dor_id: 45640

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336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

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856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/285/282

100.1.#.a: Jwo, D.J.; Chung, F.C.; Yu, K.L.

524.#.#.a: Jwo, D.J., et al. (2013). GPS/INS Integration Accuracy Enhancement Using the Interacting Multiple Model Nonlinear Filters. Journal of Applied Research and Technology; Vol. 11 Núm. 4. Recuperado de https://repositorio.unam.mx/contenidos/45640

245.1.0.a: GPS/INS Integration Accuracy Enhancement Using the Interacting Multiple Model Nonlinear Filters

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2013

264.#.1.c: 2013-08-01

653.#.#.a: Interacting multiple model; Unscented Kalman filter; Unscented particle filter; Integrated navigation

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884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/285

001.#.#.#: 074.oai:ojs2.localhost:article/285

041.#.7.h: eng

520.3.#.a: In this paper, performance evaluation for various single model nonlinear filters and nonlinear filters with interactingmultiple model (IMM) framework is carried out. A high gain (high bandwidth) filter is needed to response fast enoughto the platform maneuvers while a low gain filter is necessary to reduce the estimation errors during the uniformmotion periods. Based on a soft-switching framework, the IMM algorithm allows the possibility of using highly dynamicmodels just when required, diminishing unrealistic noise considerations in non-maneuvering situations. The IMMestimator obtains its estimate as a weighted sum of the individual estimates from a number of parallel filters matchedto different motion modes of the platform. The use of an IMM allows exploiting the benefits of high dynamic models inthe problem of vehicle navigation. Simulation and experimental results presented in this paper confirm theeffectiveness of the method.

773.1.#.t: Journal of Applied Research and Technology; Vol. 11 Núm. 4

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.1016/S1665-6423(13)71557-8

harvesting_date: 2023-11-08 13:10:00.0

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last_modified: 2024-03-19 14:00:00

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Artículo

GPS/INS Integration Accuracy Enhancement Using the Interacting Multiple Model Nonlinear Filters

Jwo, D.J.; Chung, F.C.; Yu, K.L.

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Jwo, D.J., et al. (2013). GPS/INS Integration Accuracy Enhancement Using the Interacting Multiple Model Nonlinear Filters. Journal of Applied Research and Technology; Vol. 11 Núm. 4. Recuperado de https://repositorio.unam.mx/contenidos/45640

Descripción del recurso

Autor(es)
Jwo, D.J.; Chung, F.C.; Yu, K.L.
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
GPS/INS Integration Accuracy Enhancement Using the Interacting Multiple Model Nonlinear Filters
Fecha
2013-08-01
Resumen
In this paper, performance evaluation for various single model nonlinear filters and nonlinear filters with interactingmultiple model (IMM) framework is carried out. A high gain (high bandwidth) filter is needed to response fast enoughto the platform maneuvers while a low gain filter is necessary to reduce the estimation errors during the uniformmotion periods. Based on a soft-switching framework, the IMM algorithm allows the possibility of using highly dynamicmodels just when required, diminishing unrealistic noise considerations in non-maneuvering situations. The IMMestimator obtains its estimate as a weighted sum of the individual estimates from a number of parallel filters matchedto different motion modes of the platform. The use of an IMM allows exploiting the benefits of high dynamic models inthe problem of vehicle navigation. Simulation and experimental results presented in this paper confirm theeffectiveness of the method.
Tema
Interacting multiple model; Unscented Kalman filter; Unscented particle filter; Integrated navigation
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

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