超定测距定位方程参数估计的松弛重心迭代法

Relaxation barycentre iterative algorithm for solving parameter estimation of overdetermined distance locating equations

  • 摘要: 针对重心迭代法收敛速度缓慢的不足,基于残差最小步长准则,提出了一种松弛重心迭代法. 该方法依据残差最小性质,导出了松弛因子的确定公式,从而自适应调整迭代步长来提高重心迭代法的收敛效率. 松弛重心迭代法实质为最速下降法,具有迭代格式简单、无需矩阵求逆和计算海森矩阵的优点. 最后采用全球卫星导航系统(GNSS)定位数据和水下定位数据进行验证,结果表明松弛重心迭代法能够明显提高重心迭代法的收敛效率.

     

    Abstract: Based on the minimal residual criterion, a relaxtion method is proposed to improve the convergence efficiency of the barycentre method for solving the distance equations. The relaxation factor for adaptive selecting the iterative step of barycentre method is derived by the minimum residual criterion. The proposed method has the advantages of simple iterative format without the matrix inversion and to simplify the procedure without calculating the Hessian matrix. Finally, the novel method is performed to solve the data of GNSS and marine positioning examples to show its performance, and results show the numerical convergence experiments are performed to show the convergence efficiency improvment.

     

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