Target Tracking for Mobile Sensor Networks Using Distributed Motion Planning and Distributed Filtering

Rigatos, Gerasimos

doi:10.5772/12925

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2017

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“…Measurement update. The global information state and matrix can be obtained as equations (18) and (19). Assuming that the true value of the state is written as x k , the state prediction error can be expressed by…”

Section: The Weights Functionmentioning

confidence: 99%

Robust high-degree cubature information filter and its application to trajectory estimation for ballistic missile

Wang

Qin

Cui

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part G:

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This paper presents a new recursive filter algorithm, the robust high-degree cubature information filter, which can provide reliable state estimation in the presence of non-Gaussian measurement noise. The novel algorithm is developed in the framework of the conventional information filter. The fifth-degree Cubature rule is utilized to improve the estimation accuracy and numerical stability during the time update, while the Huber technique is adopted in the measurements update stage. As the Huber technique is a combined minimum l 1 and l 2 norm estimation algorithm, the proposed algorithm could exhibit robustness to the non-Gaussian measurement noise, especially the glint noise. In addition, Monte Carlo simulation and the trajectory estimation for ballistic missile experiments demonstrate that the robust high-degree cubature information filter can provide improved state estimation performance over extended information filter and high-degree cubature information filter.

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Section: The Weights Functionmentioning

confidence: 99%