Abstract
Reliable and rapid ambiguity resolution (AR) is the key to fast precise point positioning (PPP). We propose a modified partial ambiguity resolution (PAR) method, in which an elevation and standard deviation criterion are first used to remove the low-precision ambiguity estimates for AR. Subsequently the success rate and ratio-test are simultaneously used in an iterative process to increase the possibility of finding a subset of decorrelated ambiguities which can be fixed with high confidence. One can apply the proposed PAR method to try to achieve an ambiguity-fixed solution when full ambiguity resolution (FAR) fails. We validate this method using data from 450 stations during DOY 021 to 027, 2012. Results demonstrate the proposed PAR method can significantly shorten the time to first fix (TTFF) and increase the fixing rate. Compared with FAR, the average TTFF for PAR is reduced by 14.9% for static PPP and 15.1% for kinematic PPP. Besides, using the PAR method, the average fixing rate can be increased from 83.5% to 98.2% for static PPP, from 80.1% to 95.2% for kinematic PPP respectively. Kinematic PPP accuracy with PAR can also be significantly improved, compared to that with FAR, due to a higher fixing rate.
Highlights
Integer carrier phase ambiguity resolution (AR) is the key to fast and high-precision GlobalPositioning System (GPS) positioning
In order to investigate the effect of partial ambiguity resolution (PAR) on the performance of Precise point positioning (PPP), we propose a modified PAR method, based on the method of Wang and Feng [5], to find a subset of decorrelated ambiguities which can be fixed with high confidence
The results using two processing methods are analyzed to assess the performance of our modified PPP PAR methods, including the time to first fix (TTFF), fixing rate and positioning accuracy
Summary
Integer carrier phase ambiguity resolution (AR) is the key to fast and high-precision GlobalPositioning System (GPS) positioning. Integer carrier phase ambiguity resolution (AR) is the key to fast and high-precision Global. The accuracy and reliability of estimates benefit much more with more ambiguities correctly fixed, it is not always optimal to fix all the ambiguities because the probability of successfully fixing them decreases and the computational burden increases with increasing number of ambiguities. For this reason, partial ambiguity resolution (PAR) methods were proposed in order to maintain a sufficiently high success rate [1]. Researchers have focused on fixing integer ambiguities for GPS PPP, and several methods have been proposed [7,8,9,10,11,12,13]
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