Spatially Distributed Task-Oriented Compression for Multi-Emitter Localization and Characterization with Spectral Overlap
Researchers have developed a new framework for distributed compression that aids in identifying and characterizing radio frequency emitters. This approach uses spatially distributed receivers, each encoding observations into compact latent vectors. A central decoder then fuses these vectors to estimate emitter locations, bandwidths, and waveform families, demonstrating that highly compressed representations can still be useful for emitter counting and waveform estimation. AI