Prevalence of shifted Rayleigh filter for passive surveillance in underwater

作     者：Guduru Naga Divya Sanagapallea Koteswara Rao 

作者机构：Department of Electronics and Communication EngineeringKoneru Lakshmaiah Education FoundationGunturIndia 

出 版 物：《International Journal of Intelligent Computing and Cybernetics》 (智能计算与控制论国际期刊（英文）)

年 卷 期：2022年第15卷第1期

页      面：110-123页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 07[理学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Stochastic signal processing Shifted Rayleigh filter State estimation Underwater surveillance 

摘      要：Purpose-From many decades,bearings-only tracking(BOT)is the interested problem for researchers.This utilises nonlinear filtering methods for state estimation as there is only information about the target,i.***.bearing is a nonlinear measurement.The measurement bearing is tangentially related to the target state vector.There are many nonlinear filtering algorithms developed so far in the literature.Design/methodology/approach-In this research work,the recently developed nonlinear filtering algorithm,i.***.shifted Rayleigh filter(SRF),is applied to BOT.Findings-The SRF is tested for two-dimensional BOT against various scenarios.The simulation results emphasise that the SRF performs well when compared to the standard nonlinear filtering algorithm,unscented Kalman filter(UKF).Originality/value-SRF utilises the nonlinearities present in the bearing measurement through the use of moment matching.The SRF is able to produce the solution in highly noisy environment,long ranges and high dimension tracking.