文献类型：期刊文献

英文题名：An evolutionary algorithm for optimal tracking gate based on hybrid encoding

作者：Zhao, Han[1]; Zhang, Cheng[1]; Lin, Jiajun[1]

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, 286, No. 130 Meilong Road, Xuhui District, Shanghai, 200237, China

年份：2018

卷号：458

起止页码：539

外文期刊名：Lecture Notes in Electrical Engineering

收录：EI(收录号：20174704416006)

语种：英文

外文关键词：Target tracking - Clutter (information theory) - Digital arithmetic - Encoding (symbols) - Signal encoding

摘要：Appropriate tracking gate selection will highly improve tracking quality. A hybrid encoding genetic algorithm is proposed to off-line optimization of maneuvering target tracking gate in clutter. Binary string and floating-point string represent shape and size of gate respectively. Hellinger distance is selected as metric for tracking performance evaluation and can be core part of the fitness function of genetic algorithm. Generally speaking, the tracking system optimization can be converted into genetic algorithm optimization, and the gate parameters can be efficiently tuned in different scenarios. ? 2018, Springer Nature Singapore Pte Ltd.