Startup CubeSats: learn from successive flight batches

TASA’s startup CubeSat work supports domestic industrial teams developing spacecraft and payloads with potential applications. The first phase included TORO, associated with visible and near-infrared remote sensing, and Nightjar, associated with communications experiments. TASA records their launches in August 2024. They are separate spacecraft with different payload — open definition goals, not two names for the same instrument.

The broader work includes system integration, operations, ground reception and application development. A company can learn from the interaction among these tasks rather than treating a payload as an isolated box. The satellite bus must support it, the ground system must receive its output, and users must understand what the result means. Commercial potential is a motivation; it is not itself proof of a dependable service.

TASA’s March 31, 2026 announcement records the launch and initial contacts of Bellbird-2, Black Kite-2 and Albatross-2 on the preceding day. It describes successive batches as a way to improve designs and accumulate verification experience. Those dated milestones supersede older future-tense descriptions of the same batch. They do not establish that every planned satellite or intersatellite feature is already operating.

A first contact shows that a communications path worked sufficiently to receive a signal or data. Payload commissioning — open definition, performance verification and sustained service still need evidence. When comparing batches, record which hardware or software changed and which conditions were tested. Otherwise an apparent improvement could come from a different ground station, a different measurement method or an easier observing situation.

Compare flight batches with usable evidence

Imagine two fictional payload trials. Trial A returns 90 usable images from 100 attempts. Trial B returns 95 from 125 attempts. B returns more images in total, but its usable fraction — open definition is 76 percent, compared with A’s 90 percent. Neither number alone settles which system is better: the goals, conditions, image quality and reasons for unsuccessful attempts matter.

The example teaches a useful reporting habit for an iterative program. Preserve attempted and successful counts, explain changes, and compare like with like before announcing progress. A later spacecraft may offer new functions while still needing refinement in another area. Successive CubeSat missions are valuable because they create opportunities for that learning, not because a numbered successor is automatically superior in every possible measure.