| GPS: Selecting the Best Type of GPS Data for your Application, Part 2 of 2
By Chuck Gilbert Introduction
An often misunderstood aspect of GPS is that not all GPS positions are computed in the same manner. There are actually several ways that the GPS signal can be used to compute a position. The two most common ways that the GPS signal is used are by using code data or by using carrier data. Code data are computed from a code generated by the GPS satellite, then transmitted to the user on a radio signal. Carrier data are computed from examining the actual radio signal that was used to carry information from the satellite to the user.
This month's column continues to examine these two types of GPS data and the difference between them. In July, this column discussed some of the comparative differences between GPS code data and GPS carrier data. In particular, addressing issues associated with signal continuity. Note that code data are much less accurate than carrier data, but do not require continuous tracking of every visible satellite. On the other hand, carrier data can be used to compute very accurate positions, but require a continuously clear view of most of the sky. The clear sky view is needed so that several satellites can be tracked without interruption. This requirement can be difficult to meet in some urban environments. The view of the sky is often occluded by trees, buildings, or even people. In such an environment more rigorous attention to data collection strategy is required to ensure usable carrier data. While July's column focused on where you might be able to utilize carrier data, this month focuses on how to plan and execute field work so as to get the most from your carrier data.
Most GPS users involved with GIS data collection are using single frequency GPS receivers. Therefore, the examples in this month's text assume that the GPS receiver is recording carrier data from only one of the two GPS frequencies, and that the base and rover receivers are within a few kilometers of one another. A change in field strategy
Users of code-based GPS receivers long used averaging techniques to improve their spatial accuracy. For example, recording a few hundred positions at the same location over several minutes, then averaging them together will often yield better accuracy than simply recording only one position over a one second period. If any small, random errors remain after differential processing, they can be averaged out in this manner. Such averaging techniques, taken over a 10-15 minute period, may improve code-based accuracy from the range of perhaps 1-meter to something like 50-80 centimeters. However, this is not necessarily as useful a technique for the collection of carrier data.
The key to collecting the best possible carrier data is maintaining satellite lock for as long as possible. Specifically, the factor of greatest importance is the length of time for which four or more satellites are continuously tracked (or "time since loss of lock"). As the time since loss of lock increases, the accuracy of all the positions computed during that period will improve. This is different from averaging in that each individual position that is computed will be improved. For example, suppose carrier data are successfully recorded for 20 minutes without any loss of satellite lock. If the data recording was at a five second interval, there would be 240 positions that could be computed from the carrier data. In such an example, each of these 240 positions could have an accuracy of about 10 centimeters.
The critical difference here is that the user of code-based GPS would have to stay at the same location for the entire time that is to be averaged together. In the case of the carrier data, however, the user is free to go anywhere as long as the satellite lock is maintained. Therefore, in order to achieve a 10-centimeter position for a utility pole or other asset, the user can travel from pole to pole, spending only seconds at each location and still obtain high accuracy as long as satellite lock is maintained between poles. (This is because every epoch of data during a continuous period of satellite tracking can be processed to same accuracy.) So, what's the play?
This difference between code and carrier can significantly alter one's data collection strategy. With code, the strategy was to get from point to point as quickly as possible and spend more of your time on each point. With carrier, the strategy is to maintain satellite lock for as long as possible, and to visit points in an order that caters to maximizing the time between losses of satellite lock.
It is important to note that with carrier data; the data being collected before, after, and between points of interest is just as important as the data collected at the point of interest. Considering the following scenario. A user is collecting data on some roadside assets and desires an accuracy of about 10 centimeters for each asset. (Note that the minimum amount of continuous carrier data to achieve 10 centimeter accuracy would be about 20 minutes.) Suppose that during the first five minutes of data collection, the user occupies 18 of these assets. However, only five minutes after beginning to collect data (or five minutes since the previous loss of lock) the user can see that he will pass under a bridge in a few moments. The problem is that when the user nears the bridge, he will lose satellite lock. If the user passes under the bridge immediately, the 18 previously recorded assets will be imbedded in a set of carrier data that is only five minutes long. A five minute set of carrier data may not even be processable and if it is processed, is not likely to yield results better than about 40 centimeters. This is not good enough. What are the user's options?
One option is to just sit down and wait. The user does not have to wait at any particular location, just as long as satellite lock is maintained for about another 15 minutes. Another option is to take the extra time required to go over or around the bridge, again, while maintaining satellite lock. An interesting and clever option is to have anticipated this possibility earlier in the day. Often there is a little dead time at the beginning of a day of field work while the user arranges gear, gets coffee, or plans the route, etc. If the user had thought to turn on the GPS receiver before he was ready to begin data collection, it is possible that the receiver may have been able to continuously track 30 or 40 minutes of carrier before the field work had even started. If this were the case, the user could go under the bridge then just make sure he gets his 20 minutes before the next bridge.
Note that with code data there is no incentive for the user to go out of the way (e.g. around the bridge). For code data collection there would be no penalty for passing under the bridge - your positions on either side of the bridge would be equally accurate. With code data, the greatest productivity is gained by spending the minimum travel time and maximizing the data collection time at locations of interest.
However with carrier data the opposite is true. As soon as you pass under the bridge, your time since last loss of lock is set back to zero. Therefore, all of the data collected prior to the loss of lock will be locked into an accuracy based upon the prior duration of uninterrupted carrier. With carrier data, the greatest accuracy is gained by maintaining continuous satellite lock and spending only a few moments at each location. Summary
Neither code nor carrier are inherently superior to the other. They are different tools and have differing relative strengths. Carrier data are more inherently suited to high accuracy data collection. Code data are more suited to high productivity. In order to select which type of GPS data collection is best suited to your application, it is helpful to understand the ramification on your data collection procedures. Back |
