Corpus ID: 235265792

A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems

  title={A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems},
  author={Jonathan Kelly and Christopher Grebe and Matthew Giamou},
We examine the problem of time delay estimation, or temporal calibration, in the context of multisensor data fusion. Differences in processing intervals and other factors typically lead to a relative delay between measurement from two disparate sensors. Correct (optimal) data fusion demands that the relative delay must either be known in advance or identified online. There have been several recent proposals in the literature to determine the delay parameter using recursive, causal filters such… Expand

Figures and Tables from this paper

Under the Sand: Navigation and Localization of a Small Unmanned Aerial Vehicle for Landmine Detection with Ground Penetrating Synthetic Aperture Radar
Field trials validated a localization accuracy and precision that enables coherent radar measurement addition and detection of radar targets buried in sand and validates the potential as an aerial landmine detection system. Expand


Incorporation of time delayed measurements in a discrete-time Kalman filter
Various methods in the literature along with a new method proposed by the authors will be presented and compared, based on "extrapolating" the measurement to present time using past and present estimates of the Kalman filter and calculating an optimal gain for this extrapolated measurement. Expand
Weak in the NEES?: Auto-Tuning Kalman Filters with Bayesian Optimization
A new “black box” Bayesian optimization strategy is developed for automatically tuning Kalman filters that can efficiently identify multiple local minima and provide uncertainty quantification on its results. Expand
Unified temporal and spatial calibration for multi-sensor systems
A novel framework for jointly estimating the temporal offset between measurements of different sensors and their spatial displacements with respect to each other is presented, enabled by continuous-time batch estimation and extends previous work by seamlessly incorporating time offsets within the rigorous theoretical framework of maximum likelihood estimation. Expand
Decentralized Filtering With Random Sampling and Delay
The problem formulation suggested in this paper constitutes a realistic framework for estimation problems with geographically dispersed sensors such as the multiple sensor tracking problem. Expand
Joint state and measurement time-delay estimation of nonlinear state space systems
  • John-Olof Nilsson, I. Skog, P. Händel
  • Mathematics, Computer Science
  • 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010)
  • 2010
This article suggests how the effect of the synchronization error from an unknown static or slowly varying measurement time-delays in a nonlinear state space system can be handled by linearizing the measurement equation in time. Expand
A General Approach to Spatiotemporal Calibration in Multisensor Systems
The framework exploits recent advances in continuous-time batch estimation and thus exists within the rigorous theoretical framework of maximum likelihood estimation, and represents the first general technique for temporal calibration in robotics. Expand
A General Framework for Temporal Calibration of Multiple Proprioceptive and Exteroceptive Sensors
This paper presents results from simulation studies and from experiments with a PR2 robot, which demonstrate accurate calibration of the time delays between measurements from multiple, heterogeneous sensors. Expand
3-D motion estimation and online temporal calibration for camera-IMU systems
This work proposes an online approach for estimating the time offset between the data obtained from different sensors in extended Kalman filter (EKF)-based methods, and demonstrates that the proposed approach yields high-precision, consistent estimates in scenarios involving both constant and time-varying offsets. Expand
Online temporal calibration for camera–IMU systems: Theory and algorithms
This work proposes an online approach for estimating the time offset between the visual and inertial sensors, and shows that this approach can be employed in pose-tracking with mapped features, in simultaneous localization and mapping, and in visual–inertial odometry. Expand
State estimation with delayed measurements considering uncertainty of time delay
State estimation problem with time delayed measurements is addressed with augmented state Kalman filter, and uncertainty of the delayed time is also resolved based on the probability distribution of the delay. Expand