Long-Range Strike Prophet (LRSP)

AI-Powered Bomber Fleet Trajectory Prediction

97.5% WITHIN 25 KM | 93.4% MEAN CONFIDENCE | 4.9 KM MEAN PREDICTION DISTANCE

Background:

Tracking bomber fleets across millions of square kilometers means analysts have to decide where to point limited collection assets hours before a satellite pass. Get it wrong and you waste the pass, the time, and the money. The published literature on trajectory prediction is built around civilian air traffic with dense ADS-B feeds. Military bombers don't broadcast. They fly variable profiles, coordinate in formation, and deliberately avoid predictability. We needed a different approach.

Our Solution: Quantum-Inspired Temporal Attention Network

LRSP fuses five parallel feature streams through cross-stream multi-head attention: latent state-space encodings, kinematic sequences, per aircraft identity embeddings, categorical context vectors, and hierarchical H3 spatial embeddings. Every stream attends to every other, so the model captures dependencies other architectures miss.

The quantum-inspired superposition layers at the core encode kinematic data into complex-valued representations with separate amplitude and phase components. In practice, this means the system can distinguish an H-6K on a strike approach from an H-6J in formation transit even when speed and heading look identical. Phase interference between aircraft in the same formation amplifies correlated behavior and suppresses noise, so we get fleet level prediction rather than treating each air frame independently.

Why This Matters

  • Turns reactive tracking into proactive asset positioning

  • 97.5% of predictions land within 25 km, inside a single satellite swath

  • Gives analysts hours of lead time for collection planning

Test Results: H-6K Bomber Fleet

Against 42 H-6K aircraft in synthetic open-source testing, LRSP achieved 93.4% mean confidence and a mean prediction distance of 4.9 km. Individual errors ranged from 3.42 to 6.24 km, all above 94.% confidence. All 42 aircraft processed simultaneously with stable 8-step prediction windows across the fleet.

LRSP was built on 1,180,719 synthetic trajectory points across 935 aircraft, 12 platform types, and 22 months of simulated operations, calibrated against open-source intelligence to mirror real operational patterns across the Western Pacific theater. Operational validation with real-world data is required before deployment. Use our contact form to get in touch.