A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching  

作　　者：Quanbo Ge Yang Cheng Hong Li Ziyi Ye Yi Zhu Gang Yao 

机构地区：[1]School of Automation,Nanjing University of Information Science&Technology,Jiangsu Provincial University Key Laboratory of Big Data Analysis and Intelligent Systems,Nanjing University of Information Science&Technology,and the Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET),Nanjing University of Information Science&Technology,Nanjing 210044,China [2]School of Department of Logistics Engineering,Shanghai Maritime University,Shanghai 201306,China [3]China Classification Society Nantong Office,Nantong 226006,China [4]Chinese Flight Test Establishment,Xi’an 710089,China [5]School of Mathematics,Tsinghua University,Beijing 100084,China [6]School of Automation,Nanjing University of Information Science&Technology,Nanjing 210044,China [7]Department of Logistics Engineering,Shanghai Maritime University,Shanghai 201306,China [8]IEEE

出　　处：《IEEE/CAA Journal of Automatica Sinica》2024年第6期1424-1437,共14页自动化学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(62033010);Qing Lan Project of Jiangsu Province(R2023Q07)。

摘　　要：For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity matching.In the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and symmetry.Some com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

关 键 词：Curve similarity matching Gaussian-like noise non-parametric scheme parzen window. 

分 类 号：V279[航空宇航科学与技术—飞行器设计]