Question

Brief description of requirements

(Lots of good answers here, thanks to all, I’ll update if I ever get this flying).

A detector runs along a track, measuring several different physical parameters in real-time (determinist), as a function of curvilinear distance. The user can click on a button to ‘mark’ waypoints during this process, then uses the GUI to enter the details for each waypoint (in human-time, but while the data acquisition continues).

Following this, the system performs a series of calculations/filters/modifications on the acquired data, taking into account the constraints entered for each waypoint. The output of this process is a series of corrections, also as a function of curvilinear distance.

The third part of the process involves running along the track again, but this time writing the corrections to a physical system which corrects the track (still as a function of curvilinear distance).

My current idea for your input/comments/warnings

What I want to determine is if I can do this with a PC + FPGA. The FPGA would do the ‘data acquisition’, I would use C# on the PC to read the data from a buffer. The waypoint information could be entered via a WPF/Winforms application, and stocked in a database/flatfile/anything pending ‘processing’.

For the processing, I would use F#.

The the FPGA would be used for ‘writing’ the information back to the physical machine.

The one problem that I can foresee currently is if processing algorithms require a sampling frequency which makes the quantity of data to buffer too big. This would imply offloading some of the processing to the FPGA – at least the bits that don’t require user input. Unfortunately, the only pre-processing algorithm is a Kalman filter, which is difficult to implement with an FPGA, from what I have googled.

I’d be very greatful for any feedback you care to give.

UPDATES (extra info added here as and when)

At the entrance to the Kalman filter we’re looking at once every 1ms. But on the other side of the Kalman filter, we would be sampling every 1m, which at the speeds we’re talking about would be about 2 a second.

So I guess more precise questions would be:

1. implementing a Kalman filter on an FPGA – seems that it’s possible, but I don’t understand enough about either subject to be able to work out just HOW possible it is.

2. I’m also not sure whether an FPGA implementation of a Kalman will be able to cycle every 1ms – though I imagine that it should be no problem.

3. If I’ve understood correctly, FPGAs don’t have hod-loads of memory. For the third part of the process, where I would be sending a (approximately) 4 x 400 array of doubles to use as a lookup table, is this feasible?

4. Also, would swapping between the two processes (reading/writing data) imply re-programming the FPGA each time, or could it be instructed to switch between the two? (Maybe possible just to run both in parallel and ignore one or the other).

5. Another option I’ve seen is compiling F# to VHDL using Avalda FPGA Developer, I’ll be trying that soon, I think.

Answer 1

Since you are moving along a track, I have to assume the sampling frequency isn’t more than 10 kHz. You can offload the data to PC at that rate easily, even 12 Mb USB (full-speed).

For serious processing of math data, Matlab is the way to go. But since I haven’t heard of F#, I can’t comment.

4 x 400 doubles is no problem. Even low-end FPGAs have 100’s of kb of memory.

You don’t have to change images to swap between reading and writing. That is done all the time in FPGAs.