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access icon free Improved single-epoch single-frequency Par Lambda algorithm with baseline constraints for the BeiDou Navigation Satellite System

© The Institution of Engineering and Technology
Received 16/02/2017, Accepted 15/06/2017, Revised 12/06/2017, Published 07/07/2017

A new single-epoch single-frequency algorithm based on partial least-squares ambiguity decorrelation adjustment (Par Lambda) that employs baseline constraints is developed for BeiDou Navigation Satellite System (BDS) called Improved Par Lambda, based on the characteristics of building deformation monitoring. The floating solution of double-difference ambiguities is obtained by means of double-difference observations and least-squares method. The double-difference observation equations with baseline length constraint are composed of the equations of BDS single-frequency pseudo-range observations and carrier phase observations and the baseline length constraint equation. The least-squares principle is used to compute floating solution of double-difference ambiguities and the corresponding cofactor matrix. Based on the precision of double-difference ambiguities, the ambiguities will be divided into different levels (2, 1, 1,…, 1) and then be fixed based on the Lambda method progressively. The 1, 5 and 10 s short baseline data of BDS single-epoch single-frequency based on B1 band carrier phase were computed through this method. The results showed that, for BDS single-epoch single-frequency, the success rate and the search efficiency of fixing ambiguities of Improved Par Lambda were all better than the traditional methods and the success rate was more than 98%.

Inspec keywords: matrix algebra; least squares approximations; satellite navigation

Other keywords: carrier phase observations; BeiDou navigation satellite system; partial least-squares ambiguity decorrelation adjustment; baseline length constraint equation; Lambda method; BDS single-frequency pseudorange observations; cofactor matrix; single-epoch single-frequency Par Lambda algorithm; double-difference ambiguities; building deformation monitoring; double-difference observation equations; least-squares principle; least-squares method; floating solution

Subjects: Linear algebra (numerical analysis); Interpolation and function approximation (numerical analysis); Radionavigation and direction finding

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