High-Integrity IMM-EKF-Based Road Vehicle Navigation With Low-Cost GPS/SBAS/INS

Toledo-Moreo, R.; Zamora-Izquierdo, Miguel A.; Ubeda-Miarro, B.; Gómez‐Skarmeta, Antonio F.

doi:10.1109/tits.2007.902642

Cited by 188 publications

(78 citation statements)

References 22 publications

(27 reference statements)

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“…3, integrates information from the GPS receiver, odometer, and inertial sensors (gyroscope and accelerometer), by means of an Extended Kalman Filter. Further information about this navigation unit can be found in Toledo-Moreo et al (2007).…”

Section: Navigation Systemmentioning

confidence: 99%

Telematic platform for integral management of agricultural/perishable goods in terrestrial logistics

Santa

Zamora-Izquierdo

Jara

et al. 2012

Computers and Electronics in Agriculture

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Section: Navigation Systemmentioning

confidence: 99%

Telematic platform for integral management of agricultural/perishable goods in terrestrial logistics

Santa

Zamora-Izquierdo

Jara

et al. 2012

Computers and Electronics in Agriculture

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“…Maneuvering target tracking has been widely used in many applications, such as aircraft surveillance [1,2], road vehicle navigation [3,4] and radar tracking [5][6][7]. Because of the complexity of maneuvering target motion, the single model structure is not appropriate in tracking maneuvering targets.…”

Section: Introductionmentioning

confidence: 99%

IMM Fifth-Degree Spherical Simplex-Radial Cubature Filter for Maneuvering Target Tracking

Liu¹,

Wu²

2017

Preprint

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For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named interacting multiple model fifth-degree spherical simplex-radial cubature filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and fifth-degree spherical simplex-radial cubature filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifthdegree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with IMMUKF, IMMCKF and IMM5thCKF.

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“…However, in certain circumstances, these statistics do not obey the above-mentioned distributions, and there is no closedform formula for the threshold computation. For nonGaussian noise, the extended Kalman filter (Toledo-Moreo et al 2007), Markov Chain Monte Carlo particle filter (Wang et al 2009), auxiliary particle filter (Ahn et al 2011) and genetic resampling particle filter (He et al 2013) are used in GPS positioning and integrity monitoring. The test statistic used for particle filters, i.e., the cumulative log likelihood ratio (LLR), is generated using a stochastic generator and does not obey a Gaussian-related distribution.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear fault detection threshold optimization method for RAIM algorithm using a heuristic approach

Liu

Tan

et al. 2015

GPS Solut

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The threshold value used in receiver autonomous integrity monitoring algorithms to identify faults has a significant impact on positioning integrity and GPS/ GNSS availability. The value is usually selected empirically or under certain distribution assumptions; its calculation for a non-Gaussian test statistic has not been solved. For fault detection methods using a particle filter, a new heuristic method is proposed to select an appropriate fault detection threshold value using an optimization model. In this method, a non-Gaussian cumulative log likelihood ratio (LLR) value is used as the test statistic. Its threshold is determined using an integrity risk minimization problem with an availability constraint. Since there is no closed form for this optimization model, a genetic algorithm with a local search strategy is adopted to find a near-optimal solution. Experimental results show that this method can be used to compute the non-Gaussian fault detection threshold value subject to different availability constraints. Comparisons with empirical and distribution-based methods indicate that while meeting the same probability for falsealert constraint, the probability of missed detection in the optimized approach is much lower than for other methods, especially for small numbers of errors. Since the cumulative LLR value does not exhibit obvious statistical features for any distribution, the performance of our optimized approach is stable for different test cases and satellite data sets.

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High-Integrity IMM-EKF-Based Road Vehicle Navigation With Low-Cost GPS/SBAS/INS

Cited by 188 publications

References 22 publications

Telematic platform for integral management of agricultural/perishable goods in terrestrial logistics

Telematic platform for integral management of agricultural/perishable goods in terrestrial logistics

IMM Fifth-Degree Spherical Simplex-Radial Cubature Filter for Maneuvering Target Tracking

Nonlinear fault detection threshold optimization method for RAIM algorithm using a heuristic approach

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