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Solver

SolvFilter

Multi-target EKF prediction — UKF alternative at fleet scale.

At dim=140, UKF is computationally infeasible (17–74× slower or times out). SolvFilter is a bounded radar SKU: deploy survival validated (360/360), fast path at dim<50, primary pitch vs UKF at dim≥70. Honest ~3× scipy_ekf overhead in calm noise; sparse/dropout parity only. Counter-UAV 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 — often timing out entirely. SolvFilter's validated pitch is as a UKF alternative at scale, not a drop-in replacement for every scipy EKF deployment.