3-Target Coordinated Turn Tracking
ADVANTAGES1 · dim 21SolvSRK wins. At the comparison noise level, SolvSRK beats the best baseline by at least 10 percentage points of survival, or by at least 0.05 balanced score when survival is tied. Use SolvSRK for this class of problem. All verdicts →
3 independent targets with coordinated-turn dynamics (7 states each: x, y, z, vx, vy, vz, a_mag). Turn rates 0.1, 0.3, 0.05 rad/s. Acceleration decays with tau_a=5s.
Problem definition
Bar-Shalom et al., 'Estimation with Applications to Tracking and Navigation' (2001), Ch. 11
Canonical RHS excerpt from the registered callable used for this benchmark cell. Expand it to verify the state equations; it is not a standalone runnable fixture.
Show canonical RHS excerpt
def rhs(t, y):
d = np.empty(dim)
for i in range(n_targets):
base = 7 * i
x = y[base]
yy = y[base + 1]
z = y[base + 2]
vx = y[base + 3]
vy = y[base + 4]
vz = y[base + 5]
a_m = y[base + 6]
v_mag = np.sqrt(vx * vx + vy * vy + vz * vz)
v_safe = max(v_mag, _VEL_FLOOR)
omega = omegas_arr[i]
d[base] = vx
d[base + 1] = vy
d[base + 2] = vz
d[base + 3] = -omega * vy + a_m * vx / v_safe
d[base + 4] = omega * vx + a_m * vy / v_safe
d[base + 5] = a_m * vz / v_safe
d[base + 6] = -a_m * inv_tau_a
return d- Parameters
- _VEL_FLOOR = 1e-06
- dim = 21
- inv_tau_a = 0.2
- n_targets = 3
- omegas_arr = [0.1, 0.3, 0.05]
- Initial condition
- y(0) = [1000, 0, 500, 50, 100, 0, …] [shape=(21,), min=-500, max=2000]
- Horizon
- t ∈ [0, 60]
Canonical RHS excerpt captured from the same registered callable used for the published benchmark. Frozen closure values are summarized below; helper imports and solver settings are intentionally omitted.
Fingerprint
Spread: extreme
Default noise: low
Recommendation snapshot
Clean best: SciPy Radau
Noisy best: SolvSRK
Coverage
14 solver arms · clean + 5 noise levels
Ranked on survival, precision, and speed
Versions & freeze
Methodology →- Freeze
- 2026-08-13
- libsolvsrk
- 2.3.0
- SciPy
- 1.14
- SUNDIALS
- CVODE (bundled backend)
20 seeds/cell default · 14 arms · TRL 4–5 · simulation-lab validated · this page: 3-Target Coordinated Turn Tracking (3-target-coordinated-turn-tracking)
Governed SolvTune benchmark freeze; per-arm medians only. RHS definitions and raw trial rows are not published.
Self-reported by Resonix Labs · not independently verified
Results matrix
Pick an objective and a noise level to rank all arms on survival, median SCD, median nfev, and median wall time. Medians across seeds.
Objective
Best overall trade-off of survival, precision, and speed.
Noise level
| # | Solver | Survival | SCD | nfev | Wall | Score |
|---|---|---|---|---|---|---|
| 1 | SciPy RadauSciPy | 100% | 10.4 | 3,780 | 95 ms | 0.868 |
| 2 | Vern9external | 100% | 10.4 | 642 | 3.81 s | 0.866 |
| 3 | Vern7external | 100% | 10.2 | 762 | 3.99 s | 0.863 |
| 4 | SolvSRK | 100% | 10.2 | 2,574 | 60 ms | 0.862 |
| 5 | Tsit5external | 100% | 8.8 | 1,200 | 862 ms | 0.828 |
| 6 | SciPy DOP853SciPy | 100% | 8.5 | 374 | 4 ms | 0.821 |
| 7 | SciPy RK45SciPy | 100% | 8.3 | 1,286 | 15 ms | 0.816 |
| 8 | CVODE Adamsexternal | 100% | 8.2 | 236 | 10 ms | 0.815 |
| 9 | SciPy LSODASciPy | 100% | 8.2 | 521 | 5 ms | 0.814 |
| 10 | FBDFexternal | 100% | 7.9 | 761 | 4.77 s | 0.808 |
| 11 | SciPy RK23SciPy | 100% | 7.4 | 8,255 | 111 ms | 0.795 |
| 12 | SciPy BDFSciPy | 100% | 6.8 | 898 | 35 ms | 0.780 |
| 13 | CVODE BDFexternal | 100% | 6.6 | 568 | 14 ms | 0.776 |
| 14 | TRBDF2external | 100% | 4.4 | 11,024 | 5.65 s | 0.724 |
At Clean, best balanced arm is SciPy Radau · SolvSRK survival 100%, SCD 10.2.
Values are medians across seeds, measured by Resonix Labs on Resonix hardware and not independently verified; nfev and wall are on reference lab hardware (indicative). Under injected noise only SolvSRK and the SciPy arms are run. How we measure accuracy → · Verification status →
Cite this page
Replace the access date. Pin the freeze ID and library versions when comparing against a later export. Cite it as what it is - a self-reported vendor benchmark, not an independently verified result. The note field says so; please keep it.
@misc{resonix_evidence_3_target_coordinated_turn_tracking_2026,
title = {Resonix Evidence Portal: 3-Target Coordinated Turn Tracking},
author = {{Resonix Labs (Canada) Inc.}},
year = {2026},
howpublished = {\url{https://resonixusa.com/evidence/problems/3-target-coordinated-turn-tracking}},
note = {Self-reported vendor benchmark; internally generated by Resonix Labs and not independently verified. Accessed YYYY-MM-DD. Freeze 2026-08-13; libsolvsrk 2.3.0; SciPy 1.14.}
}Related
TRL 4–5 · simulation-lab validated · 398 problems · 14 solver arms · clean + 5 noise levels
Freeze: 2026-08-13 · scipy 1.14 · libsolvsrk 2.3.0 · Methodology
Self-reported by Resonix Labs · not independently verified · Verification status