{"title":"A new TMA method for state estimation of underwater target","authors":"Wei Sun, Pulong Nan","doi":"10.1109/ISAPE.2018.8634384","DOIUrl":null,"url":null,"abstract":"In this paper, a novel target motion analysis (TMA) method using unscented Kalman Filter (UKF) based on modified polar coordinates (MPC) is proposed to improve the localization accuracy for underwater target with constant velocity. The proposed approach utilizes bearings of two-arrays to estimate the localization and velocity of the target. Unlike extended Kalman filter, unscented Kalman Filter (UKF), which is biased and sensitive to the initial value in Cartesian coordinate, the proposed scheme is much more stable and asymptotically unbiased. Moreover, the performances among these schemes are compared based on the noisy bearings from towed array sonar and flank array sonar via Monte Carlo simulations. Simulation results show that the proposed MPC-UKF has better performances with higher numerical stability and little cost of computational complexity.","PeriodicalId":297368,"journal":{"name":"2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAPE.2018.8634384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, a novel target motion analysis (TMA) method using unscented Kalman Filter (UKF) based on modified polar coordinates (MPC) is proposed to improve the localization accuracy for underwater target with constant velocity. The proposed approach utilizes bearings of two-arrays to estimate the localization and velocity of the target. Unlike extended Kalman filter, unscented Kalman Filter (UKF), which is biased and sensitive to the initial value in Cartesian coordinate, the proposed scheme is much more stable and asymptotically unbiased. Moreover, the performances among these schemes are compared based on the noisy bearings from towed array sonar and flank array sonar via Monte Carlo simulations. Simulation results show that the proposed MPC-UKF has better performances with higher numerical stability and little cost of computational complexity.