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Solver

SolvFilter

Multi-target EKF prediction that survives at fleet scale.

At dim=140, standard scipy EKF predict fails entirely while UKF cost dominates the budget. SolvFilter is a dedicated Riccati prediction engine — 140/140 survival, 74× cheaper than UKF, best NEES consistency at scale. The tracking step behind counter-UAV kill chains and Assured Sensing fusion stacks.

Multi-target track covariance propagation surviving at high state dimension on embedded hardware.

Imagine yourself in these moments. Same product, different industries.

Counter-UAV program

The track picture that lies.

A radar update arrives every tenth of a second. The fusion node must propagate dozens of coupled target states and full covariance matrices before the next measurement — on hardware that also runs detection, classification, and weapon assignment. When the prediction integrator blows up or drifts NEES-inconsistent, the kill chain breaks upstream. The operator sees a ghost track or loses a real one.

UKF is accurate enough at moderate dimension. At dim=140 it becomes the cost and consistency bottleneck. Standard scipy EKF predict does not survive the validated slate at all.