An approach to identify multiple outliers based on sequential likelihood ratio tests

One of the main challenges in the quality control of geodetic measurements is the reliable identification of multiple outliers. Within this context, the goal of this paper is to present a procedure designated here as Sequential Likelihood Ratio Tests for Multiple Outliers (SLRTMO). To verify its performance, a levelling network was simulated involving one, two and three (simultaneous) outliers. Also a GNSS network involving one and two (simultaneous) outliers was analysed. Results showed that SLRTMO is efficient for single and multiple outliers, simulated with magnitude greater than five standard deviations, with a mean success rate of 79.6% for these cases. Furthermore, the maximum number of outliers to be tested has to be defined according to the redundancy of the network so as to ensure the performance of SLRTMO.