This paper explores the application of centralised and distributed gaussianprocess algorithms to real-time target tracking and compares their performance. By embedding the algorithms into the Stone Soup, the focus is...
详细信息
ISBN:
(纸本)9798350371420;9781737749769
This paper explores the application of centralised and distributed gaussianprocess algorithms to real-time target tracking and compares their performance. By embedding the algorithms into the Stone Soup, the focus is on the innovative implementation of gaussianprocessmethods with learning hyperparameters and implementation with a factorised variance of the gaussian kernel. The performance of the methods with different kernels was evaluated, not only with the gaussian kernel. Extensive experiments with various kernel configurations demonstrate their importance in enhancing prediction accuracy and efficiency, especially in real-time tracking. The case studies with manoeuvring targets show significant advancements in tracking capabilities, particularly in wireless sensor networks, using optimised gaussianprocessmethods. This work advances Stone Soup's capabilities and lays the groundwork for future investigations into adaptive gaussianprocess applications in tracking and sensor data analysis.
暂无评论