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Multi sensor data fusion with filtering.
| Content Provider | CiteSeerX |
|---|---|
| Author | Wasniowski, Richard A. |
| Abstract | Abstract:- The purpose of data fusion is to produce an improved model or estimate of a system from a set of independent data sources. There are various multisensor data fusion approaches, of which Kalman filtering is one of the most significant. Methods for Kalman filter based data fusion include measurement fusion and state fusion. This paper gives a simple a review of fusion and state fusion, and secondly proposes new integrated method of state fusion based on fusion procedures at the prediction and update level. To illustrate application, a simple example is performed to evaluate the proposed method. Key-Words:-Multisensor data fusion, sensors network, data fusion, filtering. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Data Fusion Multi Sensor Data Fusion State Fusion Various Multisensor Data Fusion Approach Independent Data Source Multisensor Data Fusion Update Level Improved Model New Integrated Method Fusion Procedure Sensor Network Kalman Filtering Kalman Filter Measurement Fusion Simple Example |
| Content Type | Text |
| Resource Type | Article |
