A Method for Maritime Target Tracking Based on Kernelized Spectral Filter

Lu Bai, Yulong Qiao
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Abstract

Maritime target tracking can be applied in the fields of intelligent marine transportation and resource protection. The spectral filter tracking method focuses on the adaptability of the local appearance changes of targets, with the graph representation. Considering the complexity and diversity of the marine environment, we propose a maritime target tracking algorithm based on kernelized spectral filter. The spectral filtering is modeled as a tracking framework based on kernel regression. According to graph signal processing and spectral graph theory, based on the description of kernel regression on graph signals, we deduce and discuss the construction of the filter, the calculation of kernel matrix, the solution of kernel regression model, and the prediction of tracking position. With the help of a nonlinear model, it can effectively improve the precision under complex tracking conditions. The experimental results on the benchmark dataset verify the effectiveness of the proposed method, especially when the target tracking is affected by waves or wakes.
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一种基于核谱滤波的海上目标跟踪方法
海上目标跟踪可以应用于海上智能运输和资源保护等领域。光谱滤波跟踪方法注重对目标局部外观变化的适应性,采用图表示。考虑到海洋环境的复杂性和多样性,提出了一种基于核谱滤波的海洋目标跟踪算法。将谱滤波建模为基于核回归的跟踪框架。根据图信号处理和谱图理论,在描述图信号核回归的基础上,推导并讨论了滤波器的构造、核矩阵的计算、核回归模型的求解以及跟踪位置的预测。借助非线性模型,可以有效地提高复杂跟踪条件下的跟踪精度。在基准数据集上的实验结果验证了该方法的有效性,特别是当目标跟踪受到波浪或尾迹影响时。
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