wifi-densepose/v2/crates/ruview-swarm/src/evals/gdop.rs

119 lines
4.1 KiB
Rust
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

//! Geometric Dilution of Precision (GDOP) for a constellation of observers.
//!
//! GDOP quantifies how observer geometry amplifies measurement error into
//! position-estimate error. Build the geometry matrix `H` of unit
//! line-of-sight (LOS) vectors from each observer to the target, form the
//! normal matrix `HᵀH`, invert it, and take `GDOP = sqrt(trace((HᵀH)⁻¹))`.
//!
//! For the 2-D (x, y) localization case `H` is `N×2` and `HᵀH` is `2×2`, so a
//! closed-form 2×2 inverse suffices (no linear-algebra dependency needed).
//!
//! Lower GDOP = better geometry: observers spread ~120° apart around the target
//! give low GDOP; (near-)collinear observers give a singular/ill-conditioned
//! `HᵀH` → GDOP → ∞.
use crate::types::Position3D;
/// Geometric Dilution of Precision (2-D) for `observers` viewing a `target`.
///
/// Lower = better geometry. A ~120° constellation → low GDOP; collinear → very
/// large (→∞). Returns `None` if fewer than two observers, if any observer is
/// coincident with the target (undefined LOS), or if the geometry is singular
/// / degenerate (collinear) so `HᵀH` is not invertible.
pub fn gdop(observers: &[Position3D], target: &Position3D) -> Option<f64> {
if observers.len() < 2 {
return None;
}
// Accumulate HᵀH directly (2×2 symmetric) from unit LOS vectors.
// Row i of H is the unit vector from target → observer i in (x, y).
let mut a = 0.0; // sum ux*ux
let mut b = 0.0; // sum ux*uy
let mut d = 0.0; // sum uy*uy
for obs in observers {
let dx = obs.x - target.x;
let dy = obs.y - target.y;
let range = (dx * dx + dy * dy).sqrt();
if range < 1e-9 {
// Observer on top of the target → LOS undefined.
return None;
}
let ux = dx / range;
let uy = dy / range;
a += ux * ux;
b += ux * uy;
d += uy * uy;
}
// Determinant of HᵀH = [[a, b], [b, d]].
let det = a * d - b * b;
if det.abs() < 1e-12 {
// Singular: observers are (near-)collinear with the target.
return None;
}
// (HᵀH)⁻¹ = 1/det * [[d, -b], [-b, a]]; trace = (d + a) / det.
let trace_inv = (a + d) / det;
if trace_inv <= 0.0 || !trace_inv.is_finite() {
return None;
}
Some(trace_inv.sqrt())
}
#[cfg(test)]
mod tests {
use super::*;
fn p(x: f64, y: f64) -> Position3D {
Position3D { x, y, z: 0.0 }
}
#[test]
fn test_triangle_lower_than_collinear() {
let target = p(0.0, 0.0);
// Three observers at 120° around the target, radius 10.
let r = 10.0;
let triangle = [
p(r * 0.0_f64.cos(), r * 0.0_f64.sin()),
p(
r * (2.0 * std::f64::consts::PI / 3.0).cos(),
r * (2.0 * std::f64::consts::PI / 3.0).sin(),
),
p(
r * (4.0 * std::f64::consts::PI / 3.0).cos(),
r * (4.0 * std::f64::consts::PI / 3.0).sin(),
),
];
// Three nearly-collinear observers (tiny y perturbation to stay invertible).
let near_collinear = [p(5.0, 0.01), p(10.0, 0.0), p(15.0, 0.01)];
let tri = gdop(&triangle, &target).expect("triangle finite GDOP");
let col = gdop(&near_collinear, &target).expect("near-collinear finite GDOP");
assert!(tri.is_finite(), "triangle GDOP must be finite: {tri}");
assert!(
tri < col,
"120° constellation should have lower GDOP than near-collinear: tri={tri}, col={col}"
);
}
#[test]
fn test_collinear_degenerate() {
let target = p(0.0, 0.0);
// Perfectly collinear observers along +x → singular HᵀH.
let collinear = [p(5.0, 0.0), p(10.0, 0.0), p(20.0, 0.0)];
let g = gdop(&collinear, &target);
assert!(
g.is_none() || g.unwrap() > 1e6,
"perfectly collinear geometry must be None or huge, got {g:?}"
);
}
#[test]
fn test_single_observer_none() {
let target = p(0.0, 0.0);
assert!(gdop(&[p(5.0, 5.0)], &target).is_none());
assert!(gdop(&[], &target).is_none());
}
}