GPS World, December 2009

WIRELESS Receiver Design Time History of Horizontal Error 20m Outage 0 1000 2000 3000 4000 5000 6000 7000 8000 20 18 16 14 12 10 8 6 4 2 0 Horizontal Error m Time s Å FIGURE 5 Quantifying error using a truth reference From these values it is straightforward to compute basic statistics like mean 95th percentile and maximum errors over the course of the trial An example of this is shown in FIGURE 5 with the data horizontal 2D error in this case presented in several different ways Note that the time interpolation step is not necessarily negligible not all devices align their outputs to whole second boundaries of GPS time so assuming a typical 1 Hz update rate the timing skew between a DUT and the truth reference can be as large as 05 seconds At typical motorway speeds say 100 km hr this results in a 139 meter error between two points that ostensibly represent the same position On the other hand high end GPS INS systems can produce outputs at 100 Hz or higher in which case this effect may be safely neglected Despite their utility both methods described above suffer from two fundamental limitations results are inherently obtainable only in real time and the scope of test coverage is limited to the number of receivers that can be fixed on the test rig simultaneously Thus a test car outfitted with five receivers a reasonable number practically speaking would be able to generate at most five quasiindependent results per outing Software Approach The architecture of a software GNSS receiver is ideally suited to overcoming Histogram of Horizontal Error 20m 0 5 10 15 20 800 600 400 200 0 Number of position fixes Percentile 50 890 m 0 5 10 15 20 100 80 60 40 20 0 Horizontal Error m Relative number of fixes the limitations described above as follows The raw IF data stream from the analog to digital converter is recorded to a file during the initial data collection This file captures the essential characteristics of the RF chain antenna pattern downconverter filters and so on as well as the signal environment in which the recording was made fading multipath and so on The IF file is then reprocessed offline multiple times in the lab applying the results of careful profiling of various hardware platforms for example Pentium class PC ARM9 based embedded device and so on to properly model the constraints of the desired target platform Each processing pass produces a position trajectory nominally identical to what the DUT would have gathered when running live The complete multiple offset postprocessing MOPP setup is illustrated in FIGURE 6 The fundamental improvement relative to a conventional testing approach lies in the multiple reprocessing runs For each one the raw data is processed starting from a small progressively increasing time offset relative to the start of the IF file A typical case would be 256 runs with the offsets uniformly distributed between 0 and 100 milliseconds but the number of runs is limited only by the available computing resources and the granularity of the offsets is limited only Horizontal Error m 1 m bin Receiver Turned On First Fix Last Fix Availability Error 10 m Error 20 m Maximum Error Mean Error Standard Deviation N A 13 50 17 16 14 33 8679 7068 8144 5409 4405 8144 7881 6418 8144 72071 m 1057 m 2438 m RF Front End raw IF samples PP start offset 0 Trajectory 0 PP start offset B Trajectory 1 PP start offset 2B Trajectory 2 PP start offset nB Trajectory n Å FIGURE 6 Multiple Offset Post Processing MOPP by the sampling rate used for the original recording The resulting set of trajectories is essentially the physical equivalent of having taken a large number of identical receivers 256 in this example connecting them via a large signal splitter to a single common antenna starting them all at approximately the same time but not with perfect synchronization and traversing the test route This approach produces several tangible benefits The large number of runs dramatically increases the statistical significance of the quantitative results mean accuracy 95th percentile error worst case error and so on produced by the test The process significantly increases the likelihood of identifying uncommon but non negligible corner GPS World December 2009 www gpsworld com 30