To reduce the influence brought by bad data, a robust parametric harmonic analysis method is proposed, which is based on M-estimators and can be used to estimate unknown parameters of all harmonics and inter-harmonics in signals in an iterative way.

M-estimator based support vector machine and its application

After estimating the optimal control points using M-estimator, the roa.

Method for Global Motion Estimation Based on Robust M-estimator

Further more, an M-estimator for mesh filtering is presented.

Although M-estimation as the object function can be used to solve the problem,its corresponding influence function is determined by the absolute value of gross error and it is a key problem to choose initial parameters.

This method is based on M-estimation.

An Algorithm of Multi-Sensors Weighted Fusion Based on M-Estimate Applied in Single-Point Positioning;

Multi-Sensor Data Robust Weighted Fusion Algorithm Simulation Based on M-estimate;

M-estimate Based Kalman Filter with Immunity to Outliers;

For improving the accuracy, real-time property and reliability in GNSS real time single point navigation and positioning, three algorithms(Least squares estimation, M estimation and robust Kalman filter estimation) based on residual analysis for gross errors in real time observation were analyzed and compared.