TY - GEN
T1 - High precise attitude algorithm for SINS
AU - Li, Jie
AU - Liu, Jun
AU - Bo, Wang
PY - 2010
Y1 - 2010
N2 - Attitude matrix is the foundation of strapdown inertial navigation system (SINS). Equivalent rotation vector algorithm (ERVA) is now considered as the most effective method of computing the attitude matrix under the high-frequency dynamic environment. Most of the existing ERVA pay more attention to the method of optimizing the algorithm's coefficients, which are aimed at the variant sample number and update frequency. Under the condition of the given sample number and update frequency, in order to more adequately make use of the rate gyroscope's output information, and more precisely compute the attitude matrix, a novel ERVA is presented, its key thought is to improve the precision of ERV by adding its higher order cross coupling items about the different angle increment during the period of the attitude update into the ERV update equation. Taking two-sample ERVA as the example, the derivation of the novel ERV update equation is given in detail, Simulation results of the novel ERVA demonstrates its validity of improving the ERV precision under the condition of the given sample number and update frequency.
AB - Attitude matrix is the foundation of strapdown inertial navigation system (SINS). Equivalent rotation vector algorithm (ERVA) is now considered as the most effective method of computing the attitude matrix under the high-frequency dynamic environment. Most of the existing ERVA pay more attention to the method of optimizing the algorithm's coefficients, which are aimed at the variant sample number and update frequency. Under the condition of the given sample number and update frequency, in order to more adequately make use of the rate gyroscope's output information, and more precisely compute the attitude matrix, a novel ERVA is presented, its key thought is to improve the precision of ERV by adding its higher order cross coupling items about the different angle increment during the period of the attitude update into the ERV update equation. Taking two-sample ERVA as the example, the derivation of the novel ERV update equation is given in detail, Simulation results of the novel ERVA demonstrates its validity of improving the ERV precision under the condition of the given sample number and update frequency.
KW - Algorithm
KW - Attitude
KW - High precision
UR - http://www.scopus.com/inward/record.url?scp=78650482011&partnerID=8YFLogxK
U2 - 10.1109/PCSPA.2010.159
DO - 10.1109/PCSPA.2010.159
M3 - Conference contribution
AN - SCOPUS:78650482011
SN - 9780769541808
T3 - Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
SP - 636
EP - 639
BT - Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
T2 - 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Y2 - 17 September 2010 through 19 September 2010
ER -