The problem of blind adaptive equalization of underwater single-input multiple-output (SIMO) acoustic channels was analyzed by using the linear prediction method.Minimum mean square error (MMSE) blind equalizers with ...The problem of blind adaptive equalization of underwater single-input multiple-output (SIMO) acoustic channels was analyzed by using the linear prediction method.Minimum mean square error (MMSE) blind equalizers with arbitrary delay were described on a basis of channel identification.Two methods for calculating linear MMSE equalizers were proposed.One was based on full channel identification and realized using RLS adaptive algorithms,and the other was based on the zero-delay MMSE equalizer and realized using LMS and RLS adaptive algorithms,respectively.Performance of the three proposed algorithms and comparison with two existing zero-forcing (ZF) equalization algorithms were investigated by simulations utilizing two underwater acoustic channels.The results show that the proposed algorithms are robust enough to channel order mismatch.They have almost the same performance as the corresponding ZF algorithms under a high signal-to-noise (SNR) ratio and better performance under a low SNR.展开更多
Sound propagation in a deep ocean two-axis underwater channel is often complex and difficult to simulate between surface channel and sound fixing and ranging (SOFAR) channel. The beam-displacement ray-mode (BDRM) theo...Sound propagation in a deep ocean two-axis underwater channel is often complex and difficult to simulate between surface channel and sound fixing and ranging (SOFAR) channel. The beam-displacement ray-mode (BDRM) theory is a normal mode method for propagation modeling in horizontally stratified shallow water. An improved method for computing the upper boundary reflection coefficient in the BDRM is proposed and applied to calculate the acoustic fields of a two-axis underwater channel. Transmission losses in the two-axis underwater channel are calculated in the new BDRM. The corresponding results are in good agreement with those from the Kraken code, and furthermore the computed speed of the new BDRM excels the other methods.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No.60372086the Foundation for the Author of National Excellent Doctoral Dissertation of China under Grant No.200753
文摘The problem of blind adaptive equalization of underwater single-input multiple-output (SIMO) acoustic channels was analyzed by using the linear prediction method.Minimum mean square error (MMSE) blind equalizers with arbitrary delay were described on a basis of channel identification.Two methods for calculating linear MMSE equalizers were proposed.One was based on full channel identification and realized using RLS adaptive algorithms,and the other was based on the zero-delay MMSE equalizer and realized using LMS and RLS adaptive algorithms,respectively.Performance of the three proposed algorithms and comparison with two existing zero-forcing (ZF) equalization algorithms were investigated by simulations utilizing two underwater acoustic channels.The results show that the proposed algorithms are robust enough to channel order mismatch.They have almost the same performance as the corresponding ZF algorithms under a high signal-to-noise (SNR) ratio and better performance under a low SNR.
基金This project was supported by National Defense Research Found (No. 9140A03050206JB1501)
文摘Sound propagation in a deep ocean two-axis underwater channel is often complex and difficult to simulate between surface channel and sound fixing and ranging (SOFAR) channel. The beam-displacement ray-mode (BDRM) theory is a normal mode method for propagation modeling in horizontally stratified shallow water. An improved method for computing the upper boundary reflection coefficient in the BDRM is proposed and applied to calculate the acoustic fields of a two-axis underwater channel. Transmission losses in the two-axis underwater channel are calculated in the new BDRM. The corresponding results are in good agreement with those from the Kraken code, and furthermore the computed speed of the new BDRM excels the other methods.
