A New Second-order Strapdown Attitude Algorithm

Typically coning motion has been used as a standard input to assess the performance of the strapdown attitude algorithms. Traditional coning algorithms are based on the Bortz’s first-order rotation vector equation. The algorithm error is composed of two parts: drift error and approximation error. For the three (or more)-sample coning algorithms, calculation indicates that approximation error is far larger than drift error for the most general case, which means the approximation error should be reduced firstly. The existing coning algorithms generally increase the sample numbers to reduce drift error, but the increment of the sample numbers has little positive effect on reducing approximation error. To improve the algorithm performance, a new coning algorithm with an additional second-order coning correction term has been developed, which can effectively reduce the approximation error without increasing sample numbers. Simulations and practical tests demonstrate that the new algorithm is superior to the traditional coning algorithms for the general case. Although the new algorithm has increased a little computational load, practical test results validate that with the rapid development of the computer speed, the new second-order strapdown attitude algorithm still satisfies the real-time requirement.