Neil Dhingra, BlackSky; Nicholas Geraci, BlackSky; Alexander Smith, BlackSky; Pauly Cabellon, BlackSky; Ken Carnemolla, BlackSky; Ethan Dederick, BlackSky; Alexa Erdogan, BlackSky; Katelyn Fobes, BlackSky; Chris Gates, BlackSky; Kyle Gulette, BlackSky; Alyssa Hollander, BlackSky; Deep Inamdar, BlackSky; Ian Jonesi, BlackSky; Jesse Miller, BlackSky; Andrew Steen, BlackSky; Jessica Turner, BlackSky
https://doi.org/10.64861/ZMFL6824
Keywords: Space-based, space-to-space, automated, low-latency, high-resolution, optimization
Abstract:
High-quality, timely data is necessary to maintain space safety through effective Space Situational/Domain Awareness (SSA/SDA) operations. High-resolution space-to-space electro-optical (EO) observations can make space object orientation, actions, and posture directly observable; however, the collection of such data is challenging. In this paper we present an automated system for on-demand SDA data collection built by adapting BlackSky’s existing commercial Gen-2 Earth-observation architecture. It provides an accessible operational interface and proven automated planning-to-delivery processes that produce timely, high-resolution imagery; it is already being applied for space-to-space imagery collection. We expand the constellation’s current automated planning processes to improve rates of successful space-to-space collection and ensure data collection and delivery with low-latency targets of under 1 hour. Moreover, this autonomous data ordering and dissemination architecture facilitates rapid decision-making, analyses, and insights, which are of increasing interest in crowded orbital regimes.
Large relative velocities and angular velocities, along with uncertain orbit determination, make pointing for space-to-space imagery collection more challenging than space-to-Earth imaging. Moreover, higher-resolution space-to-space imaging must necessarily occur at closer ranges so such imaging has a smaller camera field of view (FOV) in square kilometers. Because more precise targeting is required to capture space objects in this smaller frame, more accurate satellite and target states are required to reliably capture space-to-space images.
To improve the success rate of space-to-space imaging, we leverage the BlackSky constellation and mission planning architecture. First, we make the best use of available data: by computing pointing vectors in consideration of the uncertainty ellipsoid, we maximize probability of collect. Second, we make the best data available: by continuously creating and uplinking plans over frequently available communications links, we persistently update pointing data so that it reflects the latest orbit estimates.
We showcase order/planning/uplink/capture/downlink latencies to illustrate the responsiveness of the constellation and the timeliness of data. In operations, latencies are driven primarily by orbital geometry. The lowest latencies occur when satellites align such that orbital geometry contributes less to this latency; best-case statistics quantify the speed of constellation automation and responsiveness and do not represent typical operational measures. Given appropriate ordering timelines and orbital geometry, the BlackSky constellation can support an order-to-capture-to-downlink turnaround for a space-to-space imaging request in under an hour.
Finally, we provide sample images of the International Space Station (ISS), Chinese Space Station (CSS), and Chinese Shenlong space plane captured from BlackSky satellites. We provide capture range, resolution, and sun illumination angles for these images.
Date of Conference: September 15-18, 2026
Track: Space-Based Assets