In this paper, we study a problem encountered during our ongoing efforts to locate radio-tagged fish aggregations with robots. The problem lies at the intersection of search-based methods whose objective is to detect a target, and active target localization methods whose objective is to precisely localize a target given its initial estimate. Real-world sensing constraints such as limited and unknown range, large measurement time, and ambiguity in bearing measurements make it imperative to have an intermediate initialization phase to transition from search to localization.We present a local search strategy aimed at reliably initializing an estimate for a single target based on observations from field experiments.We then extend this strategy to initialize multiple targets, exploiting the proximity of nearby aggregated tagged fish to decrease the cost of initialization per target. We evaluate the performance of our algorithm through simulations and demonstrate its utility through a field experiment where the robot successfully detects, initializes and then localizes nearby targets.