GPS/INS

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

Self-contained positioning method and system thereof for water and land vehicles

Abstract: A positioning method and system for water and land vehicles is disclosed for highly accurate and self-contained operation. In which, an inertial navigation system (INS) is built on the micro MEMS (MicroElectroMechanicalSystem) IMU that is the core of the position determination system. To compensate the error of the INS, multiple navigation sensors are integrated into the system. The magnetic sensor is used as a magnetic field sensor to measure the heading of the vehicle. The odometer is used to measure the distance when the vehicle is on land. An automated Zero velocity updating method is used to calibrate the ever increasing INS errors. When the vehicle is in the water, a velocimeter is used to measure water speed for the INS aiding.

A Tightly-Coupled GPS/INS/UWB Cooperative Positioning Sensors System Supported by V2I Communication

Abstract: This paper investigates a tightly-coupled Global Position System (GPS)/Ultra-Wideband (UWB)/Inertial Navigation System (INS) cooperative positioning scheme using a Robust Kalman Filter (RKF) supported by V2I communication. The scheme proposes a method that uses range measurements of UWB units transmitted among the terminals as augmentation inputs of the observations. The UWB range inputs are used to reform the GPS observation equations that consist of pseudo-range and Doppler measurements and the updated observation equation is processed in a tightly-coupled GPS/UWB/INS integrated positioning equation using an adaptive Robust Kalman Filter. The result of the trial conducted on the roof of the Nottingham Geospatial Institute (NGI) at the University of Nottingham shows that the integrated solution provides better accuracy and improves the availability of the system in GPS denied environments. RKF can eliminate the effects of gross errors. Additionally, the internal and external reliabilities of the system are enhanced when the UWB observables received from the moving terminals are involved in the positioning algorithm.

Direct exterior orientation of airborne imagery with gps/ins system: performance analysis.

Abstract: Integrating the Global Positioning System (GPS) with an Inertial Navigation System (INS) allows for direct image georeferencing, offering a possibility of relaxing the demand for aerial triangulation (AT) in airborne surveying/mapping. The performance of the prototype of the Airborne Integrated Mapping System (AIMS™), based on GPS/INS/CCD (charge-coupled device) integration, developed by The Ohio State University Center for Mapping, is investigated in this paper. A brief description of the essential features of the integrated system and its practical implementation is presented. The performance of AIMS™ is primarily assessed based on the photogrammetric processing of 1:6,000 large-scale aerial imagery considered as a truth reference. An accuracy analysis and discussion of the impact of direct orientation and the multi-sensor system calibration on the photogrammetric data extraction process are also addressed.

Low-Cost INS/GPS Integration: Concepts and Testing

Abstract: The high cost of inertial units is the main obstacle for their inclusion in precision navigation systems to support a variety of application areas. Standard inertial navigation systems (INS) use precise gyro and accelerometer sensors; however, newer inertial devices with compact, lower precision sensors have become available in recent years. This group of instruments, called motion sensors, is six to eight times less costly than a standard INS. Given their weak stand-alone accuracy and poor run-to-run stability, such devices are not usable as sole navigation systems. Even the integration of a motion sensor into a navigation system as a supporting device requires the development of non-traditional approaches and algorithms. The objective of this paper is to assess the feasibility of using a motion sensor, specifically the MotionPak, integrated with DGPS and DGLONASS information, to provide accurate position and attitude information, and to assess its capability to bridge satellite outages for up to 20 seconds. The motion sensor has three orthogonally mounted solid-state' micromachined quartz angular rate sensors, and three high performance linear servo accelerometers mounted in a compact, rugged package. Advanced algorithms are used to integrate the GPS and motion sensor data. These include INS error damping, calculated platform corrections using DGPS (or DGPS/DGLONASS) output, velocity correction, attitude correction and error model estimation for prediction. This multi-loop algorithm structure is very robust, which guarantees a high level of software reliability. Vehicular and aircraft test trials were conducted with the system and the results are discussed. Simulated outages in GPS availability were made to assess the bridging accuracy of the system. Results show that a bridging accuracy of up to 3 m after 10 seconds in vehicular mode and a corresponding accuracy of 6 m after 20 seconds in aircraft mode can be obtained, depending on vehicle dynamics and the specific MotionPak unit used. The attitude accuracy was on the order of 22 to 25 arcmin for roll and pitch, and about 44 arcmin for heading.

Integrated GPS/INS navigation system with dual-rate Kalman Filter

Abstract: A dual-rate Kalman Filter (DRKF) has been developed to integrate the time-differenced GPS carrier phases and the GPS pseudoranges with INS measurements. The time-differenced GPS carrier phases, which have low noise and millimeter measurement precision, are integrated with INS measurements using a Kalman Filter with high update rates to improve the performance of the integrated system. Since the time-differenced GPS carrier phases are only relative measurements, when integrated with INS, the position error of the integrated system will accumulate over time. Therefore, the GPS pseudoranges are also incorporated into the integrated system using a Kalman Filter with a low update rate to control the accumulation of system errors. Experimental tests have shown that this design, compared to a conventional design using a single Kalman Filter, reduces the coasting error by two-thirds for a medium coasting time of 30 s, and the position, velocity, and attitude errors by at least one-half for a 45-min field navigation experiment.