For　the　traditional　processing　tasks　of　underwater　data　analysis　system,　including　finite　impulse　response　filter　banks,　fast　Fourier　transform,　conventional　beamforming　and　target　tracking,　the　algorithm　flow　is　relatively　steady　with　little　alternative　control,　which　is　to　say　that　it　is　highly　parallel.　Besides　that,　the　processing　tasks　need　to　deal　with　enormous　data,　which　means　great　computational　burden　and　high　arithmetic　intensity.　But　fortunately　is　that　they　have　fewer　requirements　in　computational　precision.　According　to　the　significant　features　above-mentioned,　it　is　convinced　that　an　innovational　data　analysis　system　processing　framework　for　underwater　target　detection　would　come　into　being,　with　sufficient　capacity　utilization　of　one　type　of　processing　devices,　the　programmable　graphic　processor　unit　(GPU).　For　the　past　few　years,　the　GPU　has　developed　into　one　type　of　devices　with　more　generalized　processing　capability,　which　used　to　be　a　specialized　device　for　graphic　processing.　Possessing　the　characteristics　of　many-core　and　high　bandwidth,　the　modern　GPU　is　able　to　parallelly　operate　tens　of　thousands　of　light-weighted　threads,　which　implies　enormous　processing　capacity.　From　the　above　we　can　see　that　the　GPU　is　especially　appropriate　for　handling　issues　of　great　computational　burden　and　high　arithmetic　intensity.　This　paper　adopts　an　innovative　data　analysis　system　processing　framework　for　underwater　target　detection,　comprehensively　utilizing　CPU　and　GPU,　and　implements　the　real-time　signal　analysis　and　processing　for　160-channel　data　recorded　from　one　towed　array　in　marine　experiment,　demonstrating　the　feasibility　of　the　framework　in　underwater　target　detection　and　tracking.　©　2016　IEEE.