Generalized LMMSE Filtering with Out-of-Sequence Observations in Arbitrary Constant Delay

被引：0

作者：

Lei, Ming ^{[1
]}

Baehr, Christophe ^{[2
]}

Jing, Zhongliang ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Sch Aeronaut & Astronaut, Shanghai 200240, Peoples R China

[2] CNRS, Meteo France, Natl Meteorol Res Ctr, F-31057 Toulouse, France

来源：

CHINESE JOURNAL OF ELECTRONICS | 2019年 / 28卷 / 06期

基金：

中国国家自然科学基金;

关键词：

delays; filtering theory; least mean squares methods; mean square error methods; state estimation; target tracking; Out-of-sequence observations; arbitrary constant delay; sensor faults; Out-of-sequence measurement observations; Linear minimum; squared error filter; simultaneous treatment; correlated faults; arbitrary delay; linear-optimal manner; generalized LMMSE filtering; Out-of-sequence measurement (OOSM); Linear minimum mean squared error (LMMSE); Arbitrary time delay; Sensor faults; Fault-tolerant estimation; Multisensor fusion; ESTIMATOR; TRACKING; SYSTEMS; UPDATE;

D O I：

10.1049/cje.2019.08.005

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Focusing on the problem of state estimation in the presence of sensor faults and Out-of-sequence measurement (OOSM) observations synchronously, we derive a formulation of Linear minimum mean squared error (LMMSE) filter with the arbitrary time delay of OOSM, the generalization of the present work lies in simultaneous treatment of correlated faults together with OOSMs that arrive at an arbitrary delay in a linear-optimal manner. The approach is demonstrated in a numerical comparison.

引用

页码：1217 / 1226

页数：10

共 31 条

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