Logo: OroliaThe following is an interview with Lisa Perdue, Simulation Product Line Director for Orolia about the role that software-defined architecture and COTS hardware, from software-defined radios (SDR) to graphics processing units (GPU) play in building a better GNSS simulation architecture.

Q: What is software-defined architecture in the context of GNSS simulation?

Photo: Lisa Perdue

Photo: Lisa Perdue

A: At it’s core, software-defined architecture enables us to use one piece of hardware multiple ways. We can reprogram that hardware to act as a jammer, spoofer, or a GNSS signal. We don’t have to design new hardware in order to support each. The software controls the hardware, not the other way around. Rather than having an FPGA that requires programming, Software can leverage a software-defined radio (SDR) to generate signals, and COTS GPUs to scale whatever power and complexity you need.

Q: Aren’t all simulators with software instructing hardware technically software-defined?

A: No. Most simulators on the market, including our own GSG-5 and GSG-6, have boards in them that have fixed purposes. You can use those boards for any frequency band that you want. At run-time, the software sends the board an instruction, for example, “Run L5”. The next time, the same board could “Run L2”, but that hardware has been designed to only work with a fixed set of instructions. So when new signals, new capabilities, and new scenarios emerge that the hardware wasn’t designed to handle, the software has no way of issuing the orders. It’s software-defined, until the software can’t define it in a way the supporting hardware can understand.

True software-defined simulation, as Skydel offers, is hardware agnostic. It doesn’t require the hardware to be hard-coded to understand what an L5 or L2 band is. It just requires software that knows how to leverage a GPU and SDR to execute it.

Q: Why use GPUs over FPGA?

A: The biggest limitation is in the number of signals you can generate with the hardware you have. In simulators where the FPGA is generating the signals, there are fixed hardware channels. When you program the FPGA, you can only generate so many signals out of that. GPUs contain a multi-core structure suited for parallel processing, so we’re able to generate many more satellites and we’re not constrained by hardware channels. So simulators powered by GPU enable all-in-view satellites. You don’t have to choose or make a trade-off between price and the number of satellites you’re able to simulate. You are able to simulate whatever you would see in the sky. If that’s 12 GPS, 10 GLONASS, and 10 Galileo, you’re going to see the them all when using the GPU without having to purchase additional FPGAs additional channels. The GPU’s power is enough.

Q: What kinds of benefits does all of this offer a user?

A: Cost is the biggest. You can utilize hardware that’s already available on the market and scale it according to your needs. You can use the same software in a very small form factor like an Intel NUC and generate signals from it at your home office, or you can do it in a full rack, multi-element Wavefront system testing advanced anti-jam antennas, but the software remains the same.

But features are a big benefit as well. That economy of scale extends to the product, as all of our R&D at Orolia can go into making the software as advanced as possible, not into building proprietary hardware to keep up with new signals that will need replacement in a few years. We’ll trust the best GPU makers in the world like NVIDIA to scale the hardware power for us. As new SDRs enter the market, we can simply write drivers that instruct them how to generate our RF. And as new signals and use cases emerge, we can just push it as a software update to our users, without having to upgrade or service their hardware.

Q: What’s next for the GNSS simulation industry?

A: I mentioned the scalability and believe that is where the industry is heading. There are a lot of small satellite startups, UAV startups, and universities doing GNSS research requiring advanced simulation, but the cost and knowledge required are barriers to entry. We want simulation to be accessible to all and easy to learn, without having to sacrifice features. But this also requires some acknowledgment that new use cases are constantly emerging, and no one is going to write software that covers all of them. So, like any software, there will be more demand for open source architecture, so users can write and share their own plugins for specific use cases. We’re prepared at Orolia, to meet that demand and help our users define the future together with our plugin github, our user community, and our close collaboration with over 40 universities around the world doing GNSS research in our Academic Partnership Program.

For a brief, 10-minute tour of what Skydel can do, check out this on-demand demo.

Header video: Orolia

This page was produced by North Coast Media’s content marketing staff in collaboration with Orolia. NCM Content Marketing connects marketers to audiences and delivers industry trends, business tips and product information. The GPS World editorial staff did not create this content.