Topic
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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TL;DR: The results showed that the effectiveness of the proposed system over both the existing Al-based and the conventional INS/GPS integration techniques, especially during long GPS outages, was shown.
Abstract: Recently, methods based on artificial intelligence (AI) have been suggested to provide reliable positioning information for different land vehicle navigation applications. The majority of these applications utilise both the global positioning system (GPS) and the inertial navigation system (INS). These AI modules were trained to mimic the latest vehicle dynamics so that, in case of GPS outages, the system relies on INS and the recently updated AI module to provide the vehicle position. Several neural networks and neuro-fuzzy techniques were implemented in real-time in a de-centralised fashion and provided acceptable accuracy for short GPS outages. It was reported that these methods provided poor positioning accuracy during relatively long GPS outages. In order to prevail over this limitation, this study optimises the Al-based INS/GPS integration schemes utilising adaptive neuro-fuzzy inference system with performing, in real-time, both GPS position and velocity updates. In addition, a holdout cross validation method during the update procedure was utilised in order to ensure generalisation of the model. The proposed system is tested using differential GPS and both navigational and tactical grades INS field test data obtained from a land vehicle experiment. The results showed that the effectiveness of the proposed system over both the existing Al-based and the conventional INS/GPS integration techniques, especially during long GPS outages. This method may have one limitation related to the unusual significant changes of the vehicle dynamics between the update and the prediction stages of operation which may influence the overall positioning accuracy.
25 citations
28 Sep 2004
TL;DR: In this paper, a method for combining dead reckoning sensor information in order to provide an initial estimate of the six degrees of freedom of a rough terrain rover is presented. But the results show that the use of the inertial navigation system (INS) significantly improves the pose prediction.
Abstract: Many algorithms related to localization need good pose prediction in order to produce accurate results. This is especially the case for data association algorithms, where false feature matches can lead to the localization system failure. In rough terrain, the field of view can vary significantly between two feature extraction steps, so a good position prediction is necessary to robustly track features. This paper presents a method for combining dead reckoning sensor information in order to provide an initial estimate of the six degrees of freedom of a rough terrain rover. An inertial navigation system (INS) and the wheel encoders are used as sensory inputs. The sensor fusion scheme is based on an extended information filter (EIF) and is extensible to any kind and number of sensors. In order to test the system, the rover has been driven on different kind of obstacles while computing both pure 3D-odometric and fused INS/3D-odometry trajectories. The results show that the use of the INS significantly improves the pose prediction.
25 citations
TL;DR: The paper demonstrates the possibility of extending the utilization range of the GPS-based navigation system to serve as sensor for formation acquisition and coarse formation keeping and achieves an unprecedented degree of realism using a high-fidelity simulation environment with hardware-in-the-loop capabilities.
25 citations
TL;DR: In this article, a low-cost navigation system that fuses the measurements of the inertial navigation system (INS) and the global positioning system (GPS) receiver is developed.
25 citations
14 Sep 2001
TL;DR: This paper discusses the concept of GPS/INS/Pseudolite integration in detail and both system performance simulation and experimental results are presented to demonstrate the feasibility of such an integrated system.
Abstract: Traditionally, Inertial Navigation Systems (INS) provide
positioning and attitude information for the guidance (and
perhaps control) of a wide range of moving platforms in
the air, at sea, or on the ground. However, the time-
dependent growth of systematic errors is a major concern
in INS applications. Precise satellite measurements are
ideally suited for the calibration of INS systematic errors.
Therefore, integrated INS and GPS (and/or Glonass) sys-
tems have been developed, which can provide high-rate
precise positioning and attitude information.
The major drawback of existing systems is that their per-
formance decreases under difficult operational conditions,
for example when satellite signals are obstructed for ex-
tended periods of time. In the worst situations, such as
underground and inside buildings, the satellite signals
may be completely lost. In circumstances where satellite
signals are unavailable, it may be possible to maintain
availability of range measurements for use in calibrating
the INS systematic errors by placing 'pseudo-satellites'
(pseudolites) at appropriate locations. Thus, an augmen-
tation of existing systems with ranging signals from
ground-based pseudolites would result in a new design
that could address the problems of signal availability. In
fact, integrated GPS/INS/Pseudolite systems are, in prin-
ciple, an ideal option for seamless indoor-outdoor posi-
tioning and attitude determination.
This paper discusses the concept of GPS/INS/Pseudolite
integration in detail. Both system performance simulation
and experimental results are presented to demonstrate the
feasibility of such an integrated system.
25 citations