Literature DB >> 32102261

The Application of Robust Least Squares Method in Frequency Lock Loop Fusion for Global Navigation Satellite System Receivers.

Mengyue Han1, Qian Wang1, Yuanlan Wen1, Min He1, Xiufeng He1.   

Abstract

The tracking accuracy of a traditional Frequency Lock Loop (FLL) decreases significantly in a complex environment, thus reducing the overall performance of a satellite receiver. In order to ensure high tracking accuracy of a receiver in a complex environment, this paper proposes a new tracking loop combining the vector FLL (VFLL) with a robust least squares method, which accurately matches the weights of received signals of different qualities to ensure high positioning accuracy. The weights of received signals are selected at the signal level, not at the observation level. In this paper, the ranges of strong and weak signals of the loop are determined according to the different expressions of the distribution function at different signal strengths, and the concept of loop segmentation is introduced. The segmentation results of the FLL are taken as a basis of the weight selection, and then combined with the Institute of Geodesy and Geophysics (IGGIII) weight function to obtain the equivalent weight matrix; the experiments are conducted to prove the advantages of the proposed method over the traditional methods. The experimental results show that the proposed VFLL tracking method has strong denoising capability under both normal- signal and harsh application environment conditions. Accordingly, the proposed model has a promising application perspective.

Entities:  

Keywords:  VFLL; loop segmentation; robust least squares; satellite navigation; signal tracking

Year:  2020        PMID: 32102261     DOI: 10.3390/s20041224

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Special Issue on GNSS Data Processing and Navigation.

Authors:  Adria Rovira-Garcia; José Miguel Juan Zornoza
Journal:  Sensors (Basel)       Date:  2020-07-24       Impact factor: 3.576

  1 in total

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