Limitations of the unscented Kalman filter for the attitude determination on an inertial navigation system

Lacambre, Jean-Baptiste; Narozny, Michel; Louge, Jean-Marie

doi:10.1109/dsp-spe.2013.6642588

Cited by 9 publications

(6 citation statements)

References 6 publications

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“…where g(•) is the nonlinear function defined in (19) and (20) and w k is the noise term with mean zero and covariance Q. The measurement model is…”

Section: Extended Kalman Filtermentioning

confidence: 99%

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Evaluating Tracking Rotations Using Maximal Entropy Distributions for Smartphone Applications

Brotchie¹,

Kealy

et al. 2021

IEEE Access

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Recursive attitude estimation of a rigid body from inertial measurements is a crucial component of many modern systems and as such, has a rich historical background of proposed techniques. Recent work has been done on tracking rotations using maximal entropy distributions. However, there has been no evaluation done on the performance of this approach using real inertial data. In this work, we investigate the performance and limitations of classical and modern probabilistic Bayesian approaches and provide a rigorous comparison to attitude estimation on the special rotation group SO(3) using maximal entropy distributions. The extended Kalman Filter and the unscented Kalman filter are derived as benchmarks in attitude estimation from low-cost inertial measurement units, commonly found in smartphones. To evaluate robustness over multiple sampling intervals, we generated synthetic directional inertial measurements from a typical low-cost 3-axes inertial measurement unit and use the Frobenius Norm as our primary metric. To further our evaluation, we took advantage of a publicly available dataset where inertial measurements are recorded from a number of off-the-shelf smartphones and the ground truth is calculated using a Motion Capture system. Our experiments demonstrate that tracking rotations using maximum entropy distributions produce a more accurate and robust solution in contrast to alternate proven Kalman approaches.INDEX TERMS Attitude estimation, extended kalman filter, inertial measurement unit, rotation group, unscented kalman filter

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“…where g(•) is the nonlinear function defined in (19) and (20) and w k is the noise term with mean zero and covariance Q. The measurement model is…”

Section: Extended Kalman Filtermentioning

confidence: 99%

“…The UKF uses sigma points to capture the characteristics of a Gaussian distribution. However, the regenerative step of the sigma points can be a major limitation in the propagation of state uncertainty [20].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Tracking Rotations Using Maximal Entropy Distributions for Smartphone Applications

Brotchie¹,

Kealy

et al. 2021

IEEE Access

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“…Inertial Navigation System (INS) is commonly used to determine the position, speed, and attitude of projectile with a high update, which consists mainly of three gyroscopes and three accelerometers. The INS has commonly been used as a means of localization for projectiles [1][2][3]. The disadvantage in use of an INS, particularly when using low-cost sensors, is due to the accumulation of errors with time due to the dead-reckoning nature of the sensor.…”

Section: Introductionmentioning

confidence: 99%

Roll Attitude Determination of Spin Projectile Based on GPS and Magnetoresistive Sensor

Ding

Guan

2017

Mathematical Problems in Engineering

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Improvement in attack accuracy of the spin projectiles is a very significant objective, which increases the overall combat efficiency of projectiles. The accurate determination of the projectile roll attitude is the recent objective of the efficient guidance and control. The roll measurement system for the spin projectile is commonly based on the magnetoresistive sensor. It is well known that the magnetoresistive sensor produces a sinusoidally oscillating signal whose frequency slowly decays with time, besides the possibility of blind spot. On the other hand, absolute sensors such as GPS have fixed errors even though the update rates are generally low. To earn the benefit while eliminating weaknesses from both types of sensors, a mathematical model using filtering technique can be designed to integrate the magnetoresistive sensor and GPS measurements. In this paper, a mathematical model is developed to integrate the magnetoresistive sensor and GPS measurements in order to get an accurate prediction of projectile roll attitude in a real flight time. The proposed model is verified using numerical simulations, which illustrated that the accuracy of the roll attitude measurement is improved.

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“…Section 5 shows the results of land vehicle experiments and ship experiments, with a significant improvement of the positioning accuracy. In order to reduce the amount of calculation and visually show the effect of this monitoring system [33,34], the classic Kalman filter is chosen to obtain the optimal solution of the time-invariant linear system.…”

Section: Introductionmentioning

confidence: 99%

A Novel Monitoring Navigation Method for Cold Atom Interference Gyroscope

Zhang

Gao

et al. 2019

Sensors

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The implementation principle of a typical three-pulse cold atom interference gyroscope is introduced in this paper. Based on its configuration and current research status, the problems of cold atom interference gyro are pointed out. The data-rate is insufficient, and it is difficult to achieve high dynamic measurement. Then, based on these two limitations, a novel design of the monitoring navigation system of the cold atom interference gyroscope (CAIG) and an intermediate-grade inertial measurement unit (IMU) was proposed to obtain the long-term position result without GPS signals, such as the Inertial Navigation System (INS) in underwater vehicles. While the CAIG was used as the external gyro, the bias of IMU and the misalignment angle between the CAIG-frame and the IMU-frame are obtained through filtering technique. The simulation test and field test demonstrated the improvements of the long-term positioning accuracy of the INS.

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Limitations of the unscented Kalman filter for the attitude determination on an inertial navigation system

Cited by 9 publications

References 6 publications

Evaluating Tracking Rotations Using Maximal Entropy Distributions for Smartphone Applications

Evaluating Tracking Rotations Using Maximal Entropy Distributions for Smartphone Applications

Roll Attitude Determination of Spin Projectile Based on GPS and Magnetoresistive Sensor

A Novel Monitoring Navigation Method for Cold Atom Interference Gyroscope

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