On Independent Axes Estimation for Extended Target Tracking

F. Govaers
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引用次数: 7

Abstract

The trend towards high resolution sensos in combination with a growing number of automotive applications where precise estimates of dense near-range objects are required, results in an enormous need for high performance algorithms for tracking extended targets. Conventionally, this is soved by an ellipse shape approximation of the object extent. In this paper a novel method to estimate the shape parameters of an ellipse using multiple measurements is proposed. By means of an Eigenvalue Decomposition of the measurement spread matrix, the half axis can be measured. A Gaussian model for the feature observations is derived. The performance and consistency is shown by means of Monte Carlo simulations in comparison to state-of-the-art methods in literature.
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扩展目标跟踪的独立轴估计
高分辨率传感器的趋势与越来越多需要精确估计密集近距离物体的汽车应用相结合,导致对高性能算法的巨大需求,用于跟踪扩展目标。通常,这是通过物体范围的椭圆形状近似来解决的。本文提出了一种利用多次测量来估计椭圆形状参数的新方法。通过测量扩展矩阵的特征值分解,可以测量半轴。导出了特征观测的高斯模型。通过蒙特卡罗模拟,并与文献中最先进的方法进行了比较,证明了该方法的性能和一致性。
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