Online estimation of inter-frequency/system phase biases in precise positioning

Global Navigation Satellite Systems (GNSS) play an important role in precise positioning for geodesy and surveying engineering. The key to the real-time GNSS precise positioning is the instantaneous integer ambiguity resolution. However, some of the biases in carrier phase observations cannot be removed by differencing between either stations or satellites, so the integer nature of the double-differenced ambiguities is destroyed and thus the ambiguities cannot be fixed to integers. Two typical biases are the inter-frequency bias (IFB) in GLObal NAvigation Satellite System (GLONASS) data processing and the inter-system bias (ISB) in multi-GNSS integration. Hence, the main objective of this thesis is the investigation, estimation and correction of these biases in carrier phase observations to achieve better positioning accuracy, reliability and availability through the improvement of its ambiguity resolution. The estimated parameters of the carrier phase IFB and ISB are usually the IFB rate and the fractional ISB (F-ISB), respectively. Most of the current methods estimate IFB rate or F-ISB together with the float ambiguities and usually need observations of relatively long time due to their high correlation. Theoretically, the performance of the ambiguity resolution depends on the quality of the given IFB rate/F-ISB value if the observations are precisely modelled. In other words, the closer the given IFB rate/F-ISB value to the truth value is, the better the resolution will be. Therefore, the RATIO in the ambiguity fixing can be applied as the qualification factor of the IFB rate/F-ISB value. Based on this fact, a new methodology based on particle filter is developed to estimate these biases in both post-processing and real-time mode in this study. In the proposed method, the IFB/ISB is represented by its samples (i.e. particles) with the weights determined by the designed likelihood function of the related RATIO given the sample values, so that the true bias value can be estimated successfully by the particle filter approach. The integer nature of the ambiguities in the models with IFB/ISB parameters is well utilised in the ambiguity resolution with the given IFB rate/F-ISB values. Thus, the new method can significantly reduce the convergence time and increase the reliability of the estimation without a priori values. Besides, when more than one bias parameter is included in the model, the multi-dimensional particle filter approach is developed to estimate more than one bias parameter simultaneously in GNSS precise positioning. In this case, the aforementioned benefits of the method are obviously enlarged. In the GLONASS data processing with a nonzero IFB rate, the method can estimate the IFB rate from observations of a few epochs. With the estimated IFB rate, the GLONASS fixed solutions are as accurate as the GPS fixed solutions in the experiments with short baselines. In addition, the bias in the estimated IFB rate when the state noise is set to a very small value or even zero is significant, but this bias can be removed by utilising the regularized particle filter (RPF) and the precision of the estimated IFB rate is continuously improved by new observations. An approach for adapting the number of particles in the estimation of the IFB rate is also proposed to reduce the calculation burden by relating the number of particles to the standard deviation of the weighted particles. In the estimation of the F-ISB in multi-GNSS integration, the new method based on particle filter largely reduces the convergence time and improves the reliability of F-ISB estimation when satellites from each system are not sufficient for independent positioning. Due to the periodic characteristics of ISB, the F-ISB particles can be separated into different groups leading to the divergence of the filtering. This problem is solved successfully by introducing the cluster analysis method which can detect the groups automatically so that they can be shifted together into one group in the filtering. The estimation of the phase IFB rate with the new method enables the usage of GLONASS in real-time kinematic positioning even when the IFB between receivers is large. The estimation of the phase F-ISB with the new method allows the precise positioning to be carried out with fewer satellites from each system than the number of satellites required by the current methods. Therefore, the IFB rate/F-ISB estimation significantly extends the application of real-time kinematic GNSS positioning. It also proves that the developed new method is capable of estimating biases quickly and accurately, which initiates a new way of bias estimation in GNSS precise positioning.

Author dc:creator

• Tian, Yumiao

Advisor dc:contributor.advisor

• Neitzel, Frank

Licence dc:rights.uri

• https://creativecommons.org/licenses/by/4.0/

Language dc:language.iso

en

Identifier URI

http://dx.doi.org/10.14279/depositonce-5538

OAI identifier oai:identifier

oai:depositonce.tu-berlin.de:11303/5951