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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2016 Vol.17 No.5 P.449-457
A novel approach of noise statistics estimate using H∞ filter in target tracking
Abstract: Noise statistics are essential for estimation performance. In practical situations, however, a priori information of noise statistics is often imperfect. Previous work on noise statistics identification in linear systems still requires initial prior knowledge of the noise. A novel approach is presented in this paper to solve this paradox. First, we apply the H∞ filter to obtain the system state estimates without the common assumptions about the noise in conventional adaptive filters. Then by applying state estimates obtained from the H∞ filter, better estimates of the noise mean and covariance can be achieved, which can improve the performance of estimation. The proposed approach makes the best use of the system knowledge without a priori information with modest computation cost, which makes it possible to be applied online. Finally, numerical examples are presented to show the efficiency of this approach.
Key words: Noise estimate, H∞ filter, Target tracking
创新点：假设噪声为高斯分布，但不需要噪声统计特征的先验知识；在算法设计中引入H∞滤波器，获得更准确的残差信息。
方法：假设噪声统计特征的先验知识未知，通过H∞滤波器获得系统状态估计；通过得到的系统状态估计值和量测值，可以得到残差样本序列；结合数理统计知识，通过得到的残差样本序列对过程噪声和量测噪声的均值、协方差进行估计。
结论：与基于卡尔曼滤波器的同一框架下得到的估计方法相比，本文中的算法可以得到更精确的估计结果（图2、4-6）。
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DOI:
10.1631/FITEE.1500262
CLC number:
TP274+.2
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On-line Access:
2016-05-04
Received:
2015-08-17
Revision Accepted:
2016-02-16
Crosschecked:
2016-04-11