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Research on Distributed Multistatic Sonar Target Tracking Technique

机译:分布式多静学声纳目标跟踪技术研究

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Compared with monostatic sonar, multistatic sonar has a better tracking effect and a wider visible tracking range for underwater target tracking. The distributed fusion structure is widely used in multistatic sonar tracking systems because the cost is low, the calculation is simple and it is easy to achieve overall. In the distributed system, each sonar tracks the target and estimates the states independently. The tracking information is sent to the fusion center to complete the tasks of coordinate transformation, data calibration, track association and track fusion. In this paper, analysis and performance simulation of the theory in distributed multistatic sonar target track association and track fusion are given. The track processor is based on the PDAF and the Kalman filter. The track association uses two kinds of statistic association algorithm (sequential track method, and statistic double threshold association method). The track fusion is based on distributing the error covariance of the tracking system. In the track association phase, two association algorithms are discussed. One is a sequential track algorithm, which connects the history of the track with the present association state. The other is a statistic double threshold association algorithm. The first threshold of the sequential track algorithm is based on the theory of counter. The second threshold depends on the association quality and separation quality. The final determination of the statistic double threshold method on whether the tracks are from the same target and could be associated or not can be given after double threshold processing. The simulated performances of the algorithms are then discussed. In the track fusion phase, by distributing the error covariance of the system, the tracks which associated successfully are fused in the unified coordinate transformation to achieve better tracking accuracy, and the simulation analyses for bi-target algorithms in the multistatic system are given.
机译:与单体声卡相比,多晶座具有更好的跟踪效果和用于水下目标跟踪的更广泛的可见跟踪范围。分布式融合结构广泛用于多晶片声纳跟踪系统,因为成本低,计算简单,整体易于实现。在分布式系统中,每个Sonar跟踪目标并独立估计各州。跟踪信息被发送到融合中心,以完成坐标变换,数据校准,轨道关联和跟踪融合的任务。在本文中,给出了分布式多晶路馆目标轨道关联和轨道融合中的理论的分析和性能模拟。轨道处理器基于PDAF和卡尔曼滤波器。轨道关联使用两种统计关联算法(顺序轨道方法和统计双阈值关联方法)。轨道融合是基于分布跟踪系统的错误协方差。在轨道关联阶段,讨论了两个关联算法。一个是一个顺序轨道算法,它与当前关联状态连接轨道的历史。另一个是统计双阈值关联算法。顺序轨道算法的第一阈值基于计数器理论。第二个阈值取决于关联质量和分离质量。在双阈值处理之后,可以给出关于轨道是否来自同一目标的函数来自同一目标的统计双阈值方法的最终确定。然后讨论算法的模拟性能。在轨道融合阶段,通过将系统的误差协方差分配,在统一坐标变换中成功地融合的轨道以实现更好的跟踪精度,并且给出了多晶系统中的双目标算法的模拟分析。

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