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24 September 2009 Using a multiple analytical distribution filter for underwater localization
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Abstract
This paper presents a high efficiency algorithm, Multiple Analytical Distribution Filter (MADF), to estimate location for underwater navigation. Using small grid sampling around candidate areas of high probability, MADF computes probabilities directly from the known analytical distributions of each beacon. The algorithm is deterministic and achieves similar results to particle filters, but at a lower computational cost in our tests. MADF and particle filters represent improvements over Kalman Filters for environments characterized by non-Gaussian noise distribution.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dov Kruger, Hongyuan Shi, Yingying Chen, Hongbo Liu, Jie Yang, and Len Imas "Using a multiple analytical distribution filter for underwater localization", Proc. SPIE 7480, Unmanned/Unattended Sensors and Sensor Networks VI, 74800T (24 September 2009); https://doi.org/10.1117/12.834893
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