This chapter focuses on the underdetermined mixing matrix estimation problem for sufficiently sparse source signals. It first investigates clustering-based underdetermined mixing matrix estimation, including the k-means clustering algorithm, the fuzzy C-means clustering algorithm, and an improved k-means clustering algorithm. Then, two mixing matrix estimation algorithms with good anti-noise ability are studied, namely underdetermined mixing matrix estimation algorithm based on similarity detection and that based on bullseye retrieval.