Signal Intelligence

A SIGINT platform consists of: RF collection hardware (wideband receivers, software-defined radios); a signal processing pipeline (channelization, demodulation, protocol decoding); a signal database (storing intercepts with metadata – frequency, time, location); an exploitation workstation (for analyst review, transcription, and reporting); a geolocation engine; and a dissemination system that delivers finished intelligence products to C2 and fusion platforms. Corvus Intelligence engineers bespoke SIGINT platforms for defense agencies across all these components.

An SDR is a radio communications system where components traditionally implemented in hardware – filters, modulators, demodulators – are implemented in software running on a general-purpose processor or FPGA. SDR platforms like USRP, HackRF, or KiwiSDR can be reconfigured in software to receive and transmit across a wide frequency range and support multiple waveforms. In defense SIGINT, SDRs are used for wideband spectrum monitoring, signal collection, and protocol analysis – and can be updated to cover new target waveforms without hardware replacement.

TDOA measures the difference in the time a radio signal arrives at two or more synchronized collection stations. Each pair of stations defines a hyperbola of possible emitter locations; intersecting hyperbolas from three or more station pairs triangulates the emitter position. TDOA requires precise time synchronization between collection sites (typically GPS-disciplined clocks) and a signal processing pipeline that cross-correlates signals to measure arrival time differences with nanosecond precision. Accuracy depends on baseline geometry, signal bandwidth, and synchronization quality.

Spectrum monitoring in a defense context involves continuously scanning assigned frequency bands to detect signals that do not belong – unauthorized transmitters, enemy reconnaissance devices, improvised jamming sources, or inadvertent emissions from compromised equipment. Detection algorithms compare the observed spectrum against a known-good baseline and alert on anomalous signals. Real-time spectrum monitoring is a key component of TSCM (Technical Surveillance Countermeasures) and electronic protection operations.

Automated signal classification uses machine learning models – CNNs, LSTMs, or transformer architectures – to identify the waveform type, modulation scheme, protocol, and potentially the specific platform or equipment type of an intercepted signal. Training data consists of labeled I/Q samples of known waveforms. In defense SIGINT, automated classification reduces analyst workload and accelerates emitter identification – enabling real-time processing of the volume of signals encountered in a dense RF environment.

Electronic Warfare is the military action that uses the electromagnetic spectrum to sense, protect, and deny. It has three elements: Electronic Support (ES) – passive collection and analysis of emitters (overlaps with SIGINT); Electronic Attack (EA) – jamming, deception, and directed energy weapons; and Electronic Protection (EP) – protecting own systems from enemy EW. SIGINT platforms feed directly into EW operations: ES collection informs targeting for EA jamming, and spectrum monitoring supports EP by detecting enemy jamming activity.

Corvus Intelligence engineers bespoke SIGINT platforms for defense agencies, intelligence directorates, and NATO-aligned forces – covering the full pipeline from RF collection through multi-source fusion and geospatial correlation to operational decision support. Services include SDR-based signal collection system design, SIGINT processing pipeline engineering, automated signal classification (ML-based), RF geolocation (TDOA/AoA/FDOA), ELINT/COMINT data management, and integration with C2 and battlefield data fusion platforms.