Integer ambiguity estimation and validation are crucial steps when solving the carrierphase based GNSS model. For the validation, different ambiguity acceptance tests have been proposed. For those tests often fixed critical values are used, with the important disadvantage that the performance of the tests varies a lot depending on measurement set-up and circumstances. Therefore it is better to use model-driven critical values such that it is guaranteed that the failure rate will not exceed a user-defined threshold. This contribution will study the model-dependency of the critical values for two well known acceptance tests, the ratio test and difference test, and then specifically for a given application. This means that mainly the satellite-receiver geometry and number of epochs will be variable. It will be shown that critical values do exhibit a strong dependence on these factors, and it will not be possible to simply use a fixed (i.e., constant) application-driven critical value.

This paper explores the use of pantograph-catenary contact force (PCCF) for monitoring of the current collection quality and detection of anomalies in the interaction between pantograph and catenary. The concept of catenary structure wavelength (CSW) is proposed as the dominant component of PCCF. It describes the signal components caused by the cyclical catenary structure in span and inter-dropper distance. To obtain the CSWs and non-CSW residual of PCCF, an automatic extraction approach based on the ensemble empirical mode decomposition (EEMD) is proposed. In the approach, the instantaneous frequency of each intrinsic mode function generated by EEMD is employed for the extraction of CSWs. Some selected trials on the PCCF data from simulation and measurement are performed and indicate that the extraction approach is adaptive to the PCCF under various circumstances, including different operation speed, pantograph type and catenary structure. Analyses on the extracted CSWs and non-CSW residual show that, with certain tolerance against measurement noise, the approach can preserve intact the characterizations of current collection quality and make anomalies easier to detect.