Particle-filtering-based real-time tracking and precise estimation method of phase inter-system bias of GNSS

Abstract

The invention discloses a particle-filtering-based real-time tracking and precise estimation method of a phase inter-system bias of a GNSS. The method comprises: step one, data preprocessing is carried out and a satellite ephemeris value, a current epoch pseudo-range observation value and a current epoch phase observation value are inputted; step two, intra-system and inter-system observation value equations are established and linearization is carried out to obtain a single-epoch normal equation or an epoch-accumulative normal equation; step three, a GNSS observation value normal equation inter-system bias is corrected, the normal equation is calculated and a particle filter weight is updated, and according to a weighted particle, a numerical value of a fractional part of a phase inter-system bias and a particle mean square root are calculated; and step four, the previous three steps are repeated, the value of the fractional part of the phase inter-system bias of the GNSS is tracked in real time to realize real-time tracking; or the previous three steps are repeated, a phase inter-system bias value is estimated precisely and the intra-system and inter-system double-different full-cycle fuzziness values are fixed to realize precise positioning. Therefore, real-time tracking and precise estimation of the phase inter-system bias of the GNSS are realized efficiently; and indistinctive multi-mode GNSS precise positioning of the system is realized.

Description

technical field [0001] The invention relates to the technical field of satellite positioning systems and positioning measurement, in particular to a method for real-time tracking and precise estimation of deviations between GNSS phase systems based on particle filtering. Background technique [0002] The global navigation satellite system GNSS is developing rapidly. In the near future, the systems that can be used include at least the GPS of the United States, GLONASS of Russia, BDS of China and Galileo of the European Union, etc.; and the local area system QZSS of Japan and NAVIC of India; the total number of available satellites exceeds 100 satellites, nearly 20 carrier frequencies; these frequencies have many overlaps or similarities. In GNSS multi-system combined positioning, the corresponding observations can be put together to form double-difference observations between systems, so as to make full use of observation information; At the receiver end, satellite signals f...

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Problems solved by technology

[0002] The global navigation satellite system GNSS is developing rapidly. In the near future, the systems that can be used include at least the GPS of the United States, GLONASS of Russia, BDS of China and Galileo of the European Union, etc.; and the local area system QZSS of Japan and NAVIC of India; the total number of available satellites exceeds 100 satellites, nearly 20 carrier frequencies; these frequencies have many overlaps or similarities. In GNSS multi-system combined positioning, the corresponding observations can be put together to form double-difference observations between systems, so as to make full use of observation information; At the receiver end, satellite signals from different systems have differences in hardware paths, data processing, and initial phase; therefore, an inter-system phase bias (Inter-System Bias, ISB) at the receiver end will be generated after double-difference; due to the exists, so that the double-difference ambiguity between the systems is not an integer, so it cannot be fixed as an integer in the ambiguity fixation; but if the ISB is known, it can be corrected in the double-difference observation value or the corresponding method equation to restore the ambiguity The whole-cycle characteristics of the system, and finally realize the fixation of the double-difference ambiguity between the systems; the inter-system deviation ISB can be divided into two parts, which are the part that is an integer multiple of the wavelength and the part that is less than one week (Fractional ISB, F-ISB); the former can be Neglect, the latter needs to be accurately estimated or corrected; traditional processing methods include post-processing method, assumed deviation value and variance method; the former first accurately solves the integer ambiguity and then reverses the error value. When the degree resolution is important, it will fail because it cannot successfully fix the integer ambiguity; the latter will have the opposite effect when the bias value assumed is far from the true value, affecting the ambiguity fixation in the bias estimation.

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