Robustness of 6D Spacecraft Pose Estimation

A research project with EPFL's Computer Vision Lab and the European Space Agency on the robustness of 6D spacecraft pose estimation. Orbital imagery is corrupted by optical and electronic artifacts (blooming, lens flare, dark-current noise, readout glitches) that quietly break the CNNs used for rendezvous and docking, so I built a physically grounded fault-injection pipeline to reproduce them on synthetic data.

Each fault is a parameterized module derived from its real physical cause, applied in the causal order of image formation: optical effects first, then sensor, then digital readout. Lens flare follows the Fresnel reflectance R = ((n1 − n2)/(n1 + n2))² at each air-glass interface; blooming models charge overflow once a pixel passes its well capacity Qsat = Cpixel · Vsat; dark current follows the thermal law Idark = I0 · exp(−Eg/kT); channel shift reproduces chromatic aberration through the dispersion n(λ) = n0 + A/λ². Gaussian noise and JPEG compression close the chain as residual transmission degradation.

To prove the artifacts are realistic rather than just plausible, I validated the blooming effect against real images from ESA's SPEED+ dataset with two complementary metrics: the Feature Quality Index (FQI), built from the Hamming distance between ORB descriptors of matched keypoints, and the Bhattacharyya distance between intensity histograms. On region-cropped comparisons, 90% of generated images passed both thresholds, with a mean FQI of 0.908 and histogram correlation of 0.996; a control against non-bloomed crops (correlation 0.054) confirmed the metrics were actually discriminative.