Space debris is an increasing problem, with ca. 18,000 objects large enough to be tracked from the ground and conservative estimates of 670,000 small (1 – 10 cm) debris. Collisions have become a key issue in operation and decommissioning of spacecraft, adding costs and risks to space missions in all orbits, with the added threat of collisional cascading if some debris fields become dense enough. Their accurate mapping in 3-D, and their evolutionwith time, therefore become paramount, but in-flight approaches are constrained by limited fields of view and limited spatial resolutions. The shapes of debris are of interest as it might affect long-term movements, and thelarger ones will be of interest for retrieval missions and in the emerging field of debris exploitation. Leveraging on developments in acoustic imaging of complex subsea targets (e.g. Guigné, 1986; Blondel and Caiti, 2006; Guignéand Blondel, 2017), we propose an approach based on a collection of transducers acting as both EM transmitters and EM receivers, imaging debris fields in 4 dimensions (space and time) and using techniques such as beam steering and waveform inversion to retrieve as much information as possible on their shape and size distributions. Accurately located nanosatellites (as a constellation or in very small swarms) are positioned dynamically to image a particular volume in space. Individual sources are repeatedly actuated, with the other nanosatellites in the swarm acting as receivers. This gives access to a potentially large series of multistatic scattering measurements of any target. These are processed in real-time within each node, reducing the overall computation burden. The first result is a volumetric image of debris within the field of view aggregated from all nodes. Beam steering focuses on diffractions, creating virtual pencil beams from which high-resolution imagery can be formed, yielding information on sizes of individual targets and on shapes (via multi-angle diffraction patterns). This requires accurate positioning of the individual transducer nodes (nanosatellites), achievable using global positioning networks and EM time-of-flight checks between nodes. By varying the relative positions of nodes in the swarm, it is also possible to adapt the focusing toregions of particular interest. By using several nodes as transmitters, positive/destructive interference between sources can also be used to induce high signals in places of interest and null signals in other places (for example toavoid interference with or detection by instruments within the field of view). This enabling technology is adaptive, as the number of individual nodes can be adapted to suit operational requirements, from small groups to largerconstellations of nanosatellites. It is also dynamic as the virtual antenna they create can be changed very fast, either by repositioning them or only activating particular transmitters/receivers, making for responsive space missions. Onboard data processing allows fast, distributed processing, making individual nodes more affordable, and the modular aspect allow growing constellations or re-deploying subsets as mission profiles evolve. Beyond Earth orbit, thisapproach can also be used to map planetary environments and assist future asteroid mining operations
