Cascaded Kalman Filters for Accurate Estimation of Multiple Biases, Dead-Reckoning Navigation, and Full State Feedback Control of Ground Vehicles

Bevly, David M.; Parkinson, Bradford W.

doi:10.1109/tcst.2006.883311

Cited by 94 publications

(49 citation statements)

References 30 publications

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“…The noise was modelled as band-limited white noise with a sample time of 0.002 s, and the amplitude of the noise was tuned to emulate measurements taken during braking tests with a full-scale vehicle [4]. Accelerometer bias, however, was omitted, since algorithms exist to estimate this online [31].…”

Section: Observer Resultsmentioning

confidence: 99%

A high performance pneumatic braking system for heavy vehicles

Miller

Cebon

2010

Vehicle System Dynamics

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Section: Observer Resultsmentioning

confidence: 99%

A high performance pneumatic braking system for heavy vehicles

Miller

Cebon

2010

Vehicle System Dynamics

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“…Air maneuvering alignment through improvement of observability for the SINS/GNSS integrated navigation system during aircraft maneuvering is often an effective means to improve the integrated navigation precision during flight [33][34][35][36]. Specific to this problem, this subsection introduces a new SINS/GNSS air maneuvering alignment method based on system state variable observability analysis and lever arm effect error compensation [37] to compensate the lever arm effect error between the GNSS antenna and the SINS and determine the feedback factor according to the observability of each state variable.…”

Section: An Air Maneuvering Alignment Methods Based On Observability Amentioning

confidence: 99%

INS/GNSS Integrated Navigation Method

Quan

Gong

Fang

et al. 2015

INS/CNS/GNSS Integrated Navigation Technology

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Ship intertial navigation system (SINS) and global navigation satellite system (GNSS) are two kinds of common navigation equipments with respect to the advantages and disadvantages during application. The former has strong autonomy, high short-term precision, and continuous output, but errors accumulates with time; the latter has high positioning and velocity measurement precision and errors do not accumulate with time, but has incontinuous output information and susceptibility to interference. Integration of the two to realize complementary advantages will significantly improve overall performance of the navigation system. At present, the SINS/GNSS integrated navigation system has been widely used in fields such as aviation, aerospace, and sailing, and it is a relatively ideal integrated navigation system.How to give full play to overall performance of the SINS/GNSS integrated navigation to truly achieve complementary advantages of the two is a problem during practical application of the navigation system. Position and velocity or pseudorange and pseudorange rate are generally used as the observation quantities of the SINS/GNSS integrated navigation, free of attitude measurement information, but for certain application, such as the onboard high-resolution earth observation, the integrated navigation system is required to maintain high attitude precision besides possessing high-precision position information. In this way high requirements are made for filtering model precision, filtering algorithm precision, and air alignment precision of the SINS/GNSS integrated navigation system, i.e., attitude and inertial component errors of the SINS are required to be estimated while estimating the position and velocity errors of the SINS. In addition, the navigation error of a pure SINS diverges in case of GNSS signal lock losing caused by electromagnetic interference or block suffered by the GNSS signal. It is thereby required to study error inhibition and compensation techniques of the SINS during the GNSS lock losing period to maintain continuous and high-precision navigation.This chapter systematically discusses the principle, method, and engineering application problem of the SINS/GNSS integrated navigation system. First, it discusses

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“…However, during braking, wheel speeds cannot be relied upon to reflect vehicle speed. Reliable speed estimation algorithms, which have been considered in [10,[37][38][39][40][41][42], would need to be implemented in practice. The CVDC slip control braking system also relies on accurate vehicle speed information, and in these experiments it also used the longitudinal speed measurement from the RT3022.…”

Section: Test Vehicle and Instrumentationmentioning

confidence: 99%

Sideslip estimation for articulated heavy vehicles at the limits of adhesion

Morrison

Cebon

2016

Vehicle System Dynamics

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Various active safety systems proposed for articulated heavy goods vehicles (HGVs) require an accurate estimate of vehicle sideslip angle. However in contrast to passenger cars, there has been minimal published research on sideslip estimation for articulated HGVs. Stateof-the-art observers, which rely on linear vehicle models, perform poorly when manoeuvring near the limits of tyre adhesion. This paper investigates three nonlinear Kalman filters (KFs) for estimating the tractor sideslip angle of a tractor-semitrailer. These are compared to the current state-of-the-art, through computer simulations and vehicle test data. An unscented KF using a 5 degrees-of-freedom single-track vehicle model with linear adaptive tyres is found to substantially outperform the state-of-the-art linear KF across a range of test manoeuvres on different surfaces, both at constant speed and during emergency braking. Robustness of the observer to parameter uncertainty is also demonstrated. ARTICLE HISTORY

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Cascaded Kalman Filters for Accurate Estimation of Multiple Biases, Dead-Reckoning Navigation, and Full State Feedback Control of Ground Vehicles

Cited by 94 publications

References 30 publications

A high performance pneumatic braking system for heavy vehicles

A high performance pneumatic braking system for heavy vehicles

INS/GNSS Integrated Navigation Method

Sideslip estimation for articulated heavy vehicles at the limits of adhesion

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