Sparse-signal processing on information-based range grid

Radar obtains its parameters on an estimation grid whose cell size is related to resolution of underlying radar processing. Existing radar exploits a regular grid (i.e. constant resolution) although the resolution changes with stronger echoes at shorter ranges.We compute radar resolution from the intrinsic geometrical structure of data models that is characterized by the Fisher information. Based on this information-geometry approach, we create an estimation grid whose cells have a constant information distance. In addition, we explore how such an irregular estimation grid can suit radar processing in practice, and propose applying the information-based grid with the sparse-signal processing from compressive sensing. This novel radar processing is applied in an one-dimensional case of range estimation, with emphasis on the grid effects to the sensing incoherence. Results reveal the new flexibility in radar design.