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GPS/INS

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


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20 Jan 2006
TL;DR: This paper aims to develop a more precise vehicular positioning system during GPS outages by integrating GPS, a tactical grade HG1700 IMU, as well as Wheel Speed Sensor and a Yaw Rate Sensor and three types of sensor integration schemes are proposed.
Abstract: This paper aims to develop a more precise vehicular positioning system during GPS outages by integrating GPS, a tactical grade HG1700 IMU, as well as Wheel Speed Sensor and a Yaw Rate Sensor. Using a tight coupling strategy, three types of sensor integration schemes are proposed, namely GPS/INS/Wheel Speed Sensor, GPS/INS/Yaw Rate Sensor and GPS/INS/Yaw Rate Sensor/Wheel Speed Sensor. The models for each of the schemes are discussed in detail including the sensor error models. The benefits after integrating the Wheel Speed Sensor and the Yaw Rate Sensor are investigated in terms of positioning accuracy during GPS data outages. Furthermore, the reduction in the time to fix the carrier phase ambiguities after various GPS outage durations is analyzed.

39 citations

Journal ArticleDOI
15 Apr 2009-Sensors
TL;DR: This study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode.
Abstract: Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using Global Positioning System (GPS) and Inertial Navigation System (INS) using an Inertial Measurement Unit (IMU). They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. The Kalman Filter (KF) is considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent hybrid scheme consisting of an Artificial Neural Network (ANN) and KF has been proposed to overcome the limitations of KF and to improve the performance of the INS/GPS integrated system in previous studies. However, the accuracy requirements of general mobile mapping applications can’t be achieved easily, even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode. By combining the Micro Electro Mechanical Systems (MEMS) INS/GPS integrated system and the intelligent ANN-RTS smoother scheme proposed in this study, a cheaper but still reasonably accurate position and orientation determination scheme can be anticipated.

39 citations

Proceedings ArticleDOI
05 May 2014
TL;DR: Simulations have shown that the system obtains centimeter-level or better absolute positioning accuracy and sub-degree-level absolute attitude accuracy in open outdoor areas and demonstrates its performance in the challenging scenario of walking through a hallway where GPS signals are unavailable.
Abstract: A novel navigation system for obtaining high-precision globally-referenced position and attitude is presented and analyzed. The system is centered on a bundle-adjustment-based visual simultaneous localization and mapping (SLAM) algorithm which incorporates carrier-phase differential GPS (CDGPS) position measurements into the bundle adjustment in addition to measurements of point features identified in a subset of the camera images, referred to as keyframes. To track the motion of the camera in real-time, a navigation filter is employed which utilizes the point feature measurements from all non-keyframes, the point feature positions estimated by bundle adjustment, and inertial measurements. Simulations have shown that the system obtains centimeter-level or better absolute positioning accuracy and sub-degree-level absolute attitude accuracy in open outdoor areas. Moreover, the position and attitude solution only drifts slightly with the distance traveled when the system transitions to a GPS-denied environment (e.g., when the navigation system is carried indoors). A novel technique for initializing the globally-referenced bundle adjustment algorithm is also presented which solves the problem of relating the coordinate systems for position estimates based on two disparate sensors while accounting for the distance between the sensors. Simulation results are presented for the globally-referenced bundle adjustment algorithm which demonstrate its performance in the challenging scenario of walking through a hallway where GPS signals are unavailable.

39 citations

Proceedings ArticleDOI
11 Apr 1994
TL;DR: Results of simulations for a land vehicle application show that for a variety of scenarios the two design approaches for GPS/INS integration give about the same accuracy, i.e. the tighter integration of the embedded approach does not result in superior performance.
Abstract: The performance of two major design options for GPS/INS integration are studied in this paper. The first is the embedded approach, in which the receiver card is an integral part of the system and GPS-information at the measurement level is directly integrated into the navigation processor. The second is the aided approach, in which GPS information is processed independently and the resulting position and velocity is used to update the INS after appropriate time intervals. To study the two design options, the same mathematical model is used to operate two different filters. For the embedded approach, a centralized Kalman filter is applied. In this case the INS and GPS error models define the common state vector. INS input is used to define the reference trajectory which is then updated by GPS pseudo-ranges and range rates. For the aided approach, a decentralized filter design is chosen. In this case, the state vectors for INS and GPS are defined and operated independently. At specified time intervals the derived GPS position and velocity is used to update the INS position and velocity. The time intervals are determined from the error spectra of both systems. Results of simulations for a land vehicle application show that for a variety of scenarios the two design approaches give about the same accuracy, i.e. the tighter integration of the embedded approach does not result in superior performance. Reasons for this somewhat surprising result are discussed in the paper. >

39 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202317
202247
20219
202013
201925
201840