Theories And Methods In Tight Integration Of Ambiguity-fixed PPP And INS

For users in the mobile surveying and mapping areas, such as vehicular mobile surveying, aerial photogrammetry, and shipborne bathymetry, they eagerly need the surveying platform's position, velocity and attitude information with high accuracy and frequency. The paper proposes a new integration that is the tight integration of ambiguity-fixed PPP and INS. The new integration that only requires one rover GNSS receiver can achieve centimeter-level and stable positioning accuracy by using PPP ambiguity fixing techniques, and its velocity and attitude accuracy is comparable to that of the DGNSS/INS integration. Owing to no base stations to be deployed, the new integration is very suitable for mobile surveying and mapping tasks over large areas and reduces the tasks' cost and complexity; therefore, it becomes a new alternative for mobile surveying and mapping users. The paper makes a systemic study around the tight integration of ambiguity-fixed PPP and INS, which is the paper's core work. Innovation points and key results are summarized as follows,(1) The model of ambiguity-fixed GPS PPP based on integer phase clock products and single-difference-between-satellites observations is derived. A cascaded ambiguity fixing strategy with special regard to quality control(CAFQC) is proposed. Fifty tests using IGS data present that the position error dramatically drops from decimeter level to centimeter level by ambiguity fixing which converts phase observations to accurate and absolute ranges. A vehicular test demonstrates CAFQC remarkably improves the ambiguity fixing effectiveness and reliability.(2) It usually costs a long time for GPS PPP to get its first fixed solution. GLONASS observations should be added to GPS PPP to shorten the time to first fixed solution(TFFS). Forty tests using IGS data present that the mean TFFS of GPS PPP is significantly reduced and the positioning accuracy and reliability is improved by adding GLONASS. A vehicular test illustrates that GPS-only PPP has no fixed solutions due to unideal observation environment while GPS+GLONASS PPP still realizes ambiguity fixing.(3) The model of the tight integration of ambiguity-fixed PPP and INS is derived and implemented, which is the core work of the paper. Two vehicular tests are used to validate the model. The results show that once the ambiguities are successfully fixing, the new integration immediately gets centimeter-level positioning accuracy but with no base stations. Its velocity and attitude accuracy is comparable to that of the DGNSS/INS integration. When the ambiguity fixing is failed due to the weak GNSS signals, successful re-fixing is rapidly achieved due to INS' binding effect.(4) When the GNSS signals are obstructed by outside environment, PPP has to face re-convergence and re-fixing problems. When the PPP/INS integration is used, rapid re-convergence and re-fixing of PPP can be achieved aided by the INS over short blockage period. If the new cycle-slip correction method proposed in the paper is used in the integration, instantaneous re-convergence and re-fixing of PPP will be achieved. Two vehicle tests validate the performance of the new cycle-slip correction method. It should be noted that cycle-slip correction ability would decline with the extension of the GNSS signal blockage period. The tests also show the tactical INS used in the paper has no benefit in accelerating initial-convergence of PPP.(5) The backward filter of the tight integration of PPP and INS is designed. Forward backward smoothing(FBS) algorithm suitable for the new integration is proposed, FBS here is capable of simultaneously improving all solutions' accuracy, especially the position, at initialand re- convergence segments and GNSS blockage segments(i.e. INS-only segments). Two vehicular tests evaluate the actual effectiveness of FBS. The tests also find that better position is achieved by cycle-slip correction while carrying out FBS.(6) Quality checking for the solutions of the tight integration of PPP and INS is systemically researched. A quality checking method for the solutions using internal information from the tight filter is proposed. Eight kinds of internal information are analyzed and evaluated by using three vehicular tests. As two of the eight, ambiguity fixing information evidently enhances the checking effectiveness for position; the checking ability of the forward and backward discrepancy is comprehensive. The method can be treated as reference and decision basis for the surveying and mapping users.