存在传感器偏差和小目标时轨迹到真值分配的PDA技术

Yan Wang, W. Blair, T. Ogle, P. Miceli
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引用次数: 1

摘要

在利用逼真的计算机模拟或真实传感器数据对多目标跟踪算法进行性能评估时,良好的轨迹到真值分配(TTA)是任何有意义的评估的关键组成部分。在真值数据中存在传感器可能无法观察到的小物体的运动学数据,这对TTA提出了严峻的挑战。由于传感器偏差的存在,分配过程进一步复杂化。本文考虑了小目标和传感器偏差存在下的TTA问题。当目标密度很高,而一些对象很小时,正确地将轨迹分配给真值对象是具有挑战性的,并且随着传感器偏差的增加,如果没有缓解,正确地将轨迹分配给真值对象的问题是不可能的。真实目标间航迹的高假切换率极大地阻碍了目标跟踪系统的性能评估。在本文中,通过将跟踪概率添加到TTA的概率数据关联(PDA)技术中来解决这些挑战。给出了实现PDA技术的计算算法以及仿真结果,验证了PDA方法在准确估计传感器偏差、减少TTA中人为轨迹切换和模糊度方面的有效性。
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PDA Technique for Track-to-Truth Assignment in the Presence of Sensor Biases and Small Objects
When conducting performance assessment of multi-target tracking algorithms with a realistic computer simulation or real-world sensor data, good track-to-truth assignment (TTA) is a critical component of any meaningful assessment. The presence of kinematic data for small objects that may not be observed by the sensor in the truth data poses serious challenges to the TTA. The assignment process is further complicated by the presence of sensor biases. In this paper, TTA in the presence of small objects and sensor biases is considered. When the target density is high and some objects are small, correctly assigning tracks to truth objects is challenging, and with the addition of sensor biases, the problem of correctly assigning tracks to truth objects is impossible without mitigation. The high rate of false switches of tracks between true objects greatly hinders the performance assessment of the target tracking system. In this paper, these challenges are addressed by adding probability of tracking to a probabilistic data association (PDA) technique for TTA. The computational algorithms for the implementation of the PDA technique are presented along with simulation results that confirm the effectiveness of the PDA approach in accurately estimating the sensor biases, and reducing the artificial track switches and ambiguity in the TTA.
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