Speech　enhancement　is　an　indispensable　technology　in　the　field　of　speech　interaction.　With　the　development　of　microphone　array　signal　processing　technology　and　deep　learning,　the　beamforming　combined　with　neural　network　has　provided　a　more　diverse　solution　for　this　field.　In　this　paper,　a　multi-channel　speech　enhancement　method　is　proposed,　which　combines　beamforming　and　post-filtering　based　on　neural　network.　The　spatial　features　and　phase　information　of　target　speech　are　incorporated　into　the　beamforming　by　neural　network,　and　a　neural　network　based　single-channel　post-filtering　with　the　phase　correction　is　further　combined　to　improve　the　performance.　The　experiments　at　different　signal-to-noise　ratio　(SNR)　levels　confirmed　that　the　proposed　method　results　in　an　obvious　improvement　on　speech　quality　and　intelligibility　compared　to　the　reference　methods.