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。
Tracking random targets with Support Vector Regression (SVR) is studied and compared with the Least Square (LS) estimate in this paper.
为了提高在杂波环境下跟踪强机动目标的精度，提出了一种新的基于期望极大化(EM)算法的机动目标状态估计方法。
To improve the accuracy of tracking the complex maneuver target in cluttered environment, a new state estimation algorithm based on the expectation maximization (EM) algorithm is presented.
从仿真结果可以看出，在杂波环境下用IMM-PDAF进行机动目标跟踪，TS-MPWG跟踪门优于其它方法。
The simulation results suggest that: tracking maneuvering targets in cluttered environment with IMM-PDAF, gating via TS-MPWG is preferable to other methods.
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