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A Three-Dimensional Hough Transform-Based Track-Before-Detect Technique for Detecting Extended Targets in Strong Clutter Backgrounds

机译：一种基于三维霍夫变换的轨迹检测技术，用于检测强杂波背景中的扩展目标

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摘要

Hough Transform (HT), which has a low sensitivity to local faults and good ability in suppressing noise and clutters, usually applies to trajectory detection in a cluttered environment. This paper describes its application for detecting the trajectories of extended targets in three-dimensional measurements, i.e., a two-dimensional positional information and its measuring time. For taking the full merits of a multi-scan, the measuring time is regarded as a variable for the time axis. This correspondence extends the HT to 3-dimensional data. Meanwhile, a three-dimensional accumulator matrix is built for the purpose of voting. The voting process is done in an iterative way by selecting the 3D-line with the most votes and removing the corresponding measurements in each step. The three dimensional Hough Transform-based extended target track-before-detect technique (3DHT-ET-TBD), proposed here, is suitable to track the extended target and non-extended target simultaneously and few false alarm trajectories arise. Both the real data and simulated data are exploited to evaluate its performance. Compared with the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter based methods and a 4DHT-TBD algorithm, the 3DHT-ET-TBD is a more promising approach for multi-extended target tracking problems due to its high efficiency and low computation, especially in situations where the noise and false alarms are considerably high but few measurements are generated by the extended targets.
机译：Hough变换（HT）对局部故障和抑制噪声和折叠的良好能力具有低灵敏度，通常适用于杂乱环境中的轨迹检测。本文介绍了一种检测三维测量中扩展目标的轨迹的应用，即二维位置信息及其测量时间。对于采用多扫描的完整优点，测量时间被视为时间轴的变量。该对应关系将HT扩展到三维数据。同时，为投票的目的建立了三维蓄能器矩阵。通过选择具有最大投票的3D线并在每个步骤中删除相应的测量来以迭代方式完成投票过程。这里提出的三维霍夫基于延伸的扩展目标轨道预测技术（3Dht-et-TBD）适用于追踪扩展目标和非扩展目标，并且出现了很少的误报轨迹。可以利用真实数据和模拟数据来评估其性能。与高斯混合概率假设密度（GM-PHD）滤波器的方法和4Dht-TBD算法相比，3Dht-et-TBD是一种由于其高效率和低计算而具有多扩展目标跟踪问题的更有前途的方法，特别是在噪声和误报的情况下，扩展目标产生很少但是测量很少的情况。

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