carrier phase-based raim using a gaussian sum filter

Paper number

IAC-09.B2.2.10

Author

Mr. Ho Yun, Korea, Republic of

Coauthor

Ms. Junesol Song, Korea, Republic of

Coauthor

Mr. Changdon Kee, Seoul National University, Korea, Republic of

Year

2009

Abstract

Pseudorange-based RAIM (PRAIM) has been investigated for many years and is used in various applications. However, for high accuracy applications, it has a limitation because the noise levels of pseudorange measurements are fairly large. In this case, we can use carrier phase measurements and should use a carrier phase-based RAIM (CRAIM). Conventional CRAIM algorithms have been used by direct extension of PRAIM and assumed a Gaussian measurement error distribution. However, the carrier phase error does not follow the Gaussian distribution perfectly, and therefore the performance of a conventional CRAIM algorithm is degraded.
To address this problem, we propose a new CRAIM algorithm using Gaussian sum filters. A Gaussian sum filter can deal with any system nonlinearity or noise distribution, and accurately present the posterior distributions of states. In this paper, a Gaussian mixture parameter optimization technique is introduced and a detailed CRAIM algorithm using a Gaussian sum filter is described.
Simulation results show that the proposed algorithm detects about 25% smaller faults and generates about 30% lower protection levels than the conventional CRAIM algorithm that uses the overbounded Gaussian model. These results imply that it can provide better accuracy and availability performance just by changing the filtering algorithm.

Abstract document

IAC-09.B2.2.10.pdf

Manuscript document

IAC-09.B2.2.10.pdf (🔒 authorized access only).

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