Fusion algorithm for data including kinematic and attribute

Yi-Nang Chung; Joy I. Z. Chen

doi:10.1117/12.217714

1 September 1995 Fusion algorithm for data including kinematic and attribute

Yi-Nang Chung, Joy I. Z. Chen

Proceedings Volume 2561, Signal and Data Processing of Small Targets 1995; (1995) https://doi.org/10.1117/12.217714
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

The main advantage of a multi-sensor fusion approach is to complement the data of one sensor with that of another sensor in order to obtain better target measurement information and to make a more accuracy estimation. In this paper, one image processing along with neural network algorithm is applied to solve the attribute information. The fundamental idea of this paper is that one decentralized estimation approach for a sensor fusion problems in which a Bayesian mathematical structure denoted 1-step maximum a posteriori estimate algorithm is applied for the data association. In such an algorithm, one also applied a techniques to combine the target attribute data to enhance the tracking results.

Citation Download Citation

Yi-Nang Chung and Joy I. Z. Chen "Fusion algorithm for data including kinematic and attribute", Proc. SPIE 2561, Signal and Data Processing of Small Targets 1995, (1 September 1995); https://doi.org/10.1117/12.217714

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