Adaptive Extended Kalman Filter Based on Genetic Algorithm for Tightly- coupled Integrated Inertial and GPS Navigation

被引：3

作者：

Han Lu ^{[1
]}

Jing Zhan-rong ^{[1
]}

Wei Ming-ming ^{[2
]}

Zhang Li-xin ^{[2
]}

机构：

[1] Northwestern Polytech Univ, Coll Elect & Informat, Xian 710072, Peoples R China

[2] Xian Technol Univ, Coll Mech & Elect, Xian, Peoples R China

来源：

ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL I, PROCEEDINGS | 2009年

关键词：

adaptive; extended kalman filter; pseudorange; pseudorange rate; genetic algorithm;

D O I：

10.1109/ICICTA.2009.132

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An adaptive Extended Kalman Filter is derived for integrating inertial measurements from gyros, accelerometers with GPS pseudorange and pseudorange rate measurements. The adaptive filter uses an estimator based on state residual to provide a positive definite estimate of the process noise covariance matrix. The Genetic Algorithm is utilized to optimally determine the estimator's parameter which is a slide window size. The filter formulation is based on standard inertial navigation equations. Simulation results are shown to compare the performance of nonadaptive and adaptive Extended Kalman Filter.

引用

页码：520 / 524

页数：5

共 11 条

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