This paper proposes efficient algorithms for accurate recovery of\ndirection-of-arrival (DoA) of sources from single-snapshot measurements using\ncompressed beamforming (CBF). In CBF, the conventional sensor array signal\nmodel is cast as an underdetermined complex-valued linear regression model and\nsparse signal recovery methods are used for solving the DoA finding problem. We\ndevelop a complex-valued pathwise weighted elastic net (c-PW-WEN) algorithm\nthat finds solutions at knots of penalty parameter values over a path (or grid)\nof EN tuning parameter values. c-PW-WEN also computes Lasso or weighted Lasso\nin its path. We then propose a sequential adaptive EN (SAEN) method that is\nbased on c-PW-WEN algorithm with adaptive weights that depend on the previous\nsolution. Extensive simulation studies illustrate that SAEN improves the\nprobability of exact recovery of true support compared to conventional sparse\nsignal recovery approaches such as Lasso, elastic net or orthogonal matching\npursuit in several challenging multiple target scenarios. The effectiveness of\nSAEN is more pronounced in the presence of high mutual coherence.\n