Tracking an accelerated target with a nonlinear constant heading model

Rong Yang, G. Ng, B. Ng
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Abstract

This paper proposes a nonlinear model to track a maneuvering target in acceleration motion. The acceleration motion is traditionally modeled as a linear function with the state which consists of target position, speed and acceleration in the x, y and possibly z coordinates. The state elements in different coordinate are assumed uncoupled. However, This assumption is not generally true, as the state elements in different coordinates are correlated by the common target heading. Thus, a nonlinear constant heading model is suggested in this paper. To implement this nonlinear model, a two-stage least squares method is developed for track initiation, and an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) are proposed to estimate the state in track maintenance. Performance of the nonlinear model is demonstrated through simulation data, and results show that the proposed nonlinear model outperforms the traditional linear model.
用非线性恒航向模型跟踪加速目标
提出了一种用于机动目标加速度跟踪的非线性模型。加速度运动传统上被建模为一个线性函数,其状态由目标位置、速度和加速度在x、y和z坐标系中组成。假定不同坐标下的状态元素是不耦合的。然而,这种假设并不普遍成立,因为不同坐标下的状态元素是通过共同的目标航向相关联的。因此,本文提出了一种非线性恒航向模型。为了实现这一非线性模型,提出了一种两阶段最小二乘法进行轨道初始化,并提出了扩展卡尔曼滤波(EKF)和无气味卡尔曼滤波(UKF)来估计轨道维护中的状态。通过仿真数据验证了非线性模型的性能,结果表明所提出的非线性模型优于传统的线性模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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