Estimation of GPS instrumental biases from small scale network

• Published in: Advances in space research Vol. 54; no. 5; pp. 871 - 882
• Main Authors: Ma, Guanyi, Gao, Wei, Li, Jinghua, Chen, Yanhong, Shen, Hua
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2014
• Subjects: Algorithms; Fittings; Global Positioning System; GPS; Instrumental biases; Ionosphere; Networks; Radiowave propagation; Receivers; Satellite navigation systems; Satellites; Standard deviation; TEC; China, People's Rep; Instrumental biases; TEC; GPS; Radiowave propagation; Ionosphere
• ISSN: 0273-1177; 1879-1948
• DOI: 10.1016/j.asr.2013.01.008

With 4GPS receivers located in the equatorial anomaly region in southeast China, this paper proposes a grid-based algorithm to determine the GPS satellites and receivers biases, and at the same time to derive the total electron content (TEC) with time resolution of 15min and spatial resolution of 1° by 3.5° in latitude and longitude. By assuming that the TEC is identical at any point within a given grid block and the biases do not vary within a day, the algorithm arranges unknown biases and TECs with slant path TEC from the 4 receivers’ observations into a set of equations. Then the instrumental biases and the TECs are determined by using the least squares fitting technique. The performance of the method is examined by applying it to the GPS receiver chain observations selected from 16 geomagnetically quiet days in four seasons of 2006. It is found that the fitting agrees with the data very well, with goodness of fit ranging from 0.452TECU to 1.914TECU. Having a mean of 0.9ns, the standard deviations for most of the GPS satellite biases are less than 1.0ns for the 16days. The GPS receiver biases are more stable than that of the GPS satellites. The standard deviation in the 4 receiver bias is from 0.370ns to 0.855ns, with a mean of 0.5ns. Moreover, the instrumental biases are highly correlated with those derived from CODE and JPL with independent methods. The typical precision of the derived TEC is 5TECU by a conservative estimation. These results indicate that the proposed algorithm is valid and qualified for small scale GPS network.