Network RTK solution method

A network and calculation technology, applied in the field of network RTK calculation, can solve the problem of low fixed rate of double-difference integer ambiguity in the baseline, achieve good user experience, improve accuracy, and increase accuracy

Active Publication Date: 2017-12-01
QIANXUN SPATIAL INTELLIGENCE INC
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Problems solved by technology

[0019] An object of the present invention is to provide a network RTK solution method, improve the accuracy and reliability of the fixed baseline double-difference integer ambiguity in network RTK, and solve the problem that the fixed rate of baseline double-difference integer ambiguity is not high in some areas question

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  • Network RTK solution method

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[0041] The network RTK calculation method of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0042] figure 1 It is a flowchart of the network RTK solution method of the present invention, such as figure 1 As shown, the network RTK solution method of this example includes:

[0043] Step 1: According to the atmospheric (ionosphere and troposphere) scale factor, jointly solve the parameters of the baseline and atmospheric (ionosphere and troposphere) delay models involved in the GNSS network,

[0044] Jointly solve the parameters of various baselines (such as receiver clock error and carrier phase ambiguity) and double-difference atmospheric (current layer and troposphere) delay model parameters formed between the base stations in the network RTK, that is, use the same The filters estimate all baseline parameters and atmospheric parameters simultaneously. According to the current epoch, the ionospheric and tropos...

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Abstract

A network RTK solution method according to the invention comprises a first step of joint solution of the baseline involved in a GNSS network and atmosphere (ionosphere and troposphere) model parameters according to a scale factor of the atmosphere (ionosphere and troposphere); a second step of floating point ambiguity closed loop constraint; a third step of integer double-difference ambiguity searching; a fourth step of integer ambiguity closed loop check; a fifth step of integer ambiguity constraint, solving of the atmosphere (ionosphere and troposphere) model parameters, and solving, by using the constrained integer ambiguity, of a new scale factor of the atmosphere (ionosphere and troposphere) for the use in the next epoch (feedback to the first step); and a sixth step of generation of VRS observation data and the like. The network RTK solution method of the invention can improve the accuracy and reliability of the baseline double-difference integer ambiguity fixing in the network RTK and solve the problem that the fixing rate of the baseline ambiguity in some areas is not high which leads to the decline of the network RTK performance.

Description

technical field [0001] The present invention relates to a positioning technology, in particular to a network RTK solution method, which is used to improve the accuracy and reliability of the fixed ambiguity of the baseline in the network RTK, and solve the problem that the fixed rate of the ambiguity of the baseline in some areas is not high. This leads to the problem of network RTK performance degradation. Background technique [0002] A major error source of the Global Navigation Satellite System (GNSS) in satellite positioning is the additional atmospheric delay caused by atmospheric refraction when the satellite signal propagates from the satellite to the receiver. The atmospheric delay mainly includes the ionosphere and Tropospheric induced ionospheric delay and tropospheric delay. The paths through which the satellite signal transmitted by a satellite reaches two receivers with similar geographical locations are basically similar, so the atmospheric delay caused by at...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S19/29G01S19/37G01S19/23
CPCG01S19/235G01S19/29G01S19/37
Inventor 易玉丹刘莎项冬何锡扬崔红正范国泽赖乃斌
Owner QIANXUN SPATIAL INTELLIGENCE INC
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