基于SVR的机动目标跟踪

Random Target Tracking Based on SVR

本文研究了支持向量回归(SVR)在机动目标跟踪中的应用,并与传统回归方法最小二乘法(LS)进行了比较。实验结果表明,利用支持向量回归可以以很高的精度对机动目标进行跟踪,并且有着很强的适应能力,是一种有潜力的跟踪方法。

Tracking random targets with Support Vector Regression （SVR） is studied and compared with the Least Square （LS） estimate in this paper. Experiments show that SVR can track random targets with a high precision and a strong adaptation, and it is a potential tracking measure