dsfb

Drift-Slew Fusion Bootstrap (DSFB): a trust-adaptive nonlinear state estimator for tracking position (phi), drift (omega), and slew (alpha) across multiple measurement channels.

Install

From crates.io:

[dependencies]
dsfb = "0.1.1"

To track unreleased changes, use Git:

[dependencies]
dsfb = { git = "https://github.com/infinityabundance/dsfb", branch = "main" }

Quick Start

use dsfb::{DsfbObserver, DsfbParams, DsfbState};

let params = DsfbParams::new(0.5, 0.1, 0.01, 0.95, 0.1);
let mut observer = DsfbObserver::new(params, 2);
observer.init(DsfbState::new(0.0, 0.5, 0.0));

let dt = 0.01;
let measurements = [1.0, 1.05];
let state = observer.step(&measurements, dt);

println!("phi={}, omega={}, alpha={}", state.phi, state.omega, state.alpha);

Simulation Example

From workspace root:

cargo run --release -p dsfb --example drift_impulse

Outputs:

• output-dsfb/<timestamp>/sim-dsfb.csv
• metrics summary in console

Repository

Full documentation, notebooks, and verification scripts: https://github.com/infinityabundance/dsfb

Separate Crate In This Repo

For the separate synthetic benchmarking package used for fusion diagnostics paper workflows, see:

• crates/dsfb-fusion-bench
• crates/dsfb-fusion-bench/README.md

Citation

de Beer, R. (2026).
Slew-Aware Trust-Adaptive Nonlinear State Estimation for Oscillatory Systems With Drift and Corruption (v1.0).
Zenodo. https://doi.org/10.5281/zenodo.18642887