超分辨率Root-Min-Norm井下定位算法

Super-Resolution Root-Min-Norm Miner Location Algorithm

对不能处理相关信号的求根最小范数（Root—Min—Norm）算法进行了修正，对信号估计协方差运用了前后向平滑处理，在小样本条件下提高了相关矩阵和TDE（Time Delay Estimation）估计精度。将该超分辨率算法应用到井下定位算法当中，通过仿真实验得到的统计结果表明超分辨率Root—Min—Norm算法是一种高分辨率、高精度、高稳定性的算法，具有很大的实际推广价值。

Root-Min-Norm algorithm is modified which hardly processes correlated signals estimated covariance signal is smoothed forwards and backwards and in a small the accuracy of the estimates the correlation matrix and TDE （Time Delay Estimation） is improved under a conditions of small sample. Root-Min-Norm algorithm was proposed for the correlated signals. The super-resolution algorithm is applied in miner location. The statistics demonstrates that the super- resolution Root-Min-Norm algorithm is an algorithm with high resolution, accuracy and stability which owns great values in the actual applications.