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Ground target tracking with variable structure IMM estimator

机译:具有可变结构IMM估计器的地面目标跟踪

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In this paper we present the design of a Variable Structure Interacting Multiple Model (VS-IMM) estimator for tracking groups of ground targets on constrained paths using Moving Target Indicator (MTI) reports obtained from an airborne sensor. The targets are moving along a highway, with varying obscuration due to changing terrain conditions. In addition, the roads can branch, merge or cross-the scenario represents target convoys along a realistic road network with junctions, changing terrains, etc. Some of the targets may also move in an open field. This constrained motion estimation problem is handled using an IMM estimator with varying mode sets depending on the topography, The number of models in the IMM estimator, their types and their parameters are modified adaptively, in real-time, based on the estimated position of the target and the corresponding road/visibility conditions. This topography-based variable structure mechanism eliminates the need for carrying all the possible models throughout the entire tracking period as in the standard IMM estimator, significantly improving performance and reducing computational load. Data association is handled using an assignment algorithm. The estimator is designed to handle a very large number of ground targets simultaneously. A simulated scenario consisting of over one hundred targets is used to illustrate the selection of design parameters and the operation of the tracker. Performance measures are presented to contrast the benefits of the VS-IMM estimator over the Kalman filter and the standard IMM estimator, The VS-IMM estimator is then combined with multidimensional assignment to gain "time-depth." The additional benefit of using higher dimensional assignment algorithms for data association is also evaluated.
机译:在本文中,我们介绍了一种可变结构相互作用多模型(VS-IMM)估计器的设计,该估计器使用从机载传感器获得的移动目标指示器(MTI)报告来跟踪约束路径上的地面目标组。这些目标沿着高速公路行驶,由于地形条件的变化,遮盖力也有所不同。此外,道路可以分支,合并或交叉,这种情况表示目标车队沿着具有交叉路口,不断变化的地形等的现实道路网络行驶。某些目标也可能在空旷的地方移动。使用具有取决于地形的变化模式集的IMM估计器来处理此受限运动估计问题。IMM估计器中模型的数量,模型的类型和参数会根据模型的估计位置实时进行自适应修改。目标以及相应的道路/可见性条件。这种基于地形的可变结构机制消除了像标准IMM估计器一样在整个跟踪周期内携带所有可能模型的需求,从而显着提高了性能并减少了计算负荷。使用分配算法处理数据关联。估算器旨在同时处理大量地面目标。由一百多个目标组成的模拟场景用于说明设计参数的选择和跟踪器的操作。提出了性能指标,以对比VS-IMM估计器优于卡尔曼滤波器和标准IMM估计器的好处。然后,将VS-IMM估计器与多维分配结合起来以获取“时间深度”。还评估了使用更高维度的分配算法进行数据关联的其他好处。

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