GPS/INS

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

Collaborative GPS/INS Navigation in Urban Environment

Abstract: The Swedish Defence Research Agency is currently conducting research aiming at the creation of a Net work Based Defence (NBD). This research includes areas such as GPS/INS navigation and collaboration of Unmanned Ground Vehicles (UGV:s). A large problem with navigation systems that use GPS is that, due to the possibility of satellite out ages, there are many occasions when the GPS receiver fails to deliver enough information to support an error free navigation. In this paper, techniques will be presented to increase position accuracy and navigation robustness in an urban environment by means of collaborative navigation. When a vehicle is navigating in an urban environment, lines of sight (LOS) to satellites will often be blocked. However, two vehicles at different locations can have different sets of visible satellites, and by collaboration the satellite information can be shared between the vehicles, which results in better navigational performance. The three collaborative techniques investigated in this paper are based on communication between the two vehicles, as well as measurements of their relative range or range vectors. In many ways the techniques are similar to using pseudolites, but with the important difference that here the pseudolites are mobile and also navigating. The case with two collaborating vehicles is considered. Both vehicles are equipped with complementary GPS/INS navigation tools using extended tightly coupled Kalman filters. When the vehicles are not collaborating with each other, their observations consist of acceleration and angular velocity measurements for the INS, together with pseudoranges as measured by the GPS receiver. An alternate method for acquiring accurate and robust navigation of a single vehicle in urban environments is Simultaneous Localization and Mapping (SLAM). In SLAM, a range measuring device (e.g. a laser range finder) is used to extract features from the environment. Accurate navigation will be accomplished as long as the features are correctly associated. A comparison between this technique and the collaborative GPS/INS methods mentioned above is also done in this paper. Simulations for a carefully chosen urban scenario are performed. The results indicate increased accuracy when using the investigated algorithms. Collaborative navigation opens up for cheap navigational platforms where several relatively simple vehicles can achieve the same performance as expensive and complex platforms.

Modification of the nonlinear kalman filter in a correction scheme of aircraft navigation systems

Abstract: An algorithm for correction of the navigation data of an aircraft that uses an inertial navigation system and the global positioning system (GPS) is considered. Estimation algorithms, namely, linear and nonlinear Kalman filters, are investigated. A method for modification of the nonlinear Kalman filter with the use of a genetic algorithm has been developed. To estimate the operability and accuracy of the modified nonlinear Kalman filter, simulation based on the data of a laboratory experiment conducted with the use of real navigation systems KIND34-059 and AIST-350 has been performed. The results of the laboratory experiments conducted with the use of real navigation systems have demonstrated high accuracy of data processing by the nonlinear Kalman filter modified by the genetic algorithm.

Low-cost IMU/odometer/GPS integrated navigation aided with two antennae heading measurement for land vehicle application

Abstract: For the guidance, control and navigation of autonomous vehicles, both positioning and orientation are important for mission success and surveillance. Global positioning system (GPS) and strapdown inertial navigation system (SINS) have complementary characteristics to overcome the demerits of each other and can well perform as integrated navigation system. The observability analysis of low-cost SINS/GPS from many researches shown that the heading and yaw rate gyro bias is unobservable in straight motion and with constant acceleration. This paper presents integration of low-cost SINS/GPS aided with odometer and heading from two antennae GPS receiver to overcome this problem and to control the accuracy degradation during GPS outage. The carrier phase measurements are processed to obtain the heading from two antennae position measurement. The obtained heading and position from GPS and velocity measurement from odometer are used as observation input to extended Kalman filter (EKF) for the heading and positioning accuracy improvement of SINS/odometer/GPS integrated system for land vehicle navigation. When GPS signal is unavailable, the filter switches to SINS/odometer integration to control the position and velocity errors growth during this period. The observation model for heading measurement from two antennae is derived for the designed system. A field test was conducted to check the effectiveness using proposed method for heading and positioning accuracy improvement. The test results showed that Low-cost IMU/Odometer/ Two Antennae GPS integrated systems' accuracy both in position and heading is improved significantly.

System and method for detecting false navigation signals

Abstract: A system and method for detecting and excluding false GPS signals are disclosed, which predict a GPS measurement value with a high degree of confidence, compare the predicted value with measured values, and reject a false measurement based on the comparison results. As one example, a tightly coupled GPS/Inertial Navigation System (GPS/INS) is disclosed, which uses a Kalman filter for comparison of a predicted GPS measurement value with measured values (e.g., the residuals) to form the basis for the rejection of false measurements. This rejection is referred to as a chi-squared reject, and can be extended in time in order to apply the same test to a reacquired signal following the loss of an original validated GPS signal. The Kalman filter propagates the receiver's clock bias rate, and enables the system to predict the GPS measurements at the time of reacquisition. The residuals are compared to a limit defined by the uncertainties of the prediction and the measurement errors expected to be involved.

Autonomous Ground Vehicle Navigation Using Integrated GPS and Laser-scanner Measurements

Abstract: This paper describes the design, analysis and testing of a navigation system based on combined GPS and laser-scanner measurements. Using carrier phase differential GPS, centimeter- level positioning of autonomous ground vehicles (AGVs) is achievable. However, GPS signals are easily attenuated or blocked, so their use is generally restricted to open-sky areas. In response, in this work we augment GPS with two-dimensional laser-scanner measurements. The latter are available when GPS is not, and provide in addition, a means for obstacle detection. Laser measurements are processed using a Simultaneous Localization And Mapping (SLAM) procedure. Vehicle and landmark position estimation is performed simultaneously using an extended Kalman filter; we address the data association problem, which establishes correspondences between consecutive sets of measurements and a continuously updated map of landmarks. The resulting laser-based SLAM solution is carefully analyzed by identifying and isolating the individual effects of the joint angular and ranging measurements, the combination of measurements from multiple landmarks, the correlation between vehicle and landmark position estimates, and the uncertainty on the vehicle's heading angle. A detailed covariance analysis is then carried out in order to quantify the sensitivity of the vehicle's position estimate error to the vehicle's velocity, the landmark geometry, and the laser's range limit. Further sensitivity analyses are structured around two scenarios: first, a 'forest scenario' where the vehicle roves across a GPS-unavailable area using tree trunks as landmarks in order to maintain a precise position estimate; second, an 'urban canyon' scenario describing how we can make use of GPS signals that alone are too few to generate a position fix, by utilizing additional laser measurements to buildings' edges. Finally, experimental results using a prototype AGV are presented to validate the navigation system performance. I. INTRODUCTION This paper describes the design, analysis and testing of a navigation system based on combined Global Positioning System (GPS) and laser-scanner measurements. In order to fully exploit the complementary properties of the two sensors, their measurements are integrated in the range domain. The performance of the resulting positioning and mapping algorithm exceeds that of position-domain integration, especially in places such as urban canyons, where fewer than four GPS satellite signals are available. The algorithm presented in this work is intended to be used on an outdoor autonomous ground vehicle (AGV). AGVs can