通过多帧轨迹补全提升地球同步轨道目标检测精度
Space Object Detection using Multi-frame Temporal Trajectory Completion Method
- 用小波变换增强单帧信号，抑制背景噪声
- 基于匈牙利算法实现跨帧匹配，提升轨迹完整性
- 多阶段后处理有效减少漏检和误检，适合航天监测场景
地球同步轨道（GEO）空间物体在光学成像中因信号微弱、星场复杂及环境干扰面临严峻检测挑战。本文通过小波变换增强GEO目标的高频特征，同时抑制单帧背景噪声。在此基础上，提出一种基于匈牙利算法的多帧时序轨迹补全方法，实现全局最优跨帧匹配。后处理流程包括时序匹配与插值补全、基于时序一致性的噪声过滤以及渐进式轨迹优化，有效缓解漏检与误检问题。在公开数据集SpotGEO上的实验表明，该方法取得90.14%的F₁分数，验证了其有效性。
原文摘要 · Abstract (English)
Space objects in Geostationary Earth Orbit (GEO) present significant detection challenges in optical imaging due to weak signals, complex stellar backgrounds, and environmental interference. In this paper, we enhance high-frequency features of GEO targets while suppressing background noise at the single-frame level through wavelet transform. Building on this, we propose a multi-frame temporal trajectory completion scheme centered on the Hungarian algorithm for globally optimal cross-frame matching. To effectively mitigate missing and false detections, a series of key steps including temporal matching and interpolation completion, temporal-consistency-based noise filtering, and progressive trajectory refinement are designed in the post-processing pipeline. Experimental results on the public SpotGEO dataset demonstrate the effectiveness of the proposed method, achieving an F_1 score of 90.14%.
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