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Multi-mode Composite Track Estimation Method Based on Distributed Measurement Fusion

机译:基于分布式测量融合的多模复合轨道估计方法

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In the multi-mode track fusion algorithm, the commonly used method based on state fusion is relatively small in calculation, but it is not the optimal estimation. The centralized filter fusion method based on measurement is the optimal, but the measurement equation has high dimension, and the calculation is large. In this paper, the extended measurement method is used to unify the dimensionality of distributed measurement data, and a distributed measurement fusion algorithm adapted to track estimation is designed, which can effectively reduce the computation cost, improve the reliability and fault-tolerant ability, and achieve the optimal estimation of state data. The simulation results of active and passive radar composite guidance show that the algorithm is simple in calculation and fast in convergence, and can guarantee the high precision optimal estimation of target trajectory.
机译:在多模轨道融合算法中,基于状态融合的常用方法在计算中相对较小,但它不是最佳估计。 基于测量的集中滤波器融合方法是最佳的,但测量方程具有高尺寸,并且计算大。 在本文中,扩展测量方法统一统一分布式测量数据的维度,并且设计了一种适用于跟踪估计的分布式测量融合算法,可以有效地降低计算成本,提高可靠性和容错能力,以及提高可靠性和容错能力,以及 实现状态数据的最佳估计。 主动和无源雷达综合指导的仿真结果表明,算法在收敛时简单,快速,可以保证目标轨迹的高精度最佳估计。

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