Research of new concept sonar-cognitive sonar

The performance of a sonar system is closely related to the marine environment and the target characteristics. When dealing with the echoes of a traditional active sonar system, the sonar designers often do not take into account the influence of the environmental information and prior knowledge perceived by sonar receivers, making it difficult to obtain desired processing results. Based on the basic principle and key technology of sonar, this paper proposed a cognition-based intelligent sonar system in theory—cognitive sonar. Cognitive sonar is capable of jointly optimizing the transmission waveform and receiver according to the changes of environment so that its detection and identification performance can be significantly improved.

[1]  I. Rhodes.  A tutorial introduction to estimation and filtering , 1971 .

[2]  Simon S. Haykin.  Adaptive radar: evolution to cognitive radar , 2003, IEEE International Symposium on Phased Array Systems and Technology, 2003..

[3]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[4]  Simon Haykin,et al.  Cognitive Dynamic Systems , 2007, 2007 4th International Conference on Electrical and Electronics Engineering.

[5]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[6]  Rolf Pfeifer,et al.  Understanding intelligence , 2020, Inequality by Design.

[7]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[8]  H. Riquimaroux,et al.  Adaptive SONAR sounds by echolocating bats , 2007, 2007 Symposium on Underwater Technology and Workshop on Scientific Use of Submarine Cables and Related Technologies.

[9]  Simon J. Godsill,et al.  On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..

[10]  S. Haykin,et al.  Cognitive radar: a way of the future , 2006, IEEE Signal Processing Magazine.

[11]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[12]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[13]  Genshe Chen,et al.  Cognitive MIMO sonar based robust target detection for harbor and maritime surveillance applications , 2008, 2009 IEEE Aerospace conference.

[14]  Simon Haykin.  Radar vision , 1990, IEEE International Conference on Radar.

[15]  J. Villares,et al.  The quadratic extended Kalman filter , 2004, Processing Workshop Proceedings, 2004 Sensor Array and Multichannel Signal.

[16]  Robert J. Urick,et al.  Principles of underwater sound , 1975 .

[17]  S. Shahabudeen,et al.  Recent advances in underwater acoustic communications & networking , 2008, OCEANS 2008.

[18]  Yingxu Wang.  Cognitive Informatics: Towards Future Generation Computers that Think and Feel , 2006, 2006 5th IEEE International Conference on Cognitive Informatics.

[19]  Wei Ping,et al.  A novel simplex unscented transform and filter , 2007, 2007 International Symposium on Communications and Information Technologies.

[20]  Simon Haykin.  Cognitive Radar Networks , 2006 .

[21]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[22]  Yingxu Wang,et al.  The Theoretical Framework of Cognitive Informatics , 2007, Int. J. Cogn. Informatics Nat. Intell..

[23]  Yingxu Wang,et al.  On Cognitive Informatics , 2002, Proceedings First IEEE International Conference on Cognitive Informatics.