Reconstructing constant point heat sources from few temperature sensors: sparse selection and spatial resolution
The framework reconstructs unknown constant heat sources from limited temperature sensor data by combining sparse dictionary selection with continuous constrained fitting. It uses methods like Orthogonal Matching Pursuit to select candidate source locations and then employs a bounded trust-region least-squares solver to recover the number and strengths of the sources, providing a local interpretation of which source information the observations support.