GPS/INS

About: GPS/INS is a research topic. Over the lifetime, 3554 publications have been published within this topic receiving 62784 citations.

Integration of a GPS aided Strapdown Inertial Navigation System for Land Vehicles

Abstract: The estimation accuracy of a low-cost inertial navigation system (INS) is limited by the accuracy of the used sensors and the imperfect mathematical modeling of the error sources. By fusing the INS data with GPS data, the errors can be bounded and the accuracy increases considerably. In this project, a low-cost in-house constructed inertial measurement unit (IMU) and an off-the-shelf GPS receiver are used for the data acquisition. The measurements are integrated with a loosely coupled GPS aided INS approach. For the assessment of the results, one data set with real data obtained from a field test is available. The tuning of the covariance matrices is a delicate adjustment and does not always provide convergence. Values for acceptable results could be found and two implementations of inertial navigation systems are compared. The use of nonholonomic constraints showed a dramatic increase in the accuracy. An analysis of the importance and influence of different IMU sensor errors provides a foundation for the modeling and inclusion of further error states in the extended Kalman filter.

Multisensor fusion for autonomous UAV navigation based on the Unscented Kalman Filter with Sequential Measurement Updates

Abstract: This paper describes a new filtering framework of multisensor fusion and its application to the low-cost strapdown inertial navigation system of an Unmanned Aerial Vehicle (UAV). The navigation system fuses various sources of sensor information from low-cost sensor suites such as an Inertial Measurement Unit (IMU), a Global Positioning System (GPS), and a three-axis magnetometer in the new framework of the Unscented Kalman Filter with Sequential Measurement Updates (SMU-UKF). In particular, sensor measurements can be easily fused together regardless of the number of sensors, sensor update rates, and sensor data dimensions. The performance and error analysis of the integrated navigation system based on this new multisensor fusion filter are assessed in a realistic simulation environment by comparing performance with that of an existing Extended Kalman Filter-based navigation system.

Polarized Light Compass-Aided Visual-Inertial Navigation Under Foliage Environment

Abstract: This paper presents a method to extract heading information from the sky light polarization pattern and successfully implements the polarized light compass (PL-compass) under foliage environment with heavy occlusions for the first time. A classifier based on the primal support vector machine is trained to detect the sky area, and the random sample consensus algorithm is used to choose the inliers among the sky area. The sun vector is built upon the valid measurements. The attitude angles (Roll and Pitch) from the inertial navigation system (INS) are used to establish the Zenith direction when the platform tilts during traveling. The results show that the PL-compass can provide accurate heading angle (RMSE = 1.58°) by seeing only a tiny part of the skylight (minimum of 0.028%) in the dynamic vehicle test. The PL-compass is also integrated with the visual INS based on the indirect extended Kalman filter to improve the navigation accuracy. Each time a new measurement becomes available, the states estimated by the INS are used to check the consistency of the innovation and reject the outliers. The results show that the position errors of the integrated navigation system are greatly reduced with the help of the PL-compass. The estimated trajectory tracks the ground truth very well. The position error is 25.9 m (1.03% of the distance traveled) with heading errors less than 1° in the experiment.

Improved integrity algorithms for integrated GPS/INS systems in the presence of slowly growing errors

Abstract: ...........................................................................................................................iii Acknowledgements .........................................................................................................vii Table of

GPS gyro calibration

Abstract: GPS gyro calibration methods and systems are described. In an embodiment, a ground station can receive antenna position data for a spot beam antenna from a global positioning system (GPS) platform where the antenna position data indicates a boresight direction of the spot beam antenna. GPS-enabled receiver(s) can receive scan signals transmitted via the spot beam antenna of the GPS platform, and the GPS-enabled receivers can determine signal power measurements for each of the scan signals. The ground station can receive the signal power measurements from the GPS-enabled receiver(s) and estimate a pointing error of the spot beam antenna based on the signal power measurements and the antenna position data received from the GPS platform. The ground station can then determine gyro calibration parameters from the estimated pointing error and communicate the gyro calibration parameters to the GPS platform to calibrate for gyro drift errors.