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Fuzzy Neural Network Information Fusion Technology Based on Network Centric Warfare

Author: ZhangCuiCui
Tutor: ZongChengGe
School: Harbin Institute of Technology
Course: Information and Communication Engineering
Keywords: Multi-sensor information fusion Multi-target tracking Data Association Fuzzy Neural Network
CLC: TP202
Type: Master's thesis
Year: 2009
Downloads: 96
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Abstract


Network-centric warfare is proposed by the United States to adapt to the development of future information warfare, military construction and the guiding ideology of the joint operations and achieved initial success in the war in Afghanistan and the Iraq war. In the military field, the idea of ??network-centric warfare has caused a revolutionary change. Information fusion technology is facing one of the key technologies for network-centric warfare, is of great significance for the effective implementation of the network warfare. The multi-target tracking technology of multi-sensor information fusion technology in the field of target tracking application examples around the multi-target tracking and multi-sensor target tracking achieve both. The core of the multi-target tracking technology is data association. The data association problem in the the sensor observation process and the uncertainty of the environment of the multi-target tracking, data associated with ambiguity. Traditional multi-target tracking data association algorithm nearest neighbor the NNDA algorithm, Joint Probabilistic Data Association (JPDA) algorithm, but the traditional algorithm contradiction between the prevalence of the associated time-consuming and associated accuracy. Problems of the causes of the problem of data association and data association algorithm, this paper proposed a new data association algorithm, fuzzy neural network data association algorithm (FNDA). FNDA in the process of multi-target tracking data association algorithm using fuzzy neural network structures and algorithms, while non-status information of the target, the Doppler frequency and radar target cross-sectional area, is introduced into the data related to improve multi-target tracking capability. The algorithm fuzzy reasoning and neural network combines the advantages of a new solution to solve the problem of data association target tracking. Three kinds of data FNDA, NNDA, JPDA association algorithm to do a comparative analysis, simulation results show that the: NNDA algorithm associated with the shortest time-consuming, but the associated minimum accuracy; the JPDA associated accuracy FNDA JPDA in multi-target tracking, the association too time-consuming, real-time is not good; FNDA on the associated time-consuming and associated accuracy can get satisfactory results, under certain conditions, to ease the contradiction between the associated time-consuming and associated accuracy. Finally, this paper analyzes the structure of the distributed multi-sensor information fusion system, by direct methods and multi-sensor information fusion and FNDA, the use of multi-sensor information fusion algorithm is applied to multi-sensor multi-target tracking simulation system to further improve the target tracking accuracy.

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