TY - GEN
T1 - MIMO Sonar DOA Estimation Based on Improved Transmitting Diversity Smoothing (TDS)
AU - Fan, Kuan
AU - Sun, Chao
AU - Liu, Xionghou
AU - Jiang, Guangyu
AU - Lei, Zhixiong
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/1/7
Y1 - 2019/1/7
N2 - A multiple-input multiple-output (MIMO) sonar has an effect of transmission diversity smoothing (TDS), which is able to 'de-correlate' the echoes of multiple targets automatically. Accordingly, a series of high-resolution DOA estimation methods can be adopted directly without using conventional spatial smoothing, and hence avoiding the losses of array aperture and degree of freedom. However, the performance of TDS-based DOA estimation methods would degrade seriously in low signal-to-noise ratio (SNR) condition. In this paper, to solve the problem we proposed a new MIMO sonar DOA estimation method based on improved TDS. In order to improve the SNR of data used for DOA estimation, two steps are used. Firstly, we use the sum of all transmitting signals to matched filter echoes at the receiving hydrophone array. And secondly, we truncate outputs of matched filters around the zero-delay point. Synchronously, the number of truncated snapshots is carefully considered to retain the TDS effect. After the two-step processing, the TDS effect is still available and SNR of the data to be processed is remarkably improved. And thus, the performance of the TDS-based DOA estimation method is effectively improved. Numerical simulations show that the proposed method could significantly improve the performance of TDS-based DOA estimation methods in low SNR environment.
AB - A multiple-input multiple-output (MIMO) sonar has an effect of transmission diversity smoothing (TDS), which is able to 'de-correlate' the echoes of multiple targets automatically. Accordingly, a series of high-resolution DOA estimation methods can be adopted directly without using conventional spatial smoothing, and hence avoiding the losses of array aperture and degree of freedom. However, the performance of TDS-based DOA estimation methods would degrade seriously in low signal-to-noise ratio (SNR) condition. In this paper, to solve the problem we proposed a new MIMO sonar DOA estimation method based on improved TDS. In order to improve the SNR of data used for DOA estimation, two steps are used. Firstly, we use the sum of all transmitting signals to matched filter echoes at the receiving hydrophone array. And secondly, we truncate outputs of matched filters around the zero-delay point. Synchronously, the number of truncated snapshots is carefully considered to retain the TDS effect. After the two-step processing, the TDS effect is still available and SNR of the data to be processed is remarkably improved. And thus, the performance of the TDS-based DOA estimation method is effectively improved. Numerical simulations show that the proposed method could significantly improve the performance of TDS-based DOA estimation methods in low SNR environment.
KW - DOA estimation
KW - Matched filter
KW - Multiple-input multiple-output (MIMO) sonar
KW - Transmission diversity smoothing (TDS)
KW - Underwater acoustics
UR - http://www.scopus.com/inward/record.url?scp=85061802428&partnerID=8YFLogxK
U2 - 10.1109/OCEANS.2018.8604737
DO - 10.1109/OCEANS.2018.8604737
M3 - 会议稿件
AN - SCOPUS:85061802428
T3 - OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018
BT - OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - OCEANS 2018 MTS/IEEE Charleston, OCEANS 2018
Y2 - 22 October 2018 through 25 October 2018
ER -