A method of obstacle identification in ultra wideband wireless sensor networks
by Minglei You; Ting Jiang
International Journal of Sensor Networks (IJSNET), Vol. 17, No. 1, 2015

Abstract: Obstacle identification is a difficult task, which is more challenged in foliage environment. In this paper, a method of target detection is proposed, which attempts to extract information from the data being transmitted around the wireless sensor network (WSN) to identify targets that might be within the local, foliage obscured scene. The selected bispectra algorithm is applied to extract the feature vector, as well as radial-basis function (RBF) neural network is used to realise the obstacle classification. According to the experiment results, this method is able to identify the existence and the different distances of the obstacles measured in outdoor foliage scene with a good recognition rate.

Online publication date: Thu, 19-Feb-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Sensor Networks (IJSNET):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com