“…A Kalman filter with magnetic field observations is presented to correct the cumulative error of the inertial navigation [21]. The difference between the geomagnetic model value and the measured magnetic field value is taken as an observation of the Kalman filter.…”
In recent years, using smartphones for indoor positioning has become increasingly popular with consumers. This paper presents an integrated localization technique for inertial and magnetic field sensors to challenge indoor positioning without Wi-Fi signals. For dead-reckoning (DR), attitude angle estimation, step length calculation, and step counting estimation are introduced. Dynamic time warping (DTW) usually calculates the distance between the measured magnetic field and magnetic fingerprint in the database. For DR/Magnetic matching (MM), we creatively propose 3-dimensional dynamic time warping (3DDTW) to calculate the distance. Unlike traditional DTW, 3DDTW extends the original one-dimensional signal to a two-dimensional signal. Finally, the weighted least squares further improves indoor positioning accuracy. In the three different experimental scenarios—teaching building, study room, office building—DR/MM hybrid positioning accuracy is about 3.34 m.
“…A Kalman filter with magnetic field observations is presented to correct the cumulative error of the inertial navigation [21]. The difference between the geomagnetic model value and the measured magnetic field value is taken as an observation of the Kalman filter.…”
In recent years, using smartphones for indoor positioning has become increasingly popular with consumers. This paper presents an integrated localization technique for inertial and magnetic field sensors to challenge indoor positioning without Wi-Fi signals. For dead-reckoning (DR), attitude angle estimation, step length calculation, and step counting estimation are introduced. Dynamic time warping (DTW) usually calculates the distance between the measured magnetic field and magnetic fingerprint in the database. For DR/Magnetic matching (MM), we creatively propose 3-dimensional dynamic time warping (3DDTW) to calculate the distance. Unlike traditional DTW, 3DDTW extends the original one-dimensional signal to a two-dimensional signal. Finally, the weighted least squares further improves indoor positioning accuracy. In the three different experimental scenarios—teaching building, study room, office building—DR/MM hybrid positioning accuracy is about 3.34 m.
“…Algorithm 3 (as main part of algorithm of calculations of Rodrigues-Hamilton parameters) is realized [8, p. 316] in the laser aviation strapdown inertial navigation system SINS-85, serially [9] produced since 2002 and intended for the use on the airplanes Il-96-300, Tu-204, Тu-334. Modifications of the system SINS-85 (SINS-77, SINS-Т, SINS SP-1, SINS SP-2) are used on the airplanes .…”
Section: A Application Of Nonclassical Quaternions For Determination ...mentioning
The article considers the nonclassical quaternions and pentanions of helf-rotations of solid body and their application in problems of control and orientation of moving objects. In contrast to classical rationed Hamiltonian quaternions of complete rotations the nonclassical quaternions of helf-rotations may be null, they have variable rates, depending on the angle of Euler finite rotation.
“…The measurement error of Inertial Navigation System (INS) accumulates with time, so INS needs to be corrected periodically by other auxiliary methods. An effective method is to integrate geomagnetic navigation and inertial navigation [1,2]. Many scientists around the world are studying geomagnetic navigation.…”
The geomagnetic matching aided positioning system based on Iterative Closest Contour Point (ICCP) algorithm can suppress the accumulation error of the inertial navigation system and achieve the accurate positioning of the vehicle. Aiming at the problem that the ICCP algorithm is sensitive to heading error and easily mismatches in regions with similar geomagnetic general features, an improved ICCP matching algorithm based on geomagnetic vector is proposed. The ant colony algorithm is designed to improve the search strategy in a large probability range. The geomagnetic three-dimensional vector feature and the Hausdoff distance are employed as the objective function for multiple iterations, improving matching efficiency and accuracy. Simulation results show that compared with the traditional ICCP algorithm, the positioning error of the matching track, the heading error, and the matching time of the improved ICCP algorithm are reduced by 69.6%, 44.0% and 39.0%, respectively.
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