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吴仁彪

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期刊论文

Probability hypothesis density filter for radar systematic error estimation aided by ADS-B

吴仁彪Tao Zhang Renbiao Wu Ran Lai Zhe Zhang

Signal Processing, Vol.120, 2016, pp.280-287.,-0001,():

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摘要/描述

This paper provides a solution for systematic bias estimation of radar without priori information of data association based on the probability hypothesis density (PHD) filter aided by automatic dependent surveillance broadcasting (ADS-B). Novel dynamics model and measurement model of systematic bias are developed by using ADS-B surveillance data as the high-accuracy reference source. The Gaussian mixture probability hypothesis density (GM-PHD) filter is applied for recursive estimation of systematic bias by introducing the novel dynamics model and measurement model of systematic bias into the filter. Numerical results are provided to verify the effectiveness and improved performance of the proposed method for systematic bias estimation.

【免责声明】以下全部内容由[吴仁彪]上传于[2017年02月10日 09时33分00秒],版权归原创者所有。本文仅代表作者本人观点,与本网站无关。本网站对文中陈述、观点判断保持中立,不对所包含内容的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考,并请自行承担全部责任。

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