Additional tracking device augmentation techniques
Additional techniques are being developed for increasing the accuracy of the positioning information derived from the GPS for certain applications. One technique, which has been developed by the US Federal Aviation Administration (FAA), uses transmissions from communication satellites to improve the positioning accuracy of GPS tracking device in aircraft. This technique, known as the wide area augmentation system (WAAS), uses a network of wide area ground reference stations (WRS) and two wide area master stations (WMS) to calculate pseudorange correction factors for each SV, as well as to monitor the operational health of each SV. This information is uplinked to communication satellites in geostationary earth orbit (GEO), which transmit the information on the L1 frequency, along with additional ranging signals. This system has improved the positioning accuracy of GPS on board aircraft to within 7 metres horizontally and vertically, allowing the system to be used by aircraft for Category I precision approaches. A Category I system is intended to provide an aircraft operating in poor weather conditions with safe vertical guidance to a height of not less than 200 feet with runway visibility of at least 1800 feet.
Another method for improving positioning accuracy is known as carrier-phase GPS. This is a technique where the number of cycles of the carrier frequency between the SV and the receiver is measured, in order to calculate a highly accurate pseudorange. Because of the much shorter wavelength of the carrier signal relative to the code signal, positioning accuracies of a few millimetres are possible using carrier-phase electronic tracker techniques.
A variety of input sensors can be used to provide DR capability. In the intelligent vehicle example, several different sensor inputs can be made available to the navigation system to assist in DR calculation. The types of sensors that could be used to enable DR in a vehicle system include:
magnetic compass, which can provide a continuous, coarse-grained indication of the direction in which the vehicle is moving
gyroscope, which can be used to detect the angular movement of the vehicle
speedometer, which can provide the current speed of the vehicle
odometer, which can provide continuous data on the elapsed distance
wheel speed sensors, such as Hall-effect or variable reluctance sensors (VRS), which can provide fine-grained vehicle speed information
accelerometers, which can detect changes in the velocity of the vehicle.
Many of these sensors are already widely used in vehicles for other applications. Accelerometers are being used today in impact detection (airbag) systems; wheel speed sensors are being used in traction-control and anti-lock braking systems; and of course the trip meters available today in many cars use inputs from the speedometer, odometer and compass to calculate distance travelled, distance remaining and fuel economy.
Systems that leverage inputs from remote vehicle sensors to enable DR can certainly provide more consistent positioning information under some circumstances than may be possible with a single-point electronic tracker . However, depending upon the mix of sensor inputs used, the accuracy of the resulting position data may vary. Some of these sensors are more accurate than others, and most are subject to a variety of environmental, alignment and computational errors that can result in faulty readings. Some vendors of DR-enabled positioning systems have been exploring methods of reducing the effects of these errors. The development of self-correcting algorithms and selfdiagnosing sensors may help reduce the impact that sensor errors can have on these systems in the future.
More GPS Solution at http://www.jimilab.com/ .
Another method for improving positioning accuracy is known as carrier-phase GPS. This is a technique where the number of cycles of the carrier frequency between the SV and the receiver is measured, in order to calculate a highly accurate pseudorange. Because of the much shorter wavelength of the carrier signal relative to the code signal, positioning accuracies of a few millimetres are possible using carrier-phase electronic tracker techniques.
A variety of input sensors can be used to provide DR capability. In the intelligent vehicle example, several different sensor inputs can be made available to the navigation system to assist in DR calculation. The types of sensors that could be used to enable DR in a vehicle system include:
magnetic compass, which can provide a continuous, coarse-grained indication of the direction in which the vehicle is moving
gyroscope, which can be used to detect the angular movement of the vehicle
speedometer, which can provide the current speed of the vehicle
odometer, which can provide continuous data on the elapsed distance
wheel speed sensors, such as Hall-effect or variable reluctance sensors (VRS), which can provide fine-grained vehicle speed information
accelerometers, which can detect changes in the velocity of the vehicle.
Many of these sensors are already widely used in vehicles for other applications. Accelerometers are being used today in impact detection (airbag) systems; wheel speed sensors are being used in traction-control and anti-lock braking systems; and of course the trip meters available today in many cars use inputs from the speedometer, odometer and compass to calculate distance travelled, distance remaining and fuel economy.
Systems that leverage inputs from remote vehicle sensors to enable DR can certainly provide more consistent positioning information under some circumstances than may be possible with a single-point electronic tracker . However, depending upon the mix of sensor inputs used, the accuracy of the resulting position data may vary. Some of these sensors are more accurate than others, and most are subject to a variety of environmental, alignment and computational errors that can result in faulty readings. Some vendors of DR-enabled positioning systems have been exploring methods of reducing the effects of these errors. The development of self-correcting algorithms and selfdiagnosing sensors may help reduce the impact that sensor errors can have on these systems in the future.
More GPS Solution at http://www.jimilab.com/ .
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