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An Angle-Parameterized Hierarchical-Splitting Gaussian Sum Based Tracking Method Using One-Dimensional Cosine Angle and Doppler Rate-of-Changing by a Single Satellite

机译:基于角度参数化的分层基于基于轨迹的跟踪方法,使用单颗卫星的一维余弦角和多普勒变率

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摘要

In order to achieve high precision tracking of a moving airborne emitter by a single satellite platform, a novel passive tracking method, combined one-dimensional cosine angle of arrival (CAOA) and Doppler rate-of-changing, is presented. To solve the high nonlinearity in the measurements, an efficient tracking algorithm called the angle-parameterized hierarchical-splitting Gaussian sum cubature Kalman filter (APHSGSCKF) is also proposed. The APHSGSCKF algorithm consists of multiple parallel CKFs. They are initialized by a proposed method called orthogonal cosine angle parameterized hypotheses (OCAPH), which divides the area target possible lying using a parameterized cosine angle. And the area is determined by a noised one-dimensional CAOA at the beginning of the measurement. In the splitting and merging conduct, to reduce the amount of computation while improving the accuracy, a new metrics of the degree of nonlinearity is introduced. The value range of it is segmented hierarchically, which determines how many filters should be split into. All the filter outputs are used to estimate the motion state. Simulation results show that the proposed algorithm can reach better performance compared with the general single CKF algorithm and the Gaussian sum cubature Kalman filter (GSCKF) initialized by the proposed OCAPH method.
机译:为了通过单卫星平台实现高精度跟踪移动空气发射器,提出了一种新型的被动跟踪方法,组合的一维余弦(CAOA)和多普勒率改变。为了解决测量中的高非线性,还提出了一种称为角度参数化分层分离高斯和Cubyature Kalman滤波器(APHSGSCKF)的有效跟踪算法。 APHSGSCKF算法由多个并行CKF组成。它们是通过称为正交余弦角参数化假设(OCAPH)的所提出的方法初始化的方法,其划分使用参数化余弦角的区域目标。并且该区域由测量开始时由发声一维CaOa确定。在分裂和合并的行为中,为了降低计算量的同时提高准确性,引入了非线性度的新度量。它的值范围是分层分割的,这决定了应该分割的过滤器。所有滤波器输出都用于估计运动状态。仿真结果表明,与普通的单一CKF​​算法和初始化的OCAPH方法初始化的Gause Sum Cubature Kalman滤波器(GSCKF)相比,该算法可以达到更好的性能。

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