The bistatic sonar which contains separated active and passive sonar has both the advantages of them, It has great potential advantages in anti-stealth and anti-underwater acoustic countermeasure. But detection of the target echo is often heavily influenced by the active sonar direct wave interferences,
due to that the signal-to-interference ratio(SlR) is very low and the direct wave interference and the target echo arc highly correlated.To improve detection of the target echo,it is of crucial importance to suppress the active sonar direct wave interference in bistatic sonar system.This study focuses on a vector
bistatic sonar model in which the passive sonar is vector.The following assumptions arc made; 1)the active sonar direct wave interference and the target echo differs from each other only by time of arrival and amplitude; 2) the active sonar direct wave and the target echo arc partly overlapped in time-domain;
3) there is only one vector hydrophone in the passive sonar. For suppressing the direct wave interference and achieving the purpose of the detection of weak target echo under these assumptions,a method based on time-domain blocked adaptive active sonar direct wave interference suppression is proposed.This
method combines the principal component inverse (PCl) and recursive least square (RLS) algorithm.To distinguish the direct wave interference from the target echo plus marine environmental noise, it is important to choose a metric firstly.The direct wave interference and the target echo are highly correlated and they arc partly overlapped in time-domain, so it is hard to distinguish them in frequency or time domain. Another important difference between the direct wave interference and the target echo is power. As the power of the direct wave interference is much greater than the sum of the target echo and the marine environmental noise,it can be chosen as a metric. In bistatic sonar, the signal type and parameters of the active sonar transmitted signals arc all known in advance. So with the priori knowledge of the transmitted signal,the direct wave interference is firstly extracted from the received signal by PCl algorithm which can be realized via singular value decomposition(SVD) of the generating forward matnx.The forward matrix is generated with the receipt signal blocked in time-domain.The rank of the
generating forward matrix to different transmitted signals is analyzed. Having extracted the estimated direct wave interence,it is then taken as a reference signal for RLS algorithm to remove the direct wave interference. As the adaptive wiener filter of RLS algorithm is used,it can track the distortion of
amplitude dynamically over time. Both computer simulations and lake experiments carried out in a lake in eastern China are given to verify the validity and feasibility of the algorithm.The results show that this method is efficient for suppressing the direct wave and tolerahle of local distortion of direct wave.
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References
[1]Chen H,Su H J. A new approach to estimate DOA in presence of strong jamming/signal sup pression. Acta Electronica Sinica, 2006,3:530~534.
[2]Zou J W,Sun D J. MUSIC Algorithm of beam null forming on linear array of bistatic sonar. Acta Armamentar II,2010,3:364一368.
[3]Anderson V C, Rudnick P. Rejection of a co herent arrival at an array. The Journal of the A coustical Society of America 1969.2:406~410.
[4]Gao S C, Huang C L, Su Y. Direct wave sup- pression based on adaptive interference canceling method. Signal Processing, 2004,6:565一57.
[5]Sorouchyari E. Blind separation of sources sta bility analysis. Signal Processing 1991,24(1): 21一29.
[6]Lee T W Bell A J,Orglmcister R. Blind sonrce separation of real world signals, Interna tional Symposium on Neural Networks.1997.2129~2134.
[7]Belouchrani A,Meriam K A,Cardoso J F, et al. A blind source separation technique using second-order statistics. IEEE Transactions on
Signal Processing,1997,45(2):434~444.
[8]Zou J W,Sun D J,Shi J J,et al. Vector sensor hased reduction of direct wave interference for bistatic sonar systems.High Technology Let-ters,2010,11:1138~1141.
[9] Ginolhac G, Jourdain G. "Principal Component Inverse" algorithm for detection in the presence of reverberation, IEEE Journal of Oceanic Engi- neering. 2002 .2 .310-321
[10]Kumaresan K,Kirstcins 1 P, Kirsteins I. Data adaptive signal estimation by singular value de- composition of a data matrix. Proceedings of
IEEE,1982,6:684一685.
[11]Palka T A,tufts D W.Reverberation charac- tcrization and suppression by means of principal components.Oceans’98,Nice, France, 1998.
[12]Yang D, Yin Y L,Zhu M Y,et al. A corner detection method based on strong noise adapta- tion. Journal of Nanjing University(Natural
Sciences), 2008, 2(44); 140-147.杨栋,尹义龙,朱明英等.一种大噪声自适应的角点检测技术.南京大学学报(自然科学),2008, 2 (44):140一147).
[13]Babadi B, Kalouptsidis N Tarokh V.SPARLS; The sparse RLS algorithm. IEEE Transactions on Signal Processing, 2010,8:4013~4025.
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Footnotes
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