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Inertial measurement unit

About: Inertial measurement unit is a research topic. Over the lifetime, 13326 publications have been published within this topic receiving 189083 citations. The topic is also known as: IMU.


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Patent
14 Sep 2000
TL;DR: In this article, the velocity and acceleration from an inertial navigation processor of the integrated GPS/INS system are used to aid the code and carrier phase tracking of the global positioning system satellite signals.
Abstract: A real-time integrated vehicle positioning method and system with differential GPS can substantially solve the problems encountered in either the global positioning system-only or the inertial navigation system-only, such as loss of global positioning satellite signal, sensitivity to jamming and spoofing, and an inertial solution's drift over time. In the present invention, the velocity and acceleration from an inertial navigation processor of the integrated GPS/INS system are used to aid the code and carrier phase tracking of the global positioning system satellite signals, so as to enhance the performance of the global positioning and inertial integration system, even in heavy jamming and high dynamic environments. To improve the accuracy of the integrated GPS/INS navigation system, phase measurements are used and the idea of the differential GPS is employed. However, integer ambiguities have to be resolved for high accuracy positioning. Therefore, in the present invention a new on-the-fly ambiguity resolution technique is disclosed to resolve double difference integer ambiguities. The real-time fully-coupled GPS/IMU vehicle positioning system includes an IMU (inertial measurement unit), a GPS processor, and a data link which are connected to a central navigation processor to produce a navigation solution that is output to an I/O (input/output) interface.

66 citations

Journal ArticleDOI
02 Aug 2011-Sensors
TL;DR: A real time indoor navigation system that does not require prepared building environments and provides tracking accuracy superior to previously described tracking methods is described.
Abstract: Many solutions have been proposed for indoor pedestrian navigation. Some rely on pre-installed sensor networks, which offer good accuracy but are limited to areas that have been prepared for that purpose, thus requiring an expensive and possibly time-consuming process. Such methods are therefore inappropriate for navigation in emergency situations since the power supply may be disturbed. Other types of solutions track the user without requiring a prepared environment. However, they may have low accuracy. Offline tracking has been proposed to increase accuracy, however this prevents users from knowing their position in real time. This paper describes a real time indoor navigation system that does not require prepared building environments and provides tracking accuracy superior to previously described tracking methods. The system uses a combination of four techniques: foot-mounted IMU (Inertial Motion Unit), ultrasonic ranging, particle filtering and model-based navigation. The very purpose of the project is to combine these four well-known techniques in a novel way to provide better indoor tracking results for pedestrians.

66 citations

Proceedings ArticleDOI
28 Sep 2004
TL;DR: The proposed Kalman filter obtains a non-drifting orientation estimate with improved resolution by incorporating the motion dynamics of the instrument during microsurgery and models the angular velocity drift explicitly as extra dynamic states.
Abstract: This paper presents the theory and modeling of a quaternion-based augmented state Kalman filter for real-time orientation tracking of a handheld microsurgical instrument equipped with a magnetometer-aided all-accelerometer inertial measurement unit (IMU). The onboard sensing system provides two complementary sources of orientation information. The all-accelerometer IMU provides a high resolution but drifting angular velocity estimate, while the magnetic north vector is combined with the estimated gravity vector to yield a non-drifting but noisy orientation estimate. Analysis of the dominant stochastic noise components of the sensors and derivation of the noise covariance are presented. The proposed Kalman filter obtains a non-drifting orientation estimate with improved resolution by incorporating the motion dynamics of the instrument during microsurgery and models the angular velocity drift explicitly as extra dynamic states.

66 citations

16 Sep 2005
TL;DR: Results show that in open sky conditions with MEMS IMU measurements and a pseudorange/Doppler derived DGPS solution, a positional accuracy better than 38 cm can be achieved, whereas the corresponding improvements using the RTS smoother are about 99%.
Abstract: This paper focuses on evaluating the feasibility of using a low cost Micro Electro Mechanical System (MEMS) – based Inertial Measurement Unit (IMU) integrated with Differential Global Positioning System (DGPS), for land vehicle navigation. The main focus is on position accuracy analysis using a closed loop decentralized GPS/INS integration scheme. A Kalman filter is proposed for the IMU which models sensor scale factors and turn on biases. A performance comparative analysis of the MEMS Crista IMU with a tactical grade HG1700 IMU is presented. GPS outages are simulated in a clean data set collected in open sky conditions, by artificially omitting satellites during post-processing in order to asses the stand-alone performance of each IMU. Two different methods are investigated to prevent the errors from accumulating in the Inertial Navigation System (INS) in the absence of GPS. One is to use the constrained motion attributes of a land vehicle to bound the drift in the INS solution. This method is suitable for use in real-time applications. Another method is specifically a post processing scheme which involves the use of a Rauch Tung Streibel (RTS) smoother. Simultaneous field testing using DGPS and MEMS, tactical, and navigation-grade IMUs was conducted to allow for a direct comparison of their relative performance. The results show that in open sky conditions with MEMS IMU measurements and a pseudorange/Doppler derived DGPS solution, a positional accuracy better than 38 cm can be achieved. The use of vehicle movement constraints during GPS outages can prevent errors from accumulating, and can provide the improvement of up-to 80% in the position domain, whereas the corresponding improvements using the RTS smoother are about 99%.

66 citations

Journal ArticleDOI
You Li, Xiaoji Niu, Quan Zhang, Hongping Zhang, Chuang Shi1 
TL;DR: A novel and efficient in situ hand calibration method that makes use of the navigation algorithm of the loosely-coupled GPS/INS integrated systems and replaces the GPS observations with a kind of pseudo-observations, which can be stated as follows.
Abstract: MEMS chips have become ideal candidates for various applications since they are small sized, light weight, have low power consumption and are extremely low cost and reliable. However, the performance of MEMS sensors, especially their biases and scale factors, is highly dependent on environmental conditions such as temperature. Thus a quick and convenient calibration is needed to be conducted by users in field without any external equipment or any expert knowledge of calibration. A novel and efficient in situ hand calibration method is presented to meet these demands in this paper. The algorithm of the proposed calibration method makes use of the navigation algorithm of the loosely-coupled GPS/INS integrated systems, but replaces the GPS observations with a kind of pseudo-observations, which can be stated as follows: if an inertial measurement unit (IMU) was rotating approximately around its measurement center, the range of its position and its linear velocity both would be within a limited scope. Using a Kalman filtering algorithm, the biases and scale factors of both accelerometer triad and gyroscope triad can be calibrated together within a short period (about 30 s), requiring only motions by hands. Real test results show that the proposed method is suitable for most consumer grade MEMS IMUs due to its zero cost, easy operation and sufficient accuracy.

66 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231,067
20222,256
2021852
20201,150
20191,181
20181,162