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There are fuzzy positioning, no solution, and low positioning accuracy with the spherical coordinate conversion method in the four-station TDOA positioning algorithm. Focusing on these problems, we proposed a combination of TDOA and iterative Newton\u2019s method. The positioning method uses the result obtained by the four-station TDOA location algorithm as the initial value of the iterative Newton\u2019s method and solves the problem of no solution and fuzzy positioning caused by the four-station TDOA location algorithm by using the spherical coordinates conversion method. By simulating the target at a height of 5 km and traveling at a constant speed for 40 km, the positioning accuracy of the root mean square error is less than 45 m, which can achieve the same positioning accuracy of TDOA based on the least square algorithm. As the baseline length increases, the positioning accuracy is better than the least square algorithm.<\/jats:p>","DOI":"10.1186\/s13638-020-01684-7","type":"journal-article","created":{"date-parts":[[2020,4,8]],"date-time":"2020-04-08T11:02:42Z","timestamp":1586343762000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["New three-dimensional positioning algorithm through integrating TDOA and Newton\u2019s method"],"prefix":"10.1186","volume":"2020","author":[{"given":"Junsuo","family":"Qu","sequence":"first","affiliation":[]},{"given":"Haonan","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Ning","family":"Qiao","sequence":"additional","affiliation":[]},{"given":"Chen","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Chang","family":"Su","sequence":"additional","affiliation":[]},{"given":"Abolfazl","family":"Razi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,4,8]]},"reference":[{"key":"1684_CR1","first-page":"1","volume":"PP","author":"Y. 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