Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium 2012
DOI: 10.1109/plans.2012.6236851
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Improvement of TERCOM aided inertial navigation system by velocity correction

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Cited by 16 publications
(10 citation statements)
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“…The design of the gravity anomaly matching algorithm relates to techniques such as mathematical descriptions and extraction of marine gravity characteristics, error analysis of gravity sensor measurement, best matching principles, and criteria of effective location determination for preventing false locations. Applicable methods include correlation analysis, multi-model self-adaptive Kalman filter estimation, neural networks, and statistical pattern recognition [ 20 , 21 , 22 , 23 , 24 , 25 ]. The basic principles of these methods are all based on the following gravity anomaly matching method: where is the gravity anomaly measured at the actual location of the carrier, and is the gravity anomaly read from a reference map according to the location indicated by the INS.…”
Section: Principles Of Gravity-aided Navigation and Characteristicmentioning
confidence: 99%
“…The design of the gravity anomaly matching algorithm relates to techniques such as mathematical descriptions and extraction of marine gravity characteristics, error analysis of gravity sensor measurement, best matching principles, and criteria of effective location determination for preventing false locations. Applicable methods include correlation analysis, multi-model self-adaptive Kalman filter estimation, neural networks, and statistical pattern recognition [ 20 , 21 , 22 , 23 , 24 , 25 ]. The basic principles of these methods are all based on the following gravity anomaly matching method: where is the gravity anomaly measured at the actual location of the carrier, and is the gravity anomaly read from a reference map according to the location indicated by the INS.…”
Section: Principles Of Gravity-aided Navigation and Characteristicmentioning
confidence: 99%
“…Gravity matching-aided navigation primarily uses a variety of methods to compare the gravity values obtained using marine gravimeters and those stored in reference maps, thereby determining the optimal matching point according to the degree of fit between the two types of gravity values. Algorithms of gravity matching-aided navigation can largely be divided into two types, i.e., related matching algorithms represented by terrain contour matching (TERCOM) [ 18 , 19 ] and interactive closest contour point (ICCP) [ 20 ], and multi-model Kalman filtering algorithms represented by the Sandia inertial terrain-aided navigation (SITAN) [ 21 , 22 ]. There are other algorithms, such as neural networks and particle filtering [ 23 , 24 , 25 ].…”
Section: Principles Of Igns and Variation Characteristics Of Gravimentioning
confidence: 99%
“…The techniques for performing TAN are classified into batch processing and sequential processing [2]. A TAN system based on batch processing creates a profile using data acquired over a period, and it estimates the location using a correction based on the digital elevation model (DEM).…”
Section: Introductionmentioning
confidence: 99%