文献类型：期刊文献

英文题名：Target Classification Aided Variable-Structure Multiple-Model Algorithm

作者：Wang, Quanhui[1];Li, Pengfei[2];Fan, En[3]

机构：[1]Lingnan Normal Univ, Sch Informat Engn, Zhanjiang 524048, Peoples R China;[2]Army Acad Artillery & Air Def Forces, Zhengzhou Campus, Zhengzhou 450052, Henan, Peoples R China;[3]Shaoxing Univ, Dept Comp Sci & Engn, Shaoxing 312000, Peoples R China

年份：2020

卷号：8

起止页码：147692

外文期刊名：IEEE ACCESS

收录：SCI-EXPANDED(收录号：WOS:000562118700001)、、EI(收录号：20203709158841)、Scopus(收录号：2-s2.0-85090327598)、WOS

基金：This work was supported in part by the Zhanjiang Science and Technology under Project 2019B01150, in part by the National Natural Science Foundation of China under Grant 61703280, and in part by the Shenzhen Science and Technology Development Fund under Grant JCYJ20170818160138138.

语种：英文

外文关键词：Classification algorithms; Adaptation models; Target tracking; Atmospheric modeling; Aircraft; Computational modeling; Maneuvering target tracking; variable-structure multiple-model; target classification aided; ADS-B

外文摘要：Because the varieties of general aviation aircraft and their performance differences become increasingly large, the traditional multiple model tracking algorithm needs to employ more motion models to describe the actual maneuver model of a moving target. This fact is easy to degrade the tracking accuracy and brings a large computational load. Thus, a target classification aided variable-structure multiple-model algorithm (TCA-VSMM) is proposed to solve the above problem. In the proposed TCA-VSMM algorithm, the target classification aided is introduced to improve the accuracy of state estimation. Then, the target classification aided in the screening of the motion model set is analyzed. Concretely, the target classification information and velocity information in automatic dependent surveillance-broadcast (ADS-B) measurements are incorporated into the variable-structure multiple-model filter. Consequently, the screening model set is more approximated to the real motion model of a moving target. Experiments show that the TCA-VSMM algorithm can obtain better performance with small computation load and high estimation accuracy than those of the model-group switching variable-structure multiple-model algorithm.