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Inertial navigation system

About: Inertial navigation system is a research topic. Over the lifetime, 14582 publications have been published within this topic receiving 190618 citations. The topic is also known as: intertial guidance system & inertial reference platform.


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Patent
03 Jul 2003
TL;DR: In this article, a spatial image information method and system for rapid and efficient storage in a relation type database and retrieval and management of spatial images acquired by a combined system of a global positioning system (GPS), an inertial navigation system (INS), and an image acquisition device (i.e., CCD camera).
Abstract: Disclosed is a spatial image information method and system for rapid and efficient storage in a relation type database and retrieval and management of spatial images acquired by a combined system of a global positioning system (GPS), an inertial navigation system (INS), and an image acquisition device (i.e., CCD camera). The spatial image acquired by the GPS/INS/CCD camera combined system is combined with an exterior orientation composed of a camera position (x,y,z), accelerated velocity, slope and direction at the moment the image is acquired and an interior orientation acquired by a camera calibration, so that calculation of a specified spatial coordinate information becomes possible. The spatial image information system includes a section for efficiently storing a chain of still spatial image sequences acquired by the GPS/INS/CCD camera combined system, the exterior orientation, and the interior orientation in the relation type database, a section for storing spatial information recognized as the same object by a user as maintaining the relationship with the stored still spatial image sequences, a section for efficiently retrieving images that satisfy a certain spatial information operation from the still spatial image sequences, and an interface section for external systems.

69 citations

Proceedings ArticleDOI
07 May 2001
TL;DR: This paper investigates the performance of reduced rank spacetime processors in the context of anti-jam mitigation for an M-code based GPS receiver utilizing a circular array using the innovative multistage Wiener filter.
Abstract: This paper investigates the performance of reduced rank spacetime processors in the context of anti-jam mitigation for an M-code based GPS receiver utilizing a circular array. Several adaptive processing algorithms are discussed utilizing power minimization techniques. It is assumed an INS (inertial navigation system) or direction finding algorithm is incorporated into the receiver for satellite look direction based algorithms. Reduced rank space-time processing is accomplished via the innovative multistage Wiener filter (MSWF). It is demonstrated that the MSWF does not require matrix inversion, thereby reducing computational complexity. The processing algorithms are compared in terms of available degrees of freedom and distortion of the GPS cross correlation function (CCF).

69 citations

Journal ArticleDOI
TL;DR: An eight-position self-calibration method for a dual-axis rotational Inertial Navigation System (INS) is provided in this article, where not only constant biases, scale factor errors, and misalignment errors, but also g-dependent biases can be calibrated.
Abstract: An eight-position self-calibration method for a dual-axis rotational Inertial Navigation System (INS) is provided in this paper. By experiencing two more positions with tilt attitudes than those experienced in a conventional six-position method, not only constant biases, scale factor errors, and misalignment errors, but also g-dependent biases can be calibrated. Field tests indicate that, after the calibration and compensation of the g-dependent biases, both a latitude error and a longitude error remain within a small range over time. In contrast, by using the conventional six-position method, a latitude error is several times larger and a longitude error diverges rapidly over time. Compared with the six-position method, accuracy of the dual-axis rotational INS is significantly improved more than 50% by the eight-position self-calibration method. The self-calibration method is feasible both in static and over a ship at the dockside.

69 citations

Proceedings ArticleDOI
13 Jul 2018
TL;DR: This work presents a method to improve the accuracy of a zero-velocity-aided inertial navigation system (INS) by replacing the standard zero- Velocity detector with a long short-term memory (LSTM) neural network, and demonstrates how this LSTM-based zero-VELocity detector operates effectively during crawling and ladder climbing.
Abstract: We present a method to improve the accuracy of a zero-velocity-aided inertial navigation system (INS) by replacing the standard zero-velocity detector with a long short-term memory (LSTM) neural network. While existing threshold-based zero-velocity detectors are not robust to varying motion types, our learned model accurately detects stationary periods of the inertial measurement unit (IMU) despite changes in the motion of the user. Upon detection, zero-velocity pseudo-measurements are fused with a dead reckoning motion model in an extended Kalman filter (EKF). We demonstrate that our LSTM-based zero-velocity detector, used within a zero-velocity-aided INS, improves zero-velocity detection during human localization tasks. Consequently, localization accuracy is also improved. Our system is evaluated on more than 7.5 km of indoor pedestrian locomotion data, acquired from five different subjects. We show that 3D positioning error is reduced by over 34% compared to existing fixed-threshold zero-velocity detectors for walking, running, and stair climbing motions. Additionally, we demonstrate how our learned zero-velocity detector operates effectively during crawling and ladder climbing. Our system is calibration-free (no careful threshold-tuning is required) and operates consistently with differing users, IMU placements, and shoe types, while being compatible with any generic zero-velocity-aided INS.

69 citations

Journal ArticleDOI
TL;DR: The proposed inertial sensor node is compact and easily wearable; hence, it is feasible to be applied to the body motion analysis.
Abstract: A wearable wireless inertial sensor node for body motion analysis is designed and implemented. A triaxial accelerometer, a biaxial gyroscope, and a yaw rate gyroscope are employed to sense the accelerations and angular rates of the object attached. These three ICs, a wireless mote, the power circuit, and a modified printed inverted-F antenna are integrated on a four-layer printed circuit board. To achieve the compact size for comfortable wearing, the printed antenna is deliberately designed as small as possible, while maintaining a reasonable antenna performance. The proposed inertial sensor node is also easily adaptable to applications with different power requirements because of the consideration of the periodic and moving-event wakeup in the software design. The static characteristics and Allan deviations of the implemented node are measured and analyzed. The false alarm rate of a moving detection based on Bayes rule is presented and a threshold is suggested. Finally, the raw data of several body motions are measured and those behaviors are observed apparently. The proposed inertial sensor node is compact and easily wearable; hence, it is feasible to be applied to the body motion analysis.

69 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023309
2022657
2021491
2020889
20191,003
20181,013