提出新评估指标Star-ID，精准衡量轨迹的时空一致性。
From Target Tracking to Targeting Track -- Part I: A Metric for Spatio-Temporal Trajectory Evaluation
- 用曲线函数建模目标轨迹，支持任意时刻状态推断。
- 通过时空对齐区分时间匹配与错位段，量化误报、漏检和定位误差。
- 适用于单目标或多目标跟踪评估，理论与数值验证有效。
在目标跟踪领域，性能评估对跟踪器的设计、比较与分析至关重要。传统轨迹由测量时间序列中跟踪器输出的点估计构成，而本系列研究（包括本文）所追求的轨迹为时间的函数（FoT），能完整描述目标随时间的运动信息，并可推断任意时刻的状态，而不仅限于测量时刻。然而，目前尚无可用于比较和评估轨迹FoT的度量方法。为此，本文提出一种名为时空对齐轨迹积分距离（Star-ID）的新度量。Star-ID在时空域中关联并对齐估计轨迹与真实轨迹，区分时间对齐与未对齐段，在计算空间偏差时涵盖误报、漏检和定位误差。通过理论分析与单目标/多目标的数值示例，验证了该度量及其时间平均版本的有效性。
原文摘要 · Abstract (English)
In the realm of target tracking, performance evaluation plays a pivotal role in the design, comparison, and analytics of trackers. Compared with the traditional trajectory composed of a set of point-estimates obtained by a tracker in the measurement time-series, the trajectory that our series of studies including this paper pursued is given by a curve function of time (FoT). The trajectory FoT provides complete information of the movement of the target over time and can be used to infer the state corresponding to arbitrary time, not only at the measurement time. However, there are no metrics available for comparing and evaluating the trajectory FoT. To address this lacuna, we propose a metric denominated as the spatiotemporal-aligned trajectory integral distance (Star-ID). The StarID associates and aligns the estimated and actual trajectories in the spatio-temporal domain and distinguishes between the time-aligned and unaligned segments in calculating the spatial divergence including false alarm, miss-detection and localization errors. The effectiveness of the proposed distance metric and the time-averaged version is validated through theoretical analysis and numerical examples of a single target or multiple targets.
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