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首页> 外文期刊>Radar, Sonar & Navigation, IET >Debiased converted position and Doppler measurement tracking with array radar measurements in direction cosine coordinates
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Debiased converted position and Doppler measurement tracking with array radar measurements in direction cosine coordinates

机译:在方向余弦坐标中使用阵列雷达测量值对偏移的转换位置和多普勒测量值进行跟踪

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摘要

With the advantage that antenna pattern and scanning features can be described conveniently in phased array radar, direction cosine coordinates (COS) is widely used. Unfortunately, measurements reported in the COS are non-linear relative to the target states described in the Cartesian coordinates. In addition, it has been proved by the theory and practice that the tracker can perform better by making full use of the Doppler measurement. This study mainly focuses on dealing with the position and Doppler measurement in the COS. Firstly, a pseudo measurement constructed by the product of range measurement and Doppler measurement is utilized to reduce the high non-linearity between the target state and the Doppler measurement. Then, via taking the fourth-order terms of a Taylor series expansion, the consistent estimation of converted measurements errors is obtained based on current measurements. Finally, in order to process the converted position measurements and pseudo measurement sequentially, Cholesky decomposition is exploited to decorrelate the converted position and pseudo measurement errors. Simulation results illustrate that the filter presents a higher estimation accuracy of target states, whether the target is moving or static. Furthermore, compared with unscented Kalman filter, the calculation load of the proposed filter is reduced significantly.
机译:由于可以在相控阵雷达中方便地描述天线方向图和扫描特征,因此广泛使用了方向余弦坐标(COS)。不幸的是,在COS中报告的测量值相对于笛卡尔坐标中描述的目标状态是非线性的。另外,通过理论和实践证明,通过充分利用多普勒测量技术,跟踪器可以实现更好的性能。本研究主要针对COS中的位置和多普勒测量,首先,利用距离测量和多普勒测量的乘积构造的伪测量来减少目标状态和多普勒测量之间的高度非线性。然后,通过采用泰勒级数展开式的四阶项,可以基于当前测量值获得转换后的测量误差的一致估计。最后,为了顺序处理转换后的位置测量值和伪测量值,利用Cholesky分解对转换后的位置误差和伪测量值误差进行解相关。仿真结果表明,无论目标是运动的还是静止的,该滤波器都具有较高的目标状态估计精度。此外,与无味卡尔曼滤波器相比,该滤波器的计算量大大降低。

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