronically scanned array (ESA) radars) are used for centralized fusion. The combination of multisensor fusion with multidimensional assignment is done so as to maximize the “time-depth” in addition to “sensor-width” for the number S of lists handled by the assignment algorithm. The standard procedure, which associates measurements from the most recently arrived S-1 frames to established tracks, can have, in the case of S sensors, a time-depth of zero. A new technique, which guarantees maximum effectiveness for an S-dimensional data association (S⩾3), i.e., maximum time-depth (S-1) for each sensor without sacrificing the fusion across sensors, is presented. Using a sliding window technique (of length S), the estimates are updated after each frame of measurements. The algorithm provides a systematic approach to automatic track formation, maintenance, and termination for multitarget tracking using multisensor fusion with multidimensional assignment for data association. Estimation results are presented for simulated data for a large scale air-to-ground target tracking problem 相似文献
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经典的集中式多传感器多目标跟踪算法通常计算量较大,经常难以满足系统的实时性要求,工程上实现起来比较困难,为进一步扩大集中式多传感器的应用范围,使其在对算法实时性要求较高、跟踪精度要求较小的实际场合中广泛应用。文章基于最近邻域思想,研究了并行处理结构的集中式多传感器最近邻域算法,并从算法跟踪精度、实时性、有效跟踪率3个方面对其与经典的顺序多传感器联合概率数据互联算法进行了仿真比较。经仿真验证,并行处理结构的集中式多传感器最近邻域算法实时性提高了60%以上,且在跟踪背景杂波适中的情况下能够有效跟踪目标。 相似文献
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在能量受限的分布式多传感器跟踪系统中,跟踪目标的同时,需要节省能量消耗,延长系统生存周期,本文依据一种传感器节点能量消耗模型,提出了一种以能量消耗和信息增量为效用的传感器管理算法。仿真结果表明该算法能提高跟踪精度,减少能量消耗,延长系统的使用时间。 相似文献
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A Self-organizing Bearings-only Target Tracking Algorithm in Wireless Sensor Network 总被引:1,自引:0,他引:1
In the bearings-only target tracking, wireless sensor network (WSN) collects observations of the target direction at various nodes and uses an adaptive filter to combine them for target tracking. An efficient network management is necessary to gain an optimal tradeoff between locating accuracy and energy consumption. This article proposes a self-organizing target tracking algorithm to select the most beneficial subset of nodes to track the target at every snapshot. Compared with traditional methods, this scheme avoids the need for keeping global position information of the network as in greedy selection. Each node judges its future usefulness depending on the knowledge of its own position and using simple mathematics computation. Simulations indicate that this scheme has locating accuracy comparable to the global greedy algorithm. Also, it has good robustness against node failure and autonomous adaptability to the change of the network scale. Furthermore, this algorithm consumes limited energy because only a portion of nodes partakes in the selection at every snapshot. 相似文献
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Multisensor tracking of a maneuvering target in clutter 总被引:1,自引:0,他引:1
An algorithm is presented for tracking a highly maneuvering target using two different sensors, a radar and an infrared sensor, assumed to operate in a cluttered environment. The nonparametric probabilist data association filter (PDAF) has been adapted for the multisensor (MS) case, yielding the MSPDAF. To accommodate the fact that the target can be highly maneuvering, the interacting multiple model (IMM) approach is used. The results of single-model-based filters and of the IMM/MSPDAF algorithm with two and three models are presented and compared. The IMM has been shown to be able to adapt itself to the type of motion exhibited by the target in the presence of heavy clutter. It yielded high accuracy in the absence of acceleration and kept the target in track during the high acceleration periods 相似文献
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基于混合滤波的无线传感器网络融合跟踪方法 总被引:1,自引:0,他引:1
针对无线传感器网络(WSN)中的多传感器融合目标跟踪,提出一种混合滤波算法,称为无迹混合集中式粒子滤波(UM CPF)。该算法使用了一个混合的粒子传播方案。在使用集中式粒子滤波(CPF)对WSN中的节点测量信息进行融合时,粒子滤波器中的一部分粒子使用从无迹变换(UT)获得的高斯分布作为建议分布进行粒子传播,而剩余的另一部分粒子则简单地使用状态转移先验分布进行粒子传播。WSN中的融合跟踪仿真结果表明,和纯粒子滤波算法CPF相比,在仿真速率相当的情况下,混合滤波算法明显提高了跟踪精度和稳定性。 相似文献
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雷达和红外成像双传感器信息融合目标识别研究 总被引:5,自引:0,他引:5
提出了一种利用目标的雷达和红外成像2种独立的传感器信息的互补性来构造特征向量的信息融合方法——联合向量空间法,并用对应的自适应信息融合系统进行目标识别。仿真证实比用单传感器的效果明显优越,从而说明了本文方法的有效性。 相似文献
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Rapid and reliable decisions about the onset and termination of maneuvers are critical for accurate tracking of maneuvering targets. Given the appropriate filter model, the use of multiple sensors of different capabilities and strengths can improve the quality and the reliability of the tracking system A multisensor tracking system where the usage of the image sensor is two fold is presented. First, if is used to perform maneuver detection using minimum computation and storage. Second, its bearing and elevation measurements are used along with 3-D radar observations to improve the tracking quality. The advantages of the proposed multisensor tracking system are discussed and demonstrated via simulations 相似文献
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针对传统火力分配模型容易造成资源浪费的问题,将火力单元以组为单位,以最大化杀伤概率为目标,构建一种具有多次拦截时机的动态火力分配模型;考虑到组内火力单元复合打击的情况,使用Kuhn-Munkres算法,优先将目标分配给复合打击效果大的目标;在此基础之上,设计了一种基于遗传算法(GA)的Anytime算法,引入了元级控制,提出一种任意时刻算法停机时刻的判定方法;仿真实验验证了模型优越性以及算法的合理性,对火力分配任意时刻算法使用元级控制可以有效提高解的效用。 相似文献
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空中目标传感器管理方法综述 总被引:2,自引:2,他引:0
为了避免对有限的多传感器资源的无序竞争和使用,多传感系统通常在一定约束条件下工作。传感器管理即是对传感器系统的自由度进行控制,以满足实际的约束条件并实现既定的任务目标,被大规模地应用于诸如区域目标监视、空中交通管制等各种军用与民用领域。首先,给出了传感器管理系统的概念定义与基本目标;然后,对过去及现在各种空中目标传感器管理方面的理论、方法以及应用进行了全面的综述与深入的分析,并对传感器管理领域现存的问题提出了解决思路和方法;最后,对该领域下一步的发展方向做出了展望。 相似文献
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IMM estimator with out-of-sequence measurements 总被引:3,自引:0,他引:3
In multisensor tracking systems that operate in a centralized information processing architecture, measurements from the same target obtained by different sensors can arrive at the processing center out of sequence. In order to avoid either a delay in the output or the need for reordering and reprocessing an entire sequence of measurements, such measurements have to be processed as out-of-sequence measurements (OOSMs). Recent work developed procedures for incorporating OOSMs into a Kalman filter (KF). Since the state of the art tracker for real (maneuvering) targets is the interacting multiple model (IMM) estimator, the algorithm for incorporating OOSMs into an IMM estimator is presented here. Both data association and estimation are considered. Simulation results are presented for two realistic problems using measurements from two airborne GMTI sensors. It is shown that the proposed algorithm for incorporating OOSMs into an IMM estimator yields practically the same performance as the reordering and in-sequence reprocessing of the measurements. Also, it is shown how the range rate from a GMTI sensor can be used as a linear velocity measurement in the tracking filter. 相似文献