5 Reasons Why You Need to Simulate Over 1,000 GNSS Signals
So many signals
Global Navigation Satellite Systems (GNSS) have transformed the way we navigate and gather geospatial data.
With multiple satellite constellations – both global, local, and LEO — providing signals for navigation and geospatial applications, the number of signals being emitted, augmented, and echoed is staggering.
The Global Positioning System (GPS), for instance, currently consists of over 30 satellites (63 by 2025!), each transmitting multiple signals across different frequencies. When you consider other GNSS constellations like GLONASS, Galileo, and BeiDou, the total number of signals increases significantly.
Moreover, these constellations are continuously evolving, with new satellites being launched and existing ones updated.
Before modern GNSS simulators
Historically, simulating the full spectrum of GNSS signals was challenging. It demanded extensive computational power, precise modeling of satellite orbits and signal propagation, and a deep understanding of the unique characteristics of each constellation. GNSS engineers had to grapple with the intricacies of signal interference, satellite geometry, and atmospheric conditions to create a realistic testing environment.
Simulating all these aspects was beyond the capabilities of legacy simulators which were not capable of generating the number of signals in view. But modern hardware is now widening the possibilities and negating the limitations of the past.
Now: Rise of the GPU
Modern GNSS simulators, like Safran’s Skydel-powered GSG-7, GSG-8, and Wavefront have successfully overcome this technological hurdle by leveraging the immense computational power of modern GPUs (Graphics Processing Units) to simulate well over a thousand GNSS signals.
Through its software-defined architecture, Skydel takes advantage of a GPUs ability to accelerate signal generation and modulation based on the pseudorange calculations performed by the CPU, enabling real-time simulation of intricate scenarios. This capability allows GNSS engineers to create highly complex and realistic environments, replicating the crowded signal landscape of today’s world. Simulating thousands of GNSS signals ensures comprehensive testing, optimizing receiver performance, and enhancing the resilience of navigation systems in the face of challenging conditions, ultimately resulting in more reliable and accurate positioning for a wide range of applications.
Better than FPGA
Another huge advantage of GPU-leveraged simulators over FPGA ones is that GPUs do not need to be pre-programmed with a firmware. Instead, signal modulation is done on-the-fly (in the software) depending on the scenario and evolution of the sky view. Unlike FPGA-based simulators, the number of simulated signals of each constellation is not static and purely dynamic.
Why more than 1,000 signals?
GNSS engineers play a pivotal role in ensuring the reliability, resiliency, and precision of GNSS-based systems and simulating more than 1,000 signals is crucial for their work.
Here are the top 5 reasons why GNSS engineers need to simulate such a large number of signals:
1. Realistic Testing Environments
Simulating over 1,000 signals allows engineers to replicate complex real-world scenarios accurately. This helps them assess the performance of GNSS systems under challenging conditions, including signal interference, multipath reflections, and space applications where the number of satellites in view increases dramatically.
2. Antenna Array Optimization
Many GNSS applications rely on antenna arrays. These can be further divided along two industries:
Commercial: Autonomous vehicles and precision agriculture, rely on antenna arrays and multi-antenna applications (e.g., in space for attitude measurement), RTK positioning (base + rover) or multi-vehicles applications.
Defense: CRPA (antenna arrays) for interference mitigation and improved signal reception. Engineers use signal simulation to fine-tune antenna designs and configurations, ensuring optimal performance in diverse or contested environments.
3. Challenging Environment Simulation
GNSS receivers must be sensitive enough to pick up the weak signals that are often encountered in challenging environments. The ability to simulate degraded signals in locations such as urban canyons, tunnels or bridges is essential for accurate positioning. Simulating a large number of signals, such as multipath echos, helps engineers evaluate receiver sensitivity and acquisition capabilities, ensuring reliable performance even in low-signal conditions.
4. Security Enhancements
In today’s world, GNSS signals are susceptible to jamming and spoofing attacks. By simulating a large number of signals, engineers can develop and test algorithms to detect and mitigate these threats, bolstering the security of GNSS systems.
5. Multi-Constellation Integration
Modern GNSS receivers often combine signals from multiple satellite constellations to enhance accuracy and availability. Simulating signals from various constellations with their unique characteristics allows engineers to optimize receiver algorithms, ensuring seamless integration for improved positioning accuracy. Moreover, the number of constellations, frequencies, and signals – fueled by the rise of LEO PNT constellations – is growing at an accelerated rate. Currently, nearly 7000 satellites orbit Earth and that number is growing monthly.
Wrap-up: 1,000 and counting
The real world of GNSS signals is vast and intricate, with numerous satellites and signals in operation. While simulating every signal can be impractical, the simulation of over 1,000 signals remains a critical tool for GNSS engineers. By using Skydel to simulate this many signals, users are able to address the complexity of GNSS environments, optimize system components, enhance security measures, and ensure accurate positioning across a range of applications and industries.
Signals add up very quickly.
In the recently published GPU Selection Guide for GNSS Simulation, a few common scenarios are mapped out to gauge the demand on the simulator and GPU.
Here is an excerpt:
Number of Signals
You can calculate the number of signals by multiplying the number of satellites visible by the number of signals of each satellite. If you have echoes you will also need to add them to the total number of signals.
- In general, we assume that 12 satellites are visible and need to be simulated.
Ex: Simulating 12 satellites transmitting GPS L1 C/A requires “12 signals”
- For each additional signal (Ex GPS L2C), we add 12 signals
Ex: Simulating 12 satellites transmitting GPS L1 C/A + L2C requires “2×12 = 24 signals”
- Multiply the number of signals per simulated echo (Multipath)
Ex: Simulating 12 satellites transmitting GPS L1 C/A + L2C and 1 echo requires “48 signals”
Or in another example, if you need to simulate every civilian signal with 1 echo and 2 antennas for a spacecraft, you would have the following calculation:
- Number of signals at 60 MSps: 12 × 15 × 2 × 2= 720
- Number of Signals at 125 MSps: 13 × 15 × 2 × 2 = 780
Total # of signals required: 1,500
Skydel and High-Capacity
Since its inception, Skydel has strived to achieve the ability to simulate all signals in view. Its combination of software-defined architecture, and ability to leverage modern SDRs and GPUs has allowed it to reach an almost unlimited number of signals/channels.
In fact, soon, the number of signals possible in a GNSS simulator will no longer be a differentiator, and systems with a “limited” number of signals will be a relic of the past.
In the last year, Skydel has seen massive advances in signal numbers in the last year and is already capable of generating 1600+ signals (including legacy constellations) on Safran’s GSG-8 simulator platform. Paired with even higher-end hardware, a basic Skydel configuration is capable of reaching many more signals with no impact to stability and performance.