A New UWB Target Detection and Identification Method Based on Extreme Learning Machine
UWB is a short-range wireless communication technology with strong resolution, detection and anti-jamming capability. UWB radar has been widely used in the transportation detection, bridge detection , medical detection , etc. However traditional UWB radar is used for target detection and identification by analyzing the echo signals. It cannot content the requirement of accomplishing communication and target detection at the same time which is significant in individual combat and intrusion detection. In this paper, we propose a novel target detection and recognition method which is different from the traditional UWB radar to content the above requirement. This method extracts the characteristic parameters of the received signals instead of the echo signals, and employ the extreme learning machine (ELM) to identify target. According to Matlab simulation result, the new method is quite fast and effective in target identification.
KeywordsUWB ELM Channel characteristic parameters Target identification
This work was supported by NSFC (61171176).
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