#### DMCA

## Evaluation of Sensors in Modern Smartphones for Vehicular Traffic Monitoring

### Citations

3859 |
A new approach to linear filtering and prediction problems,” Trans.
- Kalman
- 1960
(Show Context)
Citation Context ...tations as well as a second order KF for the translation are given. The Kalman Filter, as introduced by Rudolf Emil Kalman describes a recursive solution to the Linear Fitting and Prediction Problems =-=[8]-=-. The filter works in the style of a predictor-corrector estimator, minimizing the estimated error covariance and therefore is optimal in that sense. For further reading, please refer to [9] [10]. The... |

1146 | An Introduction to the Kalman Filter.
- Welch, Bishop
- 2001
(Show Context)
Citation Context ...blems [8]. The filter works in the style of a predictor-corrector estimator, minimizing the estimated error covariance and therefore is optimal in that sense. For further reading, please refer to [9] =-=[10]-=-. The notion of recursive means that the KF does not require all previously measured or calculated data but has an integrated memory and therefore only relies on the last estimated and the current mea... |

464 |
Stochastic Models, Estimation, and Control.
- Maybeck
- 1982
(Show Context)
Citation Context ... Problems [8]. The filter works in the style of a predictor-corrector estimator, minimizing the estimated error covariance and therefore is optimal in that sense. For further reading, please refer to =-=[9]-=- [10]. The notion of recursive means that the KF does not require all previously measured or calculated data but has an integrated memory and therefore only relies on the last estimated and the curren... |

107 |
Virtues of the haversine.
- Sinnott
- 1984
(Show Context)
Citation Context ...p = 2atan2 (√ ap, √ 1− ap ) p(k) = cp · 6.371 · 106m p ∈ {x, y}, k ∈ I where p∗GPS(0), p ∈ {x, y} denotes the initial value of the latitude or longitude respectively. For further reading we recommend =-=[14]-=-. In a next step the angular values are merged and corrected by the use of the KF for rotational movement, given in section IV-C. Due to the fact, that the device’s orientation relative to the vehicle... |

51 | High-Performance Wide-Area Optical Tracking The HiBall Tracking System”,
- Welch, Bishop, et al.
- 2001
(Show Context)
Citation Context ... 0 0 0 0 1 ] xk + vk (17) More information about Kalman filter, its application and the estimation of the error covariances (process noise and measurement noise) can be found in [6], [8], [10], [11], =-=[12]-=- and [13]. E. Fusioning Fusioning of the available data is done in four distinct steps. First, the recent data vector m = t∗ x∗GPS y∗GPS φ θ ψ φ̇ θ̇ ψ̇ ẍ ÿ z̈ σ2GPS ... |

8 |
A.: Low cost two dimension navigation using an augmented Kalman filter/Fast Orthogonal Search module for the integration of reduced inertial sensor system and Global Positioning System. Transportation Research Part C. Aticle in press
- Shen, Georgy, et al.
- 2011
(Show Context)
Citation Context ...e of this filter is that it provides us a complete model for position, velocity and acceleration while having measurement data for position and acceleration. This assumption is also backed up by [5], =-=[6]-=-, [7]. B. Kalman Filter This section gives a brief introduction to the Kalman Filter (KF). Furthermore the evolution of a first order KF for rotations as well as a second order KF for the translation ... |

7 |
On Quaternions: Or a New System
- Hamilton
(Show Context)
Citation Context ... is arbitrary the acceleration axes have to be transformed from device coordinate system to the global coordinate system. This rotation is performed by the use of quaternions and the Hamilton formula =-=[15]-=-. Finally, the normalized acceleration values together with the transformed position data, (pk, p̈k) with p ∈ {x, y, y} and k ∈ I, now are merged by use of the KF for translations, given in section IV... |

6 |
Central limit theorem. From MathWorld–A Wolfram Web Resource. http://mathworld.wolfram.com/CentralLimitTheorem.html, 2004. last checked
- Weisstein
- 2004
(Show Context)
Citation Context ...an independent and identically distributed (iid) variate Xi, i ∈ I with an arbitrary probability distribution P (xi) with mean µi and a finite variance σ2i , we conclude, by the Central Limit Theorem =-=[4]-=- that each sensor has a cumulative distribution function Fj(t), j ∈ J which approaches a normal distribution Nj(µj , σ2j ). Further, we state that the measured µj of each sensors cumulative distributi... |

4 |
developer,” http://developer.android.com, July 2011, [accessed
- Google
(Show Context)
Citation Context ...and points upwards and the z axis points towards the outside of the front face of the screen. In this system, coordinates behind the screen have negative z values. For further reading please refer to =-=[3]-=-. B. Sensor API The three relevant MEMS sensors, namely the accelerometer, the gyroscope and the magnetic field sensor are used in addition with the GPS adapter to provide a clear picture of the real ... |

4 |
Fuzzy adaptive Kalman filtering for DR/GPS
- Zhang, Wei
- 2003
(Show Context)
Citation Context ...this filter is that it provides us a complete model for position, velocity and acceleration while having measurement data for position and acceleration. This assumption is also backed up by [5], [6], =-=[7]-=-. B. Kalman Filter This section gives a brief introduction to the Kalman Filter (KF). Furthermore the evolution of a first order KF for rotations as well as a second order KF for the translation are g... |

3 |
Europe in figures. Eurostat yearbook
- EUROSTAT
- 2007
(Show Context)
Citation Context ...ast growth of the logistic sector that adds more and more heavy traffic on our roads. In 2007, a majority of three quarters (76.4%) of the freight in the European Union was realized by road transport =-=[1]-=-. The problems that arise with the growing traffic affect economy as well as ecology. Traffic congestion causes many side-effects such as increased pollution, reduced mobility and road safety concerns... |

3 |
Optimization approach to adapt Kalman filters for the real-time application of accelerometer and gyroscope signals’filtering [J
- Kownacki
(Show Context)
Citation Context ... = [ 1 0 0 0 0 1 ] xk + vk (17) More information about Kalman filter, its application and the estimation of the error covariances (process noise and measurement noise) can be found in [6], [8], [10], =-=[11]-=-, [12] and [13]. E. Fusioning Fusioning of the available data is done in four distinct steps. First, the recent data vector m = t∗ x∗GPS y∗GPS φ θ ψ φ̇ θ̇ ψ̇ ẍ ÿ z̈ σ2GPS ... |

1 |
Advances applications of Kalman filters and nonlinear estimations in aerospace systems
- Maybeck
- 1983
(Show Context)
Citation Context ...antage of this filter is that it provides us a complete model for position, velocity and acceleration while having measurement data for position and acceleration. This assumption is also backed up by =-=[5]-=-, [6], [7]. B. Kalman Filter This section gives a brief introduction to the Kalman Filter (KF). Furthermore the evolution of a first order KF for rotations as well as a second order KF for the transla... |