Joint inversion based on a correlation constraint utilizes a linear correlation function as a structural constraint.The linear correlation function contains a denominator,which may result in a singularity as the objec...Joint inversion based on a correlation constraint utilizes a linear correlation function as a structural constraint.The linear correlation function contains a denominator,which may result in a singularity as the objective function is optimized,leading to an unstable inversion calculation.To improve the robustness of this calculation,this paper proposes a new method in which a sinusoidal correlation function is employed as the structural constraint for joint inversion instead of the conventional linear correlation function.This structural constraint does not contain a denominator,thereby preventing a singularity.Compared with the joint inversion method based on a cross-gradient constraint,the joint inversion method based on a sinusoidal correlation constraint exhibits good performance.An application to actual data demonstrates that this method can process real data.展开更多
Binary Offset Carrier(BOC) has been chosen as one of modulation methods in the future Global Navigation Satellite Systems(GNSS). Even though BOC signals can bring several advantages such as better track performance an...Binary Offset Carrier(BOC) has been chosen as one of modulation methods in the future Global Navigation Satellite Systems(GNSS). Even though BOC signals can bring several advantages such as better track performance and higher positioning accuracy, there is a drawback that the autocorrelation functions have multiple side-peaks if BOC modulation is adopted. This characteristic will lead to false acquisition and the tracking loop will be locked in false phase point. The proposed Correlation Combination Ambiguity Removing Technology(CCART) cancelled all the side-peaks of the sine-phased BOC(kn,n) signals completely by making use of two kinds of correlation functions. Two kinds of sub-correlation functions were combined separately and then final correlation function without side-peaks was acquired. The simulation results are given and compared with other techniques. It is shown that acquisition will not be degraded with the increase of k.展开更多
基金supported by the National Key Research and Development Project of China(No:2017YFC0602201)
文摘Joint inversion based on a correlation constraint utilizes a linear correlation function as a structural constraint.The linear correlation function contains a denominator,which may result in a singularity as the objective function is optimized,leading to an unstable inversion calculation.To improve the robustness of this calculation,this paper proposes a new method in which a sinusoidal correlation function is employed as the structural constraint for joint inversion instead of the conventional linear correlation function.This structural constraint does not contain a denominator,thereby preventing a singularity.Compared with the joint inversion method based on a cross-gradient constraint,the joint inversion method based on a sinusoidal correlation constraint exhibits good performance.An application to actual data demonstrates that this method can process real data.
基金supported in part by National Natural Science Foundation of China under Grant No.61372110National High Technology Research and Development Program of China (863 Program) under Grant No. 2012AA120802
文摘Binary Offset Carrier(BOC) has been chosen as one of modulation methods in the future Global Navigation Satellite Systems(GNSS). Even though BOC signals can bring several advantages such as better track performance and higher positioning accuracy, there is a drawback that the autocorrelation functions have multiple side-peaks if BOC modulation is adopted. This characteristic will lead to false acquisition and the tracking loop will be locked in false phase point. The proposed Correlation Combination Ambiguity Removing Technology(CCART) cancelled all the side-peaks of the sine-phased BOC(kn,n) signals completely by making use of two kinds of correlation functions. Two kinds of sub-correlation functions were combined separately and then final correlation function without side-peaks was acquired. The simulation results are given and compared with other techniques. It is shown that acquisition will not be degraded with the increase of k.
