A Multi-frequency Multi-mode GNSS Generalized Absolute Code Bias Estimation Method

Abstract

The invention relates to a multi-frequency multi-mode GNSS generalized absolute code bias estimation method. The method includes the steps of redefining and classifying the current multi-frequency multi-mode GNSS code bias, constructing a geometry-free observation equation and an ionosphere-free observation equation respectively by using original pseudo-range observation data of a multi-frequencymulti-mode GNSS observation network, fully expressing the code bias in the observation equations, according to the discriminability of various bias parameters in a design matrix, recombining the biasparameters combined with the condition number of the matrix rank deficiency, and estimating the code bias and other parameters by least squares; and by introducing the same observation standard as anexisting clock difference product, converting a relative code bias parameter into an absolute code bias parameter. The method of the invention can provide a quasi-absolute code bias value for an original observation value, provides a simple and uniform method of bias correction for navigation and positioning users, and greatly reduces the complexity of multi-frequency multi-mode GNSS data processing.

Description

technical field [0001] The invention belongs to the field of GNSS data processing, and relates to a multi-frequency multi-mode GNSS generalized absolute code deviation estimation method. Background technique [0002] The Global Navigation Satellite System (GNSS for short) is a major national space and information infrastructure, which plays an important role in national economic construction and national defense security. Following the GPS of the United States and the GLONASS system of Russia, the European Union has built the Galileo system, and my country is also vigorously developing the Beidou Satellite Navigation System (BDS for short) with independent intellectual property rights. Satellite navigation has entered a new era of multi-GNSS competition and cooperation from a single system monopoly. At present, more than 80 GNSS satellites in orbit provide satellite signals of more than ten different frequencies to users around the world. With the modernization of GPS / GLON...

AI Technical Summary

Problems solved by technology

Taking differential code bias estimation as an example, the existing methods ignore the characteristics of GLONASS frequency division multiple access, and use an estimation method similar to GPS (that is, the receiver DCBs of different satellites are the same), resulting in the differential code bias estimation accuracy of GLONASS and low reliability

[0005] 2) The development of multi-frequency and multi-mode GNSS makes traditional differential code bias correction more complicated. Users need to derive the correct correction method according to specific observation models (single-frequency / dual-frequency / triple-frequency, combination / non-combination, etc.), This increases the difficulty for ordinary navigation and positioning users

[0006] 3) Code-related deviations include differential code deviations, inter-frequency deviations, inter-system deviations, etc. Currently, only DCB products are available to ordinary navigation and positioning users, and there is still a lack of IFB and ISB products

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