The Seonggil-Riemann Tracking Engine: Algebraic Phase-Locking of Evasive Kinematics via Rough Operator Algebra
Lee Seonggil · Zenodo (CERN European Organization for Nuclear Research) · 2026
For decades, modern defense and aerospace tracking architectures have relied on probabilistic paradigms—such as the Interacting Multiple Model (IMM), Unscented Kalman Filters (UKF), and Particle Filters. These frameworks suffer from a fatalgeometric illusion: they treat extreme, non-linear evasive kinematics as commutative stochastic processes bounded by Gaussian noise. In this paper, we completely shatter this probabilistic tracking paradigm. By applying Rough Operator Algebra (ROA) and Seonggil Matrix Theory (SMT), we introduce the Seonggil-Riemann Tracking Engine. We elevate the target trajectory into a hyper-complex eigen projection operator X(t) on the rough phase space R^1/2. Unpredictable evasion is algebraically redefined as definitive non-commutative homological friction governed by the Seonggil Torsion Tensor T_0x8A2C. At the critical roughness exponent α = 1/2, a Topological Fractal Brake strictly bounds the error cascade into an exponential decay trajectory. Finally, through Spherical Holographic Information Dynamics (SHID), the unmapped evasive energy is dissipated as thermal entropy,while the target’s absolute true coordinate is definitively phase-locked onto the 3D radar boundary. This framework replaces statistical guessing with absolute algebraic certainty.