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.

Error compensation of an optical gyro INS by multi-axis rotation

Abstract: IMU rotation of an inertial navigation system (INS) can bound the free propagation of the INS error introduced by the drifts of inertial sensors. The rotation scheme of the IMU will directly affect the accuracy, structure and costs of the system. A reasonable rotation scheme should remove most of the system errors arising from the drifts of the inertial sensors, and at the same time, should not introduce other additional errors. First, this paper discusses the design and analysis approach of the rotation scheme based on the error propagation equations of the INS. Then, a conventional 8-position rotation scheme is analyzed for the applications of the optical gyro INS, and its drawbacks are discussed in detail. Following these, an improved 8-position rotation scheme and a novel 16-position rotation scheme are proposed for the optical gyro INS, and their merits are also discussed. Simulation results have shown that the 16-position rotation scheme, which can compensate not only the drifts but also the scale factor errors and the misalignment errors of the inertial sensors, is the best rotation scheme and can be used as a practical solution to compensate the drifts of the inertial sensors in the rotational INS.

A Wireless Micro Inertial Measurement Unit (IMU)

Abstract: In this paper, we present a wireless micro inertial measurement unit (IMU) with the smallest volume and weight requirements available at the moment. With a size of 22 mm × 14 mm × 4 mm (1.2 cm3), this IMU provides full control over the data of a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer. It meets the design prerequisites of a space-saving design and eliminates the need for hard-wired data communication, while still being competitive with state-of-the-art commercially available MEMS IMUs. A CC430 microcontroller sends the collected raw data to a base station wirelessly with a maximum sensor sample rate of 640 samples/s. Thereby, the IMU performance is optimized by moving data post processing to the base station. This development offers important features in portable applications with their significant size and weight requirements. Due to its small size, the IMU can be integrated into clothes or shoes for accurate position estimation in mobile applications and location-based services. We demonstrate the performance of the wireless micro IMU in a localization experiment where it is placed on a shoe for pedestrian tracking. With sensor data-fusion based on a Kalman filter combined with the zero velocity update, we can precisely track a person in an indoor area.

High-Accuracy Positioning in Urban Environments Using Single-Frequency Multi-GNSS RTK/MEMS-IMU Integration

Abstract: The integration of Global Positioning System (GPS) real-time kinematics (RTK) and an inertial navigation system (INS) has been widely used in many applications, such as mobile mapping and autonomous vehicle control. Such applications require high-accuracy position information. However, continuous and reliable high-accuracy positioning is still challenging for GPS/INS integration in urban environments because of the limited satellite visibility, increasing multipath, and frequent signal blockages. Recently, with the rapid deployment of multi-constellation Global Navigation Satellite System (multi-GNSS) and the great advances in low-cost micro-electro-mechanical-system (MEMS) inertial measurement units (IMUs), it is expected that the positioning performance could be improved significantly. In this contribution, the tightly-coupled single-frequency multi-GNSS RTK/MEMS-IMU integration is developed to provide precise and continuous positioning solutions in urban environments. The innovation-based outlier-resistant ambiguity resolution (AR) and Kalman filtering strategy are proposed specifically for the integrated system to resist the measurement outliers or poor-quality observations. A field vehicular experiment was conducted in Wuhan City to evaluate the performance of the proposed algorithm. Results indicate that it is feasible for the proposed algorithm to obtain high-accuracy positioning solutions in the presence of measurement outliers. Moreover, the tightly-coupled single-frequency multi-GNSS RTK/MEMS-IMU integration even outperforms the dual-frequency multi-GNSS RTK in terms of AR and positioning performance for short baselines in urban environments.

Inertial navigation system for mobile objects with constraints

Abstract: An aided inertial navigation system and method for navigating a mobile object having constraints comprising an inertial measurement unit, a processor, and an error correction device. The inertial measurement unit provides acceleration data and/or angular velocity data of the mobile object. The processor is adapted to receive the acceleration data and/or angular velocity data, and to provide output data with position output indicative of position of the mobile object. The error correction device receives as input, state and dynamics information and auxiliary input data including map information associated with the path, speed data, wheel-angle data and discrete data. The error correction device provides as output, state corrections to the processor that enhance accuracy of the position output. The state corrections are used by the processor to estimate position of the mobile object based on the constraints to the mobile object and the map information associated with the path.

Flight-Test Evaluation of Sensor Fusion Algorithms for Attitude Estimation

Abstract: In this paper, several Global Positioning System/inertial navigation system (GPS/INS) algorithms are presented using both extended Kalman filter (EKF) and unscented Kalman filter (UKF), and evaluated with respect to performance and complexity. The contributions of this study are that attitude estimates are compared with independent measurements provided by a mechanical vertical gyroscope using 23 diverse sets of flight data, and that a fundamental difference between EKF and UKF with respect to linearization is evaluated.