Results 221 to 230 of about 42,651 (258)

Fusion of multi-sensor data: a geometric approach

Proceedings. 1991 IEEE International Conference on Robotics and Automation, 2002
A geometric approach is presented to solve data fusion problems. The approach uses bounded-error data parameter estimation rather than the usual statistical approach. Updating the location (orientation and position) of a mobile robot in a known polygonal environment is shown as example.
A. Preciado, Dominique Meizel, Armando Segovia, Michèle Rombaut   +3 more
openaire   +1 more source

Multi-sensor fusion: an Evolutionary algorithm approach

Information Fusion, 2006
Modern decision-making processes rely on data coming from different sources. Intelligent integration and fusion of information from distributed multi-source, multi-sensor network requires an optimization-centered approach. Traditional optimization techniques often fail to meet the demands and challenges of highly dynamic and volatile information flow ...
Igor V. Maslov, Izidor Gertner
openaire   +1 more source

Multi sensor track fusion performance metrics

2016 24th Signal Processing and Communication Application Conference (SIU), 2016
Track fusion is one of the primary features in command and control systems. Track information of different sensors are combined to have a more accurate result. Criterions and metrics are required to evaluate and compare different fusion methods during development. This paper summarizes some important track fusion metrics.
openaire   +1 more source

Statistical modelling of multi-sensor data fusion

2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES), 2017
Increasing the reliability of sensor data, especially in collision avoidance applications, is of great importance and involves the development of different sensor fusion methods. To reduce the limitations and disadvantages of common fusion methods and their challenges with respect to highly automated driving, this paper proposes a statistical model of ...
M. Ahmadi-Pour, Thomas Ludwig 0009, Cristina Olaverri-Monreal   +2 more
openaire   +1 more source

Possibilistic multi-sensor fusion for humanitarian demining

2007 IEEE International Geoscience and Remote Sensing Symposium, 2007
We propose a method for combining humanitarian mine detection sensors based on possibility theory. Firstly, different features are extracted from the sensor data. Possibility distributions are then derived from the features based on prior information. After that, the combination of possibility degrees is performed in two steps, on separate sensor level
Nada Milisavljevic, Isabelle Bloch
openaire   +1 more source

Effective fusion of distorted multi-sensor data

Proceedings of the 2003 IEEE International Symposium on Intelligent Control ISIC-03, 2003
A framework for the detection of bandlimited signals by intelligently fusing the multi-nonlinear sensor data is developed. Though most sensors used are assumed to be linear, none of them individually or in series give the truly linear relationship and errors are inevitable as a result of the assumption of linearity.
Sugathevan Suranthiran, Suhada Jayasuriya   +1 more
openaire   +1 more source

Multi-Sensor Measurement and Data Fusion

IEEE Instrumentation & Measurement Magazine, 2022
Zheng Liu 0002, George Xiao 0001, Huan Liu 0002, Hanbing Wei   +3 more
openaire   +1 more source

A variational approach to multi-sensor fusion of images

Applied Intelligence, 1995
Past research into multi-modality sensor data fusion has given rise to approaches that are generally heuristic and ad hoc. In this paper we utilize the calculus of variations as the underlying framework for fusing registered images of different modalities when models relating these modalities are available.
Homer H. Pien, John M. Gauch
openaire   +1 more source

A STPHD-Based Multi-sensor Fusion Method

2012
In order to extract the peaks of PHD, a novel method STPHD has been proposed recently. This method can provide more accurate target state estimates than the general clustering algorithm such as k-means clustering. This paper presents a version of STPHD for multi-sensor scene and makes two contributions.
Zhenwei Lu, Lingling Zhao, Xiaohong Su, Peijun Ma   +3 more
openaire   +1 more source

A Review of Multi-sensor Data Fusion for Traffic

2018
Data fusion is the process of integrating multi-sources data to obtain more consistent, accurate, and beneficial information than that provided by any single data source. This paper sum the state of the data fusion field and describes the most relevant studies. We first explain data fusion and multiple sensors Then, data fusion in traffic are reviewed.
Xue Zhao, Dongbo Zhang 0001
openaire   +1 more source