A method of target identification with UWB based on genetic algorithm and fuzzy pattern recognition
Ultra wideband (UWB) signal has a broad spectrum and high resolution; therefore it is potential in communication and identification areas. At present, for the communication perspective, UWB wireless sensor network (WSN) plays an important role. And for the identification perspective, UWB radar, radar, passive radar and WSN with special sensors make a great achievement. In the paper, a novel method of target identification with UWB based on genetic algorithm (GA) and fuzzy pattern recognition (FPR) is proposed. This method integrates communication and targets identification. Firstly, extensive UWB measurement data are got from the foliage environment with different kinds of targets. Secondly, character parameters related to targets information are extracted from the received signals and the target prediction function is built based on these parameters. Finally, based on FPR, the maximal membership principle is used to identify the targets and GA is used to get near-optimal solution of the sub-membership functions. The recognition results demonstrate that the method is effective to identify targets.