Insense is an optimization algorithm to select sensors that take linear measurements from a structured (e.g., sparse or near-sparse) signal. Insense finds a small number of the rows of a potenitally large matrix that have small mutual coherence across their columns. The problem is NP-Hard in general. Insense relaxes the objective into a non-convex optimization program and solves it using an itereative-projection method.
Mathematical details of Insense are provided in the manuscrit in the manuscript "Insense: Incoherent sensor selection for sparse signals".