一种鲁棒的矿井接近探测定位算法研究

Research on a robust positioning algorithm for mine proximity detection

针对现有矿井接近探测定位算法由于非视距等因素导致测距误差较大及复杂情况下测距方程组的解不收敛的问题,将高斯牛顿法、加权最小二乘法及Levenberg-Marquardt法相结合,提出了一种鲁棒的矿井接近探测定位算法,即加权LM法。该算法将测距误差信息通过增加权值的方法加入非线性迭代求解中,并在迭代过程加入阻尼系数,在保证迭代收敛速度的前提下大大提高了定位稳定性和鲁棒性。测试结果表明,加权LM法的定位效率和精度较高。

In view of problems of existing positioning algorithms for mine proximity detection that ranging error is large due to non-line-of-sight and other factors,and solution of ranging equation set does not converge under complex conditions,a robust positioning algorithm for mine proximity detection was proposed,namely weighted LM algorithm,which combines Gauss-Newton algorithm,weighted least square algorithm and Levenberg-Marquardt algorithm.The algorithm adds ranging error information to nonlinear iterative solution by adding weight,and adds damping coefficient in iterative process,which greatly improves positioning stability and robustness under precondition of ensuring convergence speed of iteration.Test results show that the weighted LM algorithm has high positioning efficiency and accuracy.