Could cold atom interferometry sensors be the future inertial sensors? — First simulation results

Bochkati, Mohamed; Schön, Steffen; Schlippert, Dennis; Schubert, C.; Rasel, Ernst M.

doi:10.1109/inertialsensors.2017.8171500

Cited by 6 publications

(2 citation statements)

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“…They differ significantly from one technology, one manufacturer, and even one sensor, to another. The cold atom is the most accurate IMU [ 1 ], but it is very expensive and not applicable for commercial applications, such as mobile mapping. Other IMU technologies, such as mechanical IMU and Micro-Electro-Mechanical System (MEMS), suffer from common error sources, such as bias and scale factor errors and some technology-specific error sources, such as dead zone errors in Ring Laser Gyros (RLGs).…”

Section: Problem Statementmentioning

confidence: 99%

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study

Hosseinyalamdary

2018

Sensors

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Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy.

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Section: Problem Statementmentioning

confidence: 99%

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study

Hosseinyalamdary

2018

Sensors

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“…This insufficient data-rate will lead to algorithmic solution error. At the same time, the limited dynamic range of the CAIG cannot meet the requirement of accurately capturing the dynamic information of the carrier [31,32]. On the other hand, FOG is an advanced inertial sensor for rotation measurement of carriers.…”

Section: Introductionmentioning

confidence: 99%

A Novel Monitoring Navigation Method for Cold Atom Interference Gyroscope

Zhang

Gao

et al. 2019

Sensors

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The implementation principle of a typical three-pulse cold atom interference gyroscope is introduced in this paper. Based on its configuration and current research status, the problems of cold atom interference gyro are pointed out. The data-rate is insufficient, and it is difficult to achieve high dynamic measurement. Then, based on these two limitations, a novel design of the monitoring navigation system of the cold atom interference gyroscope (CAIG) and an intermediate-grade inertial measurement unit (IMU) was proposed to obtain the long-term position result without GPS signals, such as the Inertial Navigation System (INS) in underwater vehicles. While the CAIG was used as the external gyro, the bias of IMU and the misalignment angle between the CAIG-frame and the IMU-frame are obtained through filtering technique. The simulation test and field test demonstrated the improvements of the long-term positioning accuracy of the INS.

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