Teledyne SP Devices enable scalable satellite signal monitoring across multiple frequency bands
Satellite monitoring allows continuous observation of satellite communications and navigation signals to guarantee link quality, detect interference, and verify compliance with spectrum regulations
These systems deliver global, consistent visibility into uplink and downlink behaviour- critical for applications such as GNSS integrity, spectrum surveillance, interference hunting, and system validation.
Monitoring objectives and system architecture
The main goal with satellite monitoring is to maintain the integrity of space-to-ground and ground-to-space links, including verifying uplink and downlink quality, detecting unintentional or malicious interference, and supporting regulatory enforcement.
Monitoring systems are usually structured around three elements:
- The space segment: Consists of satellites with transponders and antennas operating in defined frequency bands.
- The ground segment: Contains monitoring stations equipped with large antennas, RF front ends, and digitisers
- The user segment: Where specialised software and hardware analyse and visualise the captured data
Frequency bands and sampling considerations
Satellite services operate across designated radio-frequency bands divided into uplink and downlink sub-bands in bidirectional systems to minimise mutual interference. Downlinks are typically allocated to the lower portion of a band because of lower atmospheric attenuation, whereas uplinks occupy higher frequencies to support higher data rates. Sub-band definitions can vary by system; for example, Galileo uses ‘E’ designations within the L-band rather than the ‘L’ nomenclature used by other GNSS constellations.
This diversity makes frequency planning and sampling strategy critical in monitoring. The sampling rate must ensure that the signal of interest falls within a single Nyquist zone, with out-of-band components suppressed by analog filtering. For direct sampling, this translates to minimum rates of 2 GSPS for L-band, 4 GSPS for S-band, and 8 GSPS for C-band, assuming appropriate bandpass filters are applied.
Digitisation and front-end signal capture
Modern monitoring systems are dependent on wideband digitisers to convert analog RF signals into digital data streams. Devices such as the ADQ35-WB from Teledyne SP Devices support sampling of L- and S-band signals without frequency mixers, reducing system complexity and calibration effort.
With 12-bit resolution and up to 9GHz of usable input bandwidth, these digitisers enable flexible deployment across multiple satellite bands. External low-noise amplifiers and anti-alias filters are essential to preserve signal fidelity and prevent spectral folding during analog-to-digital conversion.
Sampling-rate selection impacts data integrity and downstream processing efficiency. For example, sampling the L-band at 5 GSPS positions the signal within the first Nyquist zone, while S-band undersampling at 4 GSPS confines the signal to the second Nyquist zone with sufficient guard bands. In contrast, poorly chosen rates can split the signal across Nyquist boundaries, introducing unavoidable aliasing.
FPGA pre-processing and data reduction
Raw data rates from wideband digitisers can exceed practical limits for transfer and storage. At 10 billion samples per second and 2 bytes per sample, a channel can generate around 20GB/s. To manage this volume, on-board FPGA processing is used to reduce data rates before transfer over PCIe links.
Two approaches are relevant for satellite monitoring:
- Bit compression: Can reduce the number of bits per sample to enable continuous streaming within PCIe bandwidth constraints while preserving full-band information.
- Digital down-conversion: Implemented using FPGA-based numerically controlled oscillators, filters, and decimation stages, translates selected RF channels to baseband or intermediate frequencies. This can reduce data rates and improve signal-to-noise ratio through filtering and coherent processing.
High-throughput data transfer and GPU processing
For real-time and near-real-time analysis, PCIe-based architectures are ideal. Peer-to-peer data transfer enables digitisers to stream data to GPUs using DMA, bypassing host CPU and system memory. This decreased latency and allows aggregate throughputs approaching the limits of PCIe Gen5, supporting simultaneous streams from several digitisers.
GPUs complement FPGA processing by handling computationally intensive but less latency-critical tasks, including channelisation, demodulation, and long-term statistical analysis.
High-speed recording and storage
When long-duration recording is needed, storage bandwidth can be a limiting factor. RAID configurations based on NVMe SSDs, connected through PCIe carrier boards, enable parallel writes across multiple drives.
Enterprise-grade SSDs maintain sustained write speeds over long periods, facilitating aggregate recording rates of tens of gigabytes per second and total capacities reaching the petabyte scale per slot. Consumer-grade drives are suitable for shorter captures but exhibit throughput degradation once internal SLC caches are exhausted.
For modern satellite monitoring
Combining wideband digitisation, FPGA-based pre-processing, GPU acceleration, and scalable PCIe storage has enabled modern satellite monitoring systems to provide a cost-efficient, flexible foundation for RF intelligence.
This architecture supports evolving requirements such as real-time interference detection, multi-band monitoring, and large-scale data capture, making it suitable for operational monitoring networks and research-oriented measurement campaigns.
