Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

Baoliang Sun

doi:10.3390/s16111823

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Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

2016-11-01

Baoliang Sun *

Chunlan Jiang

Ming Li

DOI：10.3390/s16111823

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Abstract

En 中文

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi -node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi -node target tracking of WSNs.

Keywords:

wireless sensor network

multi-sensing data fusion

interacting multiple model

fuzzy neural network

target tracking

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