Spacecraft Angular Rate Estimation via Event-Based Camera Sensing

TL;DR

Gyroscope drift and failure risks motivate alternative angular-rate sensing for spacecraft. The paper develops an event-based vision approach that uses the apparent motion of stars to estimate the spacecraft's angular rates, solving a least-squares problem mapping image-plane motion to p, q, r via a motion-field model derived from contrast-maximized event streams. A dual orthogonal event-camera configuration substantially improves observability and reduces estimation error, with a reported RMS of 0.0275 deg/s, and a sensitivity analysis showing robustness under realistic noise. These findings indicate event-based sensing can complement or substitute traditional rate sensors, particularly during fast maneuvers or in high-dynamic-range scenarios.

Abstract

This paper presents a method for determining spacecraft angular rates using event-based camera sensing. This is achieved by analyzing the temporal distribution of brightness events triggered by the apparent motion of stars. The location and polarity of the events are used to infer the apparent motion field of the stars, which is, in turn, employed to estimate the observer angular velocity in the camera frame. This can be converted to the spacecraft angular rates provided an attitude reference. The method is validated through numerical simulation for a synthetic dataset of event streams generated on random spacecraft pointing and rates conditions. The accuracy of the method is assessed, demonstrating its potential to complement or replace conventional rate sensors in spacecraft systems using event camera sensing.

Figures (8)

• Figure 1: Visualization of the inertial reference frame [$\hat{\bm{e}}_1$, $\hat{\bm{e}}_2$, $\hat{\bm{e}}_3$], camera reference frame [$\hat{\bm{c}}_1$, $\hat{\bm{c}}_2$, $\hat{\bm{c}}_3$], and projection of a star onto the focal plane of a pinhole camera. For simplicity, the inertial and camera reference frames share the same origin owing to the negligible parallax of stars.
• Figure 2: Apparent motion of stars on the focal plane of (a) a frame-based camera and (b) an event-based camera. The red and blue pixels denote positive and negative event polarity.
• Figure 3: Representation of a stream of events: (a) events triggered by the apparent motion of stars, which are shown as dotted lines in the (x, y, t) space; (b) projection of events on the (x, y) plane; (c) projection of events on the (x, t) plane; (d) projection of events on the (y, t) plane. The projections of events on the (x, y) plane reveal the apparent motion of stars, while the projections on the (x, t) and (y, t) planes highlights the apparent motion field components u and v, respectively.
• Figure 4: Contrast maximization algorithm: (a) Input unwarped events stream represented on the (x, y) plane; (b) Output warped event stream on the (x, y) plane according to the best fit velocity $\bm{v}^*$ = [$u$, $v$].
• Figure 5: Block diagram of the simulation workflow for event-based angular rate estimation.