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Session D8: PNT Situational Awareness 1

Spectral Compression for RF Capture and Forward
David Noll, Derek Anton, William Woodworth, Lockheed Martin
Location: Ballroom D
Alternate Number 1

Objective:
This presentation will provide a novel algorithmic approach to capture, compress, and forward RF spectral data to a centralized location for processing. The compression approach was developed leveraging the Lockheed Martin Software Defined Radio (SDR) framework, and was evaluated for use in a GPS civil and military monitoring mission. The goal was to reduce requirements on communications bandwidth, while maintaining sufficient measurement quality and minimizing data demodulation errors.
Background:
RF spectral compression is a major enabler for RF capture and forward applications when links are bandwidth constrained. Utilization of remote assets (e.g. terrestrial, airborne, or space) for data capture, compression, and forwarding could supplement Positioning, Navigation, and Timing (PNT) monitoring and situational awareness missions with data previously not operationally available. Additionally, this has the potential to reduce the security footprint of classified signal monitoring as it enables sensitive signal processing to be moved from the edge to a central processing facility.
This work continues the evolution of the Lockheed Martin Software Defined Radio (SDR) framework, which is a mature framework developed over 10 years through contract and internal LM investment. The LM SDR framework flexibility comes from its use of high-level C/C++ software on a general purpose Central Processing Unit (CPU) / General-Purpose Computation on Graphics Processing Unit (GP-GPU) for all baseband signal processing and commodity RF hardware to reach target frequencies. Multiple operational programs have been developed from the LM SDR framework, including 1.) GPS Operational Monitor Station Receivers (Monitor Station Technology Improvement Capability (MSTIC) and Modernized MSTIC (M-MSTIC)), 2.) GPS Operational Receiver Commanding and Keying Capability (MRCK), and 3.) GPS Payload Verification Equipment (GPS III RF Coupling, GPS IIIF Signal Characterization Set (SCS)).
Technical Summary:
Typical RF spectral compression approaches use RF filtering, quantization, and duty cycling to reduce the effective bandwidth. The approach presented here includes the use of a single frequency domain compression operation (Fast Fourier Transform (FFT) -> Bin Selection/Compression -> Inverse Fast Fourier Transform (IFFT)) to achieve filtering and spectral compression. This contrasts with other approaches that perform more serial processing using a time domain polyphase filter. Our approach simplifies the algorithm and provides fine-grained control over the selection of the spectrum; exclusions and inclusions can occur at the granularity of a single FFT frequency bin, which is not practically achievable with other approaches. This approach is also highly parallelizable, making it well suited for GP-GPU processing in the LM SDR framework and able to seamlessly take advantage of processing gains as COTS hardware evolves.
The RF spectral compression approach was assessed against a simulated monitoring scenario. GPS L1 C/A, P-Code, and M’-code were generated at complex baseband, compressed, decompressed, and processed in the software receiver portion of the M-MSTIC. The impact to the receiver’s tracking performance, measurement quality, and data demodulation were characterized. The results were found to compress the data by 99.6% and while still maintaining sufficient measure quality to meet the monitoring mission.
In addition to the results described, we believe the algorithm, enabled by our fundamental full software SDR, has a wide range of mission applicability beyond traditional PNT, is tunable for waveform/mission requirements, and is able to run on a wide range of hardware platforms.

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