Phase Differential Global Positioning System Research Articles

An Adaptive Fault-Tolerant Multisensor Navigation Strategy for Automated Vehicles

This paper presents a novel adaptive fault-tolerant multisensor navigation strategy for automated vehicles on the automated highway system. To ensure safe and reliable running, the main concern is how we can realize sensor fault detection, isolation, and accommodation. The proposed strategy adopts a hybrid decentralized filter architecture that fuses multiple sensors, including the strapdown inertial navigation system, the carrier phase-differential Global Positioning System (GPS), the wheel encoder, and the electronic compass. Through the integration of multiple redundancy sensors, the navigation system has fault-tolerant potential. The integrated filter model is first established in detail. Then, a highly fault-tolerant navigation filter iterative algorithm is proposed. The proposed algorithm realizes fault tolerance by utilizing fuzzy logic to update the local filter based on a relative degree of mismatch by simultaneously considering sensor failure degree and to make fault isolation decisions. To compare and evaluate the fault-tolerant performance, several traditional navigation methods are also investigated. Simulation results demonstrate that the proposed integrated navigation method can effectively detect, isolate, and accommodate a variety of hard and soft sensor failures, which may even simultaneously occur.

Reliable integrated navigation system based on adaptive fuzzy federated Kalman filter for automated vehicles

There is an increasing interest worldwide in developing automated vehicles on the highway. From the viewpoint of safe driving, their navigation system should be accurate, robust, and reliable. This paper presents a fault-tolerant navigation approach for automated vehicles based on multi-sensor integration utilizing a proposed adaptive fuzzy federated Kalman filter (AF-FKF). The FKF model is first discussed in detail, which fuses multiple and redundant sensors incorporating strapdown inertial navigation system, carrier phase-differential global positioning system, electronic compass, machine vision, and digital map. The adaptive fuzzy FKF algorithm is then proposed to adjust the FKF information-sharing factors adaptively, detect, and isolate the faulty sensor in the FKF effectively. In order to compare the fault-tolerant performance, several traditional navigation methods are also considered. Simulation results demonstrate that the proposed integrated navigation approach can detect, isolate, and accommodate different types of sensor failures including hard failures and soft failures. The proposed approach can adapt to highly reliable navigation requirements for automated vehicles in complex situations.

ACC+Stop&Go Maneuvers With Throttle and Brake Fuzzy Control

Research on adaptive cruise control (ACC) with Stop&Go maneuvers is presently one of the most important topics in the field of intelligent transportation systems. The main feature of such controllers is that there is adaptation to a user-preset speed and, if necessary, speed reduction to keep a safe distance from the vehicle ahead in the same lane of the road, whatever the speed. The extreme case is the stop and go operation in which the lead car stops and the vehicle at the rear must also do so. This paper presents the development of an ACC system and related experiments. The system input information is acquired by a real-time kinematic phase differential global positioning system (GPS) (i.e., centimetric GPS) and wireless local area network links. The outputs are the variables that control the pressure on the throttle and brake pedals, which is calculated by an onboard computer. In addition, the car control is based on fuzzy logic. The system has been installed in two mass-produced Citroe/spl uml/n Berlingo electric vans, in which all the actuators have been automated to achieve humanlike driving. The results from real experiments show that the unmanned vehicles behave very similarly to human-driven cars and are very adaptive to any kind of situation at a broad range of speeds, thus raising the safety of the driving and allowing cooperation with manually driven cars.

Two antennas GPS-aided INS for attitude determination

This paper describes a navigation system incorporating inertial and two-antenna carrier phase differential global positioning system (GPS) measurements. The major objective is to demonstrate full attitude determination even for a nonaccelerating vehicle. The motivating application for this project is vehicle control. Therefore, the system is designed to operate reliably whether or not GPS measurements are available. The navigation system estimates vehicle position, velocity, acceleration, attitude, and angular rates at 150 Hz with accuracy (standard deviation) of 1.5 cm, 0.8 cm/s, 2.2 cm/s/s, 0.03 deg (pitch and roll), 0.1 deg (yaw), and 0.1 deg/s using a 1.01 m baseline between antennas. The navigation state vector is processed to produce a control state vector at 30 Hz. The control demonstrations involve basic trajectory following as well as trajectory relative maneuvering (i.e., tracking sinusoidal perturbations and performing lane changes). During experimental testing, a magnetic system was available to provide a ground truth reference. The demonstrated accuracy is sufficient for control of vehicles in an automated highway system. Other possible applications include precision farming, aircraft and satellite control, and control or guidance of automated mining or highway maintenance vehicles.

Magnetometer and differential carrier phase GPS-aided INS for advanced vehicle control

This paper describes the design, analysis, implementation, and experimental results of a triple redundancy navigation system incorporating magnetometer, inertial, and carrier phase differential Global Positioning System (GPS) measurements. The navigation system is able to accurately estimate vehicle attitude (including yaw) as long as the vehicle velocity is not zero. The motivating application was lateral vehicle control for intelligent highway systems. The system was designed to operate reliably whether or not GPS and magnetometer measurements were available. The navigation system provides vehicle position, velocity, acceleration, pitch and roll, yaw, and angular rates at 150 Hz with accuracies (standard deviation) of 2.8 cm, 0.8 cm/s, 2.2 cm/s/s, 0.03/spl deg/, 0.18/spl deg/, and 0.1/spl deg//s. This navigation state vector was processed to produce a control state vector at approximately 30 Hz. This triplicate redundancy navigation system reliably demonstrated lateral vehicle control in the following situations: both GPS and magnetometer aiding the inertial navigation system (INS), GPS-aided INS, magnetometer aided-INS, and switching between GPS and magnetometer aiding of the INS at random times.

Digital elevation map generation using VHF-band SAR data in forested areas

The paper investigates digital elevation model (DEM) generation based on data from the ultra wideband coherent all radio band sensing (CARABAS) very high frequency (VRF)-band synthetic aperture radar (SAR). The results show excellent capability to penetrate forest areas, i.e., the generated DEMs are found to be close to the true ground height. A conventional DEM, based on stereo photography and surveying, and additional phase differential Global Positioning System (GPS) measurements have been used for comparison. The results in heavily vegetated areas (stem volume up to 600 m/sup 3//ha) show a mean height difference of less than 1.5 m and a root-mean-square (rms) error of less than 1.0 in compared to the conventional DEM. Stable backscattering properties allows us to use large baselines in order to obtain high height sensitivity. However, the amount of poor data due to low coherence increases with the increase of the baseline. The optimum baseline which balances these two effects is found to correspond to an incidence angle difference of 4/spl deg/-8/spl deg/.

Real-time differential carrier phase GPS-aided INS

This article describes the implementation and experimental results of a real-time carrier phase differential Global Positioning System (GPS) aided inertial navigation system (INS). The implementation is the result of a study to analyze the capabilities of such a system relative to the requirements of advanced vehicle control and safety systems for intelligent transportation systems. Such navigation systems have many application possibilities (e,g., aviation and precision flight, automated mining, precision farming, dredging, satellite attitude control). Advantages and disadvantages of the GPS, INS, and differential GPS-aided INS approaches are discussed. The implementation achieves 100-Hz vehicle state estimates with position accuracies at the centimeter level through the use of differential carrier phase GPS techniques.