For the navigation algorithm of the strapdown inertial navigation system, by comparing to the equations of the dual quaternion and quaternion, the superiority of the attitude algorithm based on dual quaternion over th...For the navigation algorithm of the strapdown inertial navigation system, by comparing to the equations of the dual quaternion and quaternion, the superiority of the attitude algorithm based on dual quaternion over the ones based on rotation vector in accuracy is analyzed in the case of the rotation of navigation frame. By comparing the update algorithm of the gravitational velocity in dual quaternion solution with the compensation algorithm of the harmful acceleration in traditional velocity solution, the accuracy advantage of the gravitational velocity based on dual quaternion is addressed. In view of the idea of the attitude and velocity algorithm based on dual quaternion, an improved navigation algorithm is proposed, which is as much as the rotation vector algorithm in computational complexity. According to this method, the attitude quaternion does not require compensating as the navigation frame rotates. In order to verify the correctness of the theoretical analysis, simulations are carried out utilizing the software, and the simulation results show that the accuracy of the improved algorithm is approximately equal to the dual quaternion algorithm.展开更多
Traditional coning algorithms are based on the first-order coning correction reference model.Usually they reduce the algorithm error of coning axis(z)by increasing the sample numbers in one iteration interval.But the ...Traditional coning algorithms are based on the first-order coning correction reference model.Usually they reduce the algorithm error of coning axis(z)by increasing the sample numbers in one iteration interval.But the increase of sample numbers requires the faster output rates of sensors.Therefore,the algorithms are often limited in practical use.Moreover,the noncommutivity error of rotation usually exists on all three axes and the increase of sample numbers has little positive effect on reducing the algorithm errors of orthogonal axes(x,y).Considering the errors of orthogonal axes cannot be neglected in the high-precision applications,a coning algorithm with an additional second-order coning correction term is developed to further improve the performance of coning algorithm.Compared with the traditional algorithms,the new second-order coning algorithm can effectively reduce the algorithm error without increasing the sample numbers.Theoretical analyses validate that in a coning environment with low frequency,the new algorithm has the better performance than the traditional time-series and frequency-series coning algorithms,while in a maneuver environment the new algorithm has the same order accuracy as the traditional time-series and frequency-series algorithms.Finally,the practical feasibility of the new coning algorithm is demonstrated by digital simulations and practical turntable tests.展开更多
An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVD...An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVDR）, the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.展开更多
基金supported by the National Natural Science Foundation of China (No. 61174126)
文摘For the navigation algorithm of the strapdown inertial navigation system, by comparing to the equations of the dual quaternion and quaternion, the superiority of the attitude algorithm based on dual quaternion over the ones based on rotation vector in accuracy is analyzed in the case of the rotation of navigation frame. By comparing the update algorithm of the gravitational velocity in dual quaternion solution with the compensation algorithm of the harmful acceleration in traditional velocity solution, the accuracy advantage of the gravitational velocity based on dual quaternion is addressed. In view of the idea of the attitude and velocity algorithm based on dual quaternion, an improved navigation algorithm is proposed, which is as much as the rotation vector algorithm in computational complexity. According to this method, the attitude quaternion does not require compensating as the navigation frame rotates. In order to verify the correctness of the theoretical analysis, simulations are carried out utilizing the software, and the simulation results show that the accuracy of the improved algorithm is approximately equal to the dual quaternion algorithm.
基金Supported by the National Natural Science Foundation of China(61104188,91016019)the National Basic Research Program of China(2009CB724002)the Research Funding of Nanjing University of Aeronautics and Astronautics(NS2010084,NP2011049)
文摘Traditional coning algorithms are based on the first-order coning correction reference model.Usually they reduce the algorithm error of coning axis(z)by increasing the sample numbers in one iteration interval.But the increase of sample numbers requires the faster output rates of sensors.Therefore,the algorithms are often limited in practical use.Moreover,the noncommutivity error of rotation usually exists on all three axes and the increase of sample numbers has little positive effect on reducing the algorithm errors of orthogonal axes(x,y).Considering the errors of orthogonal axes cannot be neglected in the high-precision applications,a coning algorithm with an additional second-order coning correction term is developed to further improve the performance of coning algorithm.Compared with the traditional algorithms,the new second-order coning algorithm can effectively reduce the algorithm error without increasing the sample numbers.Theoretical analyses validate that in a coning environment with low frequency,the new algorithm has the better performance than the traditional time-series and frequency-series coning algorithms,while in a maneuver environment the new algorithm has the same order accuracy as the traditional time-series and frequency-series algorithms.Finally,the practical feasibility of the new coning algorithm is demonstrated by digital simulations and practical turntable tests.
基金supported by the National Science&Technology Pillar Program(2013BAF07B03)Zhejiang Provincial Natural Science Foundation of China(LY13F010009)
文摘An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVDR）, the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.
