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Link to original content: https://api.crossref.org/works/10.1108/IJICC-06-2021-0105
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There are many nonlinear filtering algorithms developed so far in the literature.<\/jats:p><\/jats:sec>Design\/methodology\/approach<\/jats:title>In this research work, the recently developed nonlinear filtering algorithm, i.e. shifted Rayleigh filter (SRF), is applied to BOT.<\/jats:p><\/jats:sec>Findings<\/jats:title>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).<\/jats:p><\/jats:sec>Originality\/value<\/jats:title>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.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ijicc-06-2021-0105","type":"journal-article","created":{"date-parts":[[2021,9,10]],"date-time":"2021-09-10T08:06:52Z","timestamp":1631261212000},"page":"110-123","source":"Crossref","is-referenced-by-count":0,"title":["Prevalence of shifted Rayleigh filter for passive surveillance in underwater"],"prefix":"10.1108","volume":"15","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-7195-8097","authenticated-orcid":false,"given":"Guduru","family":"Naga Divya","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2129-2084","authenticated-orcid":false,"given":"Sanagapallea","family":"Koteswara 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