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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:基于一维余弦角和多普勒变化率的单卫星角参数分层高斯和跟踪方法

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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:为了通过单个卫星平台对移动的机载发射器进行高精度跟踪,提出了一种新颖的被动跟踪方法,将一维余弦波到达角(CAOA)和多普勒变化率相结合。为了解决测量中的高非线性问题,还提出了一种有效的跟踪算法,该算法称为角度参数化的分层分裂高斯和温育卡尔曼滤波器(APHSGSCKF)。 APHSGSCKF算法由多个并行CKF组成。它们通过一种称为正交余弦角参数化假设(OCAPH)的拟议方法进行初始化,该方法使用参数化余弦角划分可能的区域目标。在测量开始时,该区域由一维噪声CAOA确定。在拆分和合并过程中,为了减少计算量,同时提高精度,引入了非线性度的新度量。它的值范围是按层次划分的,这决定了应将多少个过滤器拆分为多个。所有滤波器输出均用于估计运动状态。仿真结果表明,与普通的单CKF算法和由OCAPH方法初始化的高斯和库曼卡尔曼滤波器(GSCKF)相比,该算法具有更好的性能。

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