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SCIENTIA SINICA Informationis, Volume 46 , Issue 8 : 1053-1085(2016) https://doi.org/10.1360/N112016-00064

Marine information gathering, transmission, processing, and \\fusion: current status and future trends

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  • ReceivedMar 26, 2016
  • AcceptedJun 1, 2016

Abstract


Funded by

国家自然科学基金(61531017)

国家自然科学基金(61431020)

国家自然科学基金(61431005)

国家自然科学基金(61531015)

国家自然科学基金(61531018)

国家自然科学基金(41376104)


References

[1] Zhang R H. The development trend of underwater acoustic technology is osculatory combination of underwater acoustic physics, signal processing and ocean environment. Appl Acoust, 2006, 25: 325-327 [张仁和. 水声物理、信号处理与海洋环境紧密结合是水声技术发展的趋势. 应用声学, 2006, 25: 325-327]. Google Scholar

[2] Scharf L L. Statistical Signal Processing: Detection, Estimation, and Time Series Analysis. Upper Saddle River: Prentice Hall, 1991. Google Scholar

[3] Kay S. Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory. Upper Saddle River: Prentice Hall, 1991. Google Scholar

[4] Poor H V, Thomas J B. Advances in Statistical Signal Processing. Stamford: JAI Press Inc, 1993. Google Scholar

[5] Scharf L L. On Unbiasedness and Invariance in Signal Detection Theory. Dissertation for Ph.D. Degree. Washington D C: University of Washington, 1969. Google Scholar

[6] Shannon C E. A mathematical theory of communication. Bell Sys Tech J, 1948, 27: 379-423 CrossRef Google Scholar

[7] Jaynes E T. Information theory and statistical mechanics. Phys Rev, 1957, 106: 620-630 CrossRef Google Scholar

[8] Verdu S. Guest editorial. IEEE Trans Inf Theory, 1998, 44: 2042-2044 CrossRef Google Scholar

[9] Verdu S. Fifty years of Shannon theory. IEEE Trans Inf Theory, 1998, 44: 2057-2078 CrossRef Google Scholar

[10] Wiener N. Selected Papers of Norbert Wiener. Cambridge: MIT Press & SIAM, 1964. Google Scholar

[11] Kalman R E, Bucy R S. New results in linear filtering and prediction theory. J Basic Eng, 1961, 83: 95-108 CrossRef Google Scholar

[12] Candy J V. Bayesian Signal Processing: Classical, Modern, and Particle Filtering Methods. Wiley Inter Science, 2009. Google Scholar

[13] Fisher R A. Theory of statistical estimation. Proc Cambridge Phil Soc, 1925, 22: 700-725 CrossRef Google Scholar

[14] Kailath T, Poor H V. Detection of stochastic processes. IEEE Trans Inf Theory, 1998, 44: 2230-2259 CrossRef Google Scholar

[15] Helmberg G. Introduction to Spectral Theory in Hilbert Space. New York: Dover Publications, 2008. Google Scholar

[16] Synowiec J A. Introduction to Hilbert spaces with applications. SIAM Rev, 1993, 35: 341-342 CrossRef Google Scholar

[17] Colton D, Kress R. Inverse acoustic and electromagnetic scattering theory. Appl Math Sci, 1998, 93: 67-110. Google Scholar

[18] Kailath T. RKHS approach to detection and estimation problems I: deterministic signals in Gaussian noise. IEEE Trans Inf Theory, 1971, 17: 530-549 CrossRef Google Scholar

[19] O'Sullivan J A, Blahut R E, Snyder D L. Information-theoretic image formation. IEEE Trans Inf Theory, 1998, 44: 2049-2123. Google Scholar

[20] Chen S, Lan Y. Broadband flextensional transducer with major axis lengthened. Acta Acustica, 2011, 36: 638-644 [陈思, 蓝宇. 长轴加长型宽带弯张换能器. 声学学报, 2011, 36: 638-644]. Google Scholar

[21] Li Q H. New advances of underwater acoustic signal processing. Appl Acoust, 2012, 31: 1-9 [李启虎. 水声信号处理领域新进展. 应用声学, 2012, 31: 1-9]. Google Scholar

[22] Burenkov S V, Gavrilov A N, Uporin A Y, et al. Heard Island feasibility test: long-range sound transmission from Heard Island to Krylov underwater mountain. J Acoust Soc Am, 1994, 96: 2458-2463 CrossRef Google Scholar

[23] Worcester P F, Spindel R C. North pacific acoustic laboratory. J Acoust Soc Am, 2005, 117: 1449-1510. Google Scholar

[24] Li S, Schuliheiss P M. Depth measurement of remote sources using multipath propagation. IEEE J Ocean Eng, 1993, 18: 379-387 CrossRef Google Scholar

[25] Del Balzo D R, Feuillade C, Rowe M M. Effects of water-depth mismatch on matched-field localization in shallow water. J Acoust Soc Am, 1988, 83: 2180-2185 CrossRef Google Scholar

[26] Feillade C, Del Balzo D R, Rowe M M. Environmental mismatch in shallow-water matched field processing: geoacoustic parameter variability. J Acoust Soc Am, 1989, 85: 2354-2364 CrossRef Google Scholar

[27] An L, Wang Z, Lu J. Calculating the waveguide invariant by the 2-D Fourier transform ridges of Lofargram image. J Chin Electron Inf, 2008, 30: 2930-2933. Google Scholar

[28] Li Q. Theoretical analysis and experimental results of interference striation of underwater target noise in shallow water waveguide. Chin J Acoust, 2011, 31: 73-80. Google Scholar

[29] Nehorai A, Padeli E. Acoustic vector-sensor array processing. IEEE Trans Signal Process, 1994, 42: 2481-2491 CrossRef Google Scholar

[30] Lemon S G. Towed array history, 1917-2003. IEEE J Ocean Eng, 2004, 29: 365-373 CrossRef Google Scholar

[31] Ricker D W. Estimation of coherent detection performance for spread scattering in reverberation noise mixtures. J Acoust Soc Am, 2000, 107: 1978-1986 CrossRef Google Scholar

[32] Hlawatsch F. Time-frequency formulation, design, and implementation of time-varying optimal filters for signal estimation. IEEE Trans Signal Process, 2000, 48: 417-432. Google Scholar

[33] Pan X, Li C, Xu Y, et al. Combination of time-reversal focusing and nulling for detection of small targets in strong reverberation environments. IET Radar Sonar Nav, 2014, 8: 9-16 CrossRef Google Scholar

[34] Bhattacharya T K. Neural network-based radar detection for an ocean environment. IEEE Trans Aerosp Electron Syst, 1997, 33: 408-420 CrossRef Google Scholar

[35] Buzzi S, Lops M, Venturino L. Track-before-detect procedures for early detection of moving target from airborne radars. IEEE Trans Aerosp Electron Syst, 2005, 41: 937-954 CrossRef Google Scholar

[36] Hayes M P, Gough P T. Synthetic aperture sonar: a review of current status. IEEE J Ocean Eng, 2009, 34: 207-224 CrossRef Google Scholar

[37] Lee J, Burke M, Hammond J. The theoretical prediction, interpretation and computation of the Fourier-Mellin transform applied to sonar classification of ships. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE Signal Processing Society, Albuquerque, 1990. 2735-2738. Google Scholar

[38] Goldberg D E. Genetic algorithms and Walsh functions: part I, a gentle introduction. Complex Syst, 1989, 3: 129-152. Google Scholar

[39] Alan I C, Atkins P R, Foo K Y, et al. Phase calibration of sonar systems using standard targets and dual-frequency transmission pulses. J Acoust Soc Am, 2011, 130: 1880-1887 CrossRef Google Scholar

[40] Li Q H, Li M, Yang X T. The detection of single frequency component of underwater radiated noise of target: theoretical analysis. Acta Acustica, 2008, 33: 193-196 [李启虎, 李敏, 杨秀庭. 水下目标辐射噪声中单频信号分量的检测: 理论分析. 声学学报, 2008, 33: 193-196]. Google Scholar

[41] Liu G M, Sun C, Yang Y X. Feature extraction of passive sonar target based on two cepstrums. J Northwestern Polytech Univ, 2008, 26: 276-281 [柳革命, 孙超, 杨益新. 两种倒谱特征提取技术在水声目标识别中的应用. 西北工业大学学报, 2008, 26: 276-281]. Google Scholar

[42] Wu G Q, Chen Y Q, Li L Q, et al. The analysis of underwater transient signal and their detection by spectral correlation. Acta Acustica, 2000, 25: 510-515 [吴国清, 陈永强, 李乐强, 等. 水声瞬态信号短时谱形态及谱相关法检测. 声学学报, 2000, 25: 510-515]. Google Scholar

[43] Zhang X Y, Luo L Y. Recent development of passive sonar signal detection. Tech Acoust, 2014, 33: 559-563 [张晓勇, 罗来源. 被动声纳信号检测技术发展. 声学技术, 2014, 33: 559-563]. Google Scholar

[44] Yan S F, Ma Y L. Sensor Array Beampattern Optimization: Theory with Applications. Beijing: Science Press, 2009 [鄢社锋, 马远良. 传感器阵列波束优化设计及应用. 北京: 科学出版社, 2009]. Google Scholar

[45] Yan S F, Ma X C. Designs and implementations of broadband beamformers. Acta Acustica, 2008, 33: 316-326 [鄢社锋, 马晓川. 宽带波束形成器的设计与实现. 声学学报, 2008, 33: 316-326]. Google Scholar

[46] Mio K, Chocheyras Y, Doisy Y. Space time adaptive processing for low frequency sonar. In: Proceedings of OCEANS 2000 MTS/IEEE Conference and Exhibition, Providence, 2000. 1315-1319. Google Scholar

[47] Candy J V. Signal Processing: the Model Based Approach. New York: McGraw-Hill, 1986. Google Scholar

[48] Fizell R G. Application of high-resolution processing to range and depth estimation using ambiguity function methods. J Acoust Soc Am, 1987, 82: 606-613 CrossRef Google Scholar

[49] Livingston E, Diachok O. Estimation of average under-ice reflection amplitudes and phases using matched-field processing. J Acoust Soc Am, 1989, 86: 1909-1919 CrossRef Google Scholar

[50] Hamson R M, Heitmeyer R M. Environmental and system effects on source localization in shallow water by the matched-field processing of a vertical array. J Acoust Soc Am, 1989, 86: 1950-1959 CrossRef Google Scholar

[51] Fueillade C, Kinney W A, Del Balzo D R. Shallow-water matched field localization off Panama City, Florida. J Acoust Soc Am, 1990, 88: 423-433 CrossRef Google Scholar

[52] Richardson A M, Nolte L W. A posteriori probability source localization in an uncertain sound speed, deep ocean environment. J Acoust Soc Am, 1991, 89: 2280-2284 CrossRef Google Scholar

[53] Xu W, Baggeroer A B, Schmidt H. Performance analysis for matched-field source localization: simulations and experimental results. IEEE J Ocean Eng, 2006, 31: 325-344 CrossRef Google Scholar

[54] Xu W, Xiao Z, Yu L. Performance analysis of matched-field source localization under spatially correlated noise field. IEEE J Ocean Eng, 2011, 36: 273-284 CrossRef Google Scholar

[55] Baggeroer A B. Why did applications of MFP fail, or did we not understand how to apply MFP? In: Proceedings of the 1st Conference and Exhibition on Underwater Acoustics, Corfu island, 2013. 41-49. Google Scholar

[56] Sazontov A G, Malekhanov A I. Matched field signal processing in underwater sound channels (Review). Acoust Phys, 2015, 61: 213-230 CrossRef Google Scholar

[57] Cox H. Fundamentals of bistatic active SONAR. In: Underwater Acoustic Data Processing. Berlin: Springer, 1989. 3-24. Google Scholar

[58] Carey W M, Cable P G, Cox H. Shallow water active sonar environmental acoustic issues. J Acoust Soc Am, 1993, 93: 2267. Google Scholar

[59] Zhao J W, Yan Y S, Ding W, et al. The performance and prospect of bi-static sonar. Acoust Electric Eng, 1991, 23: 29-33 [赵俊渭, 阎宜生, 丁纬, 等. 双基地声纳的性能与展望. 声学与电子工程, 1991, 23: 29-33]. Google Scholar

[60] Zhang X F, Zhao J W, Wang R Q, et al. Research on accuracy of localization algorithm for bi-static Sonar. Acta Simulata Systematica Sinica, 2003, 15: 1471-1473 [张小凤, 赵俊渭, 王荣庆, 等. 双基地声纳定位精度和算法研究. 系统仿真学报, 2003, 15: 1471-1473]. Google Scholar

[61] Yang L, Cai Z M. Analysis of detectable region for the bi-static sonar in reverberation background. J Harbin Eng Univ, 2006, 27: 597-602 [杨丽, 蔡志明. 混响背景下双基地声纳的探测范围分析. 哈尔滨工程大学学报, 2006, 27: 597-602]. Google Scholar

[62] Arii M. Ship detection from full polarimetric SAR data at different incidence angles. In: Proceedings of the 3rd International Asia-Pacific Conference on IEEE Synthetic Aperture Radar, Seoul, 2011. 1-4. Google Scholar

[63] Wilson H, Leong H. An estimation and verification of vessel radar cross sections for HF surface wave radar. IEEE Antennas Propag Mag, 2006, 48: 11-16. Google Scholar

[64] Ouchi K. Ship detection by ALOS-PALSAR: an overview. In: Proceedings of the 3rd International Asia-Pacific Conference on IEEE Synthetic Aperture Radar, Seoul, 2011. 1-2. Google Scholar

[65] Tello M, L{ó}pez-Mart{\'\i}nez C, Mallorqui J J. A novel algorithm for ship detection in SAR imagery based on the wavelet transform. IEEE Geosci Remote Sens Lett, 2005, 2: 201-205 CrossRef Google Scholar

[66] Wang Y, Li H, Zhang Y, et al. Marine target detection in quad-pol synthetic aperture radar imagery based on the relative phase of cross-polarized channels. J Appl Remote Sens, 2015, 9: 096092-205 CrossRef Google Scholar

[67] Rey M T, Tunaley J K, Folinsbee J T, et al. Application of Radon transform techniques to wake detection in Seasat-A SAR images. IEEE Trans Geosci Remote Sens, 1990, 28: 553-560 CrossRef Google Scholar

[68] Ai J, Qi X, Yu W, et al. A novel ship wake CFAR detection algorithm based on SCR enhancement and normalized Hough transform. IEEE Geosci Remote Sens Lett, 2011, 8: 681-685 CrossRef Google Scholar

[69] Greidanus H, Kourti N. Findings of the DECLIMS project-detection and classification of marine traffic from space. In: Proceedings of SEASAR, Frascati, 2006. 23-26. Google Scholar

[70] Estable S, Teufel F, Petersen L, et al. Detection and classification of offshore artificial objects in TerraSAR-X images: first outcomes of the DeMarine-DEKO project. In: Proceedings OCEANS 2009 MTS/IEEE Conference and Exhibition, Bremen, 2009. 1-8. Google Scholar

[71] Wu F, Wang C, Zhang B, et al. Study on vessel classification in SAR imagery: a survey. Remote Sens Tech Appl, 2014, 29: 1-8 [吴樊, 王超, 张波, 等. SAR 图像船只分类识别研究进展. 遥感技术与应用, 2014, 29: 1-8]. Google Scholar

[72] Zhu C, Zhou H, Wang R, et al. A novel hierarchical method of ship detection from spaceborne optical image based on shape and texture features. IEEE Trans Geosci Remote Sens, 2010, 48: 3446-3456 CrossRef Google Scholar

[73] Zhang F, Zhang L, Wu B. Progress of ship detection technology and system based on remote sensing technology in European union. J Remote Sens, 2007, 11: 552-562. Google Scholar

[74] Goferman S, Zelnic-Manor L, Tal A. Context-aware saliency detection. IEEE Trans Pattern Anal, 2012, 34: 1915-1926 CrossRef Google Scholar

[75] Antelo J, Ambrosio G, Gonzalez J, et al. Ship detection and recognition in high-resolution satellite images. In: Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Cape Town, 2009. 514-517. Google Scholar

[76] Bi F K, Liu F, Gao L N. A hierarchical salient-region based algorithm for ship detection in remote sensing images. In: Advances in Neural Network Research and Applications, the series Lecture Notes in Electrical Engineering. New York: Springer, 2010. 67: 729-738. Google Scholar

[77] Perez A, Gonzalez R C. An iterative thresholding algorithm for image segmentation. IEEE Trans Pattern Anal, 1987, 9: 742-751. Google Scholar

[78] Lie W N. Automatic target segmentation by locally adaptive image thresholding. IEEE Trans Image Process, 1995, 4: 1036-1041 CrossRef Google Scholar

[79] Espindola G M, Camara G, Reis I A, et al. Parameter selection for region-growing image segmentation algorithms using spatial autocorrelation. Int J Remote Sens, 2006, 27: 3035-3040 CrossRef Google Scholar

[80] Zhao Y H, Wu X Q, Wen L Y, et al. Ship target detection scheme for optical remote sensing images. Opto-Electron Eng, 2008, 35: 102-106 [赵英海, 吴秀清, 闻凌云, 等. 可见光遥感图像中舰船目标检测方法. 光电工程, 2008, 35: 102-106]. Google Scholar

[81] Corbane C, Marre F, Petit M. Using SPOT-5 HRG data in panchromatic mode for operational detection of small ships in tropical area. Sensors, 2008, 8: 2959-2973 CrossRef Google Scholar

[82] Maresca S, Braca P, Horstmann J, et al. Maritime surveillance with multiple over-the-horizon HFSW radars: an overview of recent experimentation. IEEE Aerosp Electron Syst Mag, 2015, 30: 4-18 CrossRef Google Scholar

[83] Liu Y, Xu R, Zhang N. Progress in HFSWR research at Harbin Institute of Technology. In: Proceedings of International Radar Conference, Adelaide, 2003. 522-528. Google Scholar

[84] Ji Y G, Zhang J, Wang Y M, et al. Ship detection point association and fusion with dual-frequency HF surface wave radar. Syst Eng Electron, 2014, 36: 266-271 [纪永刚, 张杰, 王祎鸣, 等. 双频地波雷达船只目标点迹关联与融合处理. 系统工程与电子技术, 2014, 36: 266-271]. Google Scholar

[85] Sun W F, Ji Y G, Zhang X Y, et al. Ship target tracking based on adaptive $\alpha$-$\beta$ filter in HFSWR. Adv Marine Sci, 2015, 33: 394-402 [孙伟峰, 纪永刚, 张晓莹, 等. 基于自适应 $\alpha$-$\beta$ 滤波的 HFSWR 目标航迹跟踪. 海洋科学进展, 2015, 33: 394-402]. Google Scholar

[86] Leong H. The potential of bistatic HF surface wave radar system for the surveillance of water-entry area along coastline. In: Proceedings of IEEE International Conference on Radar, Shanghai, 2006. 45: 51-65. Google Scholar

[87] Anna D, Klaus-Werner G, Hermann R, et al. Low power high frequency surface wave radar application for ship detection and tracking. In: Proceedings of IEEE International Conference on Radar. New York: IEEE, 2008. 627-632. Google Scholar

[88] Maresca S, Horstmann J, Grasso R, et al. Performance assessment of HF-radar ship detection. In: Proceedings of International Radar Symposium, Leipzig, 2011. 131-136. Google Scholar

[89] Wang Y M, Zhang J, Ji Y G, et al. CFAR ship detection verification method of HFSWR based on range-Doppler projection of AIS data. Haiyang Xuebao, 2015, 37: 76-82 [王祎鸣, 张杰, 纪永刚, 等. 基于 AIS 距离-多普勒投影的地波雷达 CFAR 检测验证方法. 海洋学报, 2015, 37: 76-82]. Google Scholar

[90] Dzvonkovskaya A, Gurgel K-W, Rohling H, et al. Low power high frequency surface wave radar application for ship detection and tracking. In: Proceedings of International Conference on Radar. New York: IEEE, 2008. 627-632. Google Scholar

[91] Hugh J, Roarty H, Smith M, et al. Real-time beyond the horizon vessel detection. In: Proceedings of SPIE Defense, Security, and Sensing, International Society for Optics and Photonics, Baltimore, 2013. 813-831. Google Scholar

[92] Wen B Y, Shi Y S, Yang J, et al. Target detection using multi-station HFSWR. Chin J Radio Sci, 2015, 30: 535-541 [文必洋, 石阳升, 杨静, 等. 多站高频地波雷达目标检测研究. 电波科学学报, 2015, 30: 535-541]. Google Scholar

[93] Lin M S, Zhang Y G, Yuan X Z. The development course and trend of ocean remote sensing satellite. Haiyang Xuebao, 2015, 37: 1-10 [林明森, 张有广, 袁欣哲. 海洋遥感卫星发展历程与趋势展望. 海洋学报, 2015, 37: 1-10]. Google Scholar

[94] Barrick D, Fernandez V, Ferrer M I, et al. A short-term predictive system for surface currents from a rapidly deployed coastal HF radar network. Ocean Dynam, 2012, 62: 725-740 CrossRef Google Scholar

[95] Ulaby F T, Long D G, Blackwell W J, et al. Microwave Radar and Radiometric Remote Sensing. Ann Arbor: the University of Michigan Press, 2014. Google Scholar

[96] Imperatore P, Riccio D. Geoscience and Remote Sensing, New Achievements. Rijeka: In-Tech, 2010. Google Scholar

[97] Lee Z, Cui T, Sun L. Derivation and application of biogeochemical properties from the measurement of water color: methods and challenges. Acta Laser Biology Sinica, 2014, 23: 481-501. Google Scholar

[98] Lu X, Hu Y, Trepte C, et al. Ocean subsurface studies with the CALIPSO spaceborne lidar. J Geophys Res Ocean, 2014, 119: 4305-4317 CrossRef Google Scholar

[99] Hill V J, Zimmerman R C. Estimates of primary production by remote sensing in the arctic ocean: assessment of accuracy with passive and active sensors. Deep-Sea Res I, 2010, 57: 1243-1254 CrossRef Google Scholar

[100] Liu X D, Wang L, Yang J, et al. Competitiveness analysis for China's ocean acoustic detection technologies. J Ocean Tech, 2015, 34: 80-85 [刘晓东, 王磊, 杨娟, 等. 我国海洋声学探测技术竞争力分析. 海洋技术学报, 2015, 34: 80-85]. Google Scholar

[101] Munk W, Worcester P, Wunsch C. Ocean Acoustic Tomography. Cambridge: Cambridge University Press, 1995. Google Scholar

[102] Dushaw B, Bold G, Chiu C-S, et al. Observing the ocean in the 2000s: a strategy for the role of acoustic tomography in ocean climate observation. In: Observing the Oceans in the 21st Century. Melbourne: GODAE Project Office and Bureau of Meteorology, 2001. 391-418. Google Scholar

[103] Zhao H F, Wang F Y, Zhu X H, et al. Ocean acoustic tomography: current progress and future prospect. J Ocean Tech, 2015, 34: 69-74 [赵航芳, 汪非易, 朱小华, 等. 海洋声学层析研究现状与展望. 海洋技术学报, 2015, 34: 69-74]. Google Scholar

[104] Worcester P F, Dzieciuch M A, Mercer A J, et al. The north pacific acoustic laboratory deep-water acoustic propagation experiments in the Philippine Sea. J Acoust Soc Am, 2013, 134: 3359-3375 CrossRef Google Scholar

[105] Wang T, Xu W. Sparsity-based approach for ocean acoustic tomography using learned dictionaries. In: Proceedings of OCEANS MTS/IEEE Conference and Exhibition, Shanghai, 2016. 1-6. Google Scholar

[106] Makris N C. Imaging ocean-basin reverberation via inversion. J Acoust Soc Am, 1993, 94: 983-993 CrossRef Google Scholar

[107] Ratilal P, Lai Y, Symonds D T, et al. Long range acoustic imaging of the continental shelf environment: the acoustic clutter Reconnaissance experiment 2001. J Acoust Soc Am, 2005, 117: 1977-1998 CrossRef Google Scholar

[108] Makris N C, Ratilal P, Symonds D T, et al. Fish population and behavior revealed by instantaneous continental shelf-scale imaging. Science, 2006, 311: 660-663 CrossRef Google Scholar

[109] Makris N C, Ratilal P, Jagannathan S, et al. Critical population density triggers rapid shoal formation in vast oceanic fish shoals. Science, 2009, 323: 1734-1737 CrossRef Google Scholar

[110] Cella M U, Johnstone R, Shuley N. Electromagnetic wave wireless communication in shallow water coastal environment: Theoretical analysis and experimental results. In: Proceedings the 4th ACM International Workshop on UnderWater Networks. New York: ACM, 2009. 1-9. Google Scholar

[111] Stojanovic M. Acoustic (underwater) communications. In: Proakis J G, eds. Encyclopedia of Telecommunications. Hoboken: John Wiley and Sons, 2003. Google Scholar

[112] Anguita D, Brizzolara D, Parodi G, et al. Optical wireless underwater communication for AUV: preliminary simulation and experimental results. In: Proceedings of OCEANS 2011 MTS/IEEE Conference and Exhibition, Santander, 2011. 1-5. Google Scholar

[113] Fletcher A S, Hamilton S A, Moores J D. Undersea laser communication with narrow beams. IEEE Commun Mag, 2015, 11: 49-55. Google Scholar

[114] Liu J T, Chen W B. Feasibility study of laser communications from satellite to submerged platform. Acta Optica Sinica, 2006, 26: 1441-1446 [刘金涛, 陈卫标. 星载激光对水下平台通信可行性研究. 光学学报, 2006, 26: 1441-1446]. Google Scholar

[115] Tian B, Zhang F, Tan X. Design and development of an LED-based optical communication system for autonomous underwater robots. In: Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Wollongong, 2013. 1558-1563. Google Scholar

[116] Doniec M, Detweiler C, Vasilescu I, et al. Using optical communication for remote underwater robot operation. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, 2010. 4017-4022. Google Scholar

[117] Oubei H M, Li C, Park K-H, et al. 2.3 Gbit/s underwater wireless optical communications using directly modulated 520 nm laser diode. Opt Express, 2015, 23: 20743-20748. Google Scholar

[118] Sun M, Zheng B, Zhao L, et al. A design of the video transmission based on the underwater laser communication. In: Proceedings of OCEANS MTS/IEEE Conference and Exhibition, St. John's, 2014. 1-4. Google Scholar

[119] Green D, Rice J. Channel-tolerant FH-MFSK acoustic signaling for undersea communications and networks. IEEE J Ocean Eng, 2000, 25: 28-39 CrossRef Google Scholar

[120] Melodia T, Kulhandjian H, Kuo L C, et al. Advances in underwater acoustic networking. In: Mobile Ad Hoc Networking: Cutting Edge Directions. 2nd ed. Hoboken: John Wiley & Sons, 2013. 804-854. Google Scholar

[121] Kilfoyle D B, Baggeroer A B. The state of the art in underwater acoustic telemetry. IEEE J Ocean Eng, 2000, 25: 4-27 CrossRef Google Scholar

[122] Stojanovic M, Beaujean P P. Acoustic Communication. In: Dhanak M R, Xiros N I, eds. Springer Handbook of Ocean Engineering, Curtin T, ed. Part B: Autonomous Ocean Vehicles and Control. Berlin: Springer, 2016. Google Scholar

[123] Freitag L, Grund M, Singh S, et al. The WHOI micro-modem: an acoustic communications and navigation system for multiple platforms. In: Proceedings of OCEANS IEEE/MTS Conference and Exhibition, Washington, 2005. 1086-1092. Google Scholar

[124] Zhou S, Wang Z. OFDM for Underwater Acoustic Communications. Hoboken: John Wiley & Sons, Ltd, 2014. Google Scholar

[125] Yu H, Song A, Badiey M, et al. Iterative estimation of doubly selective underwater acoustic channel using basis expansion models. Ad Hoc Netw, 2015, 34: 52-61 CrossRef Google Scholar

[126] Lin N, Sun H, Cheng E, et al. Prediction based sparse channel estimation for underwater acoustic OFDM. Appl Acoust, 2015, 96: 94-100 CrossRef Google Scholar

[127] Xia M, Rouseff D, Ritcey J A, et al. Underwater acoustic communication in a highly refractive environment using SC-FDE. IEEE J Ocean Eng, 2014, 39: 491-499 CrossRef Google Scholar

[128] Zheng Y, Wu J, Xiao C. Turbo equalization for single-carrier underwater acoustic communications. IEEE Commun Mag, 2015, 53: 79-87. Google Scholar

[129] Roy S, Duman T M, McDonald V, et al. High rate communication for underwater acoustic channels using multiple transmitters and space-time coding: receiver structures and experimental results. IEEE J Ocean Eng, 2007, 32: 663-688 CrossRef Google Scholar

[130] Vajapeyam M, Vedantan S, Mitra U. Distributed space-time cooperative schemes for underwater acoustic communications. IEEE J Ocean Eng, 2008, 33: 489-501 CrossRef Google Scholar

[131] Edelman G, Hodgkiss W S, Kim S, et al. Underwater acoustic communication using time reversal. IEEE J Ocean Eng, 2005, 30: 852-864 CrossRef Google Scholar

[132] Rouseff D, Jackson D R, Fox L J, et al. Underwater acoustic communication by passive-phase conjugation: theory and experimental results. J Acoust Soc Am, 2000, 26: 821-831. Google Scholar

[133] Flynn J A, Ritcey J A, Rouseff D, et al. Multichannel equalization by decision-directed passive phase conjugation: Experimental results. IEEE J Ocean Eng, 2004, 29: 824-836 CrossRef Google Scholar

[134] Zeng W, Yu Z, Xu W. Experimental demonstration of time reversal communication in doubly dispersive underwater channels. In: Proceedings of the 8th ACM International Workshop on UnderWater Networks. New York: ACM, 2013. 1-5. Google Scholar

[135] Choi J W, Riedl T, Kim K, et al. Adaptive linear turbo equalization over doubly selective channels. IEEE J Ocean Eng, 2011, 36: 473-489 CrossRef Google Scholar

[136] Pelekanakis K, Chitre M. New sparse adaptive algorithms based on the natural gradient and the L0-norm. IEEE J Ocean Eng, 2013, 38: 323-332 CrossRef Google Scholar

[137] Roy S, Duman T, McDonald V. Error rate improvement in underwater MIMO communications using sparse partial response equalization. IEEE J Ocean Eng, 2009, 34: 181-201 CrossRef Google Scholar

[138] Wan L, Zhou H, Xu X, et al. Adaptive modulation and coding for underwater acoustic OFDM. IEEE J Ocean Eng, 2015, 40: 327-336 CrossRef Google Scholar

[139] Curtin T B, Bellingham J G, Progress toward autonomous ocean sampling networks. Deep Sea Res Part II Topical Studies Oceanogr, 2009, 56: 62-67. Google Scholar

[140] Rice J, Creber B, Fletcher C, et al. Evolution of Seaweb underwater acoustic networking. In: Proceedings of OCEANS 2000 MTS/IEEE Conference and Exhibition, Providence, 2000. 2007-2017. Google Scholar

[141] Grund M, Freitag L, Preisig J, et al. The PLUSNet underwater communications system: Acoustic telemetry for undersea surveillance. In: Proceedings of OCEANS 2006 MTS/IEEE Conference and Exhibition, Boston, 2006. 1-5. Google Scholar

[142] Acar G, Adams A E. ACMENet: an underwater acoustic sensor network protocol for real-time environmental monitoring in coastal areas. IET Radar Sonar Nav, 2006, 153: 365-380 CrossRef Google Scholar

[143] Chen K, Ma M, Cheng E, et al. A survey on MAC protocols for underwater wireless sensor networks. IEEE Commun Surv Tut, 2014, 16: 1433-1447 CrossRef Google Scholar

[144] Syed W, Ye H, Heidemann J. T-Lohi: a new class of MAC protocols for underwater acoustic sensor networks. In: Proceedings of the 27th Conference on Computer Communications, Phoenix, 2007. 231-235. Google Scholar

[145] Petrioli R P, Cahiara, Potter J. Performance evaluation of underwater MAC protocols: from simulation to at sea testing. In: Proceedings of OCEANS 2011 MTS/IEEE Conference and Exhibition, Santander, 2011. 1-10. Google Scholar

[146] Pu L, Luo Y, Mo H, et al. Comparing underwater MAC protocols in real sea experiment. Comput Commun, 2013, 56: 1-9. Google Scholar

[147] Khalil I, Gadallah Y, Khreishah M H. An adaptive OFDMA-based MAC protocol for underwater acoustic wireless sensor networks. Sensors, 2012, 12: 8782-8805 CrossRef Google Scholar

[148] Sozer E M, Stojanovic M, Proakis J G. Underwater acoustic networks. IEEE J Ocean Eng, 2000, 25: 72-83 CrossRef Google Scholar

[149] Proakis J G, Sozer E M, Rice J A, et al. Shallow water acoustic networks. IEEE Commun Mag, 2001, 39: 114-119. Google Scholar

[150] Heidemann J, Stojanovic M, Zorzi M. Underwater sensor networks: applications, advances and challenges. Philos Trans R Soc A, 2012, 370: 158-175 CrossRef Google Scholar

[151] Zhu Y, Peng Z, Cui J-H, et al. Toward practical MAC design for underwater acoustic networks. IEEE Trans Mobile Comput, 2015, 14: 872-886 CrossRef Google Scholar

[152] Ahn J, Syed A, Krishnamachari B, et al. Design and analysis of a propagation delay tolerant ALOHA protocol for underwater networks. Ad Hoc Netw, 2011, 9: 752-766 CrossRef Google Scholar

[153] Han G, Jiang J, Bao N, et al. Routing protocols for underwater wireless sensor networks. IEEE Commun Mag, 2015, 53: 72-78. Google Scholar

[154] Darehshoorzadeh A, Boukerche A. Underwater sensor networks: a new challenge for opportunistic routing protocols. IEEE Commun Mag, 2015, 53: 98-106. Google Scholar

[155] Jim P, Kurose J, Levine B N. A survey of practical issues in underwater networks. ACM SIGMOBILE Mobile Comput Commun Rev, 2007, 11: 23-33 CrossRef Google Scholar

[156] He Y, Wang G H, Guan X, et al. Information Fusion Theory With Applications. Beijing: Electronics Industry Press, 2010 [何友, 王国宏, 关欣, 等. 信息融合理论及应用. 北京: 电子工业出版社, 2010]. Google Scholar

[157] StoneL D, Corwin T L, Barlow C A. Bayesian Multiple Target Tracking. Norwood: Artech House Inc, 1999. Google Scholar

[158] HallD L, Llinas J. An introduction to multisensor data fusion. Proc IEEE, 1997, 85: 6-23 CrossRef Google Scholar

[159] KhaleghiB , Khamis A, Karray F O. Multisensor data fusion: a review of the state-of-the-art. Inform Fusion, 2013, 14: 28-44 CrossRef Google Scholar

[160] Han C. Multi-Source Information Fusion. Beijing: Tsinghua University Press, 2010 [韩崇昭. 多源信息融合. 北京: 清华大学出版社, 2010]. Google Scholar

[161] Yang W. Multi-sensor Data Fusion and Its Applications. Xian: Xidian University Press, 2004 [杨万海. 多传感器数据融合及其应用. 西安: 西安电子科技大学出版社, 2004]. Google Scholar

[162] Zhao Z G, Xiong Z H, Wang K, et al. Conceptions, Methods and Applications on Information Fusion. Beijing: National Defense Industry Press, 2012 [赵宗贵, 熊朝华, 王珂, 等. 信息融合概念方法与应用. 北京: 国防工业出版社, 2012]. Google Scholar

[163] Pan Q, Cheng Y M, Liang Y, et al. Multi-source Information Fusion Theory and its Applications. Beijing: Tsinghua University Press, 2013 [潘泉, 程咏梅, 梁彦, 等. 多源信息融合理论及应用. 北京: 清华大学出版社, 2013]. Google Scholar

[164] Chen D, Liu Z, Wang L, et al. Natural disaster monitoring with wireless sensor networks: a case study of data-intensive applications upon low-cost scalable systems. Mobile Netw Appl, 2013, 18: 651-663 CrossRef Google Scholar

[165] Corke P, Wark T, Jurdak R, et al. Environmental wireless sensor networks. Proc IEEE, 2010, 98: 1903-1917 CrossRef Google Scholar

[166] Ji Y, Zhang J, Meng J, et al. Point association analysis of vessel target detection with SAR, HFSWR and AIS. Acta Oceanol Sin, 2014, 33: 73-81. Google Scholar

[167] Liu G W, Liu Y X, Ji Y G, et al. Track association for high-frequency surface wave radar and AIS based on fuzzy double threshold theory. Syst Eng Electron, 2015, 38: 557-562 [刘根旺, 刘永信, 纪永刚, 等. 基于模糊双门限的高频地波雷达与 SAR 目标航迹关联方法. 系统工程与电子技术, 2015, 38: 557-562]. Google Scholar

[168] Xia D W, Shi S X, Yu G, et al. Study on the techniques of marine data warehouse and data mining. Marine Sci Bulletin, 2005, 24: 60-65 [夏登文, 石绥祥, 于戈, 等. 海洋数据仓库及数据挖掘技术方法研究. 海洋通报, 2005, 24: 60-65]. Google Scholar

[169] Sun C, Liu Q, Hu T, et al. Software architecture for oceanographic big data processing. Periodical of Ocean University of China, 2015, 45: 134-137 [孙朝随, 刘青, 胡桐, 等. 海洋大数据处理软件体系结构设计. 中国海洋大学学报, 2015, 45: 134-137]. Google Scholar

[170] Zhang J, Cao C, Guo J, et al. Technical demands and development priorities in China's 13th five-year plan period for marine environment observing and forecasting: Case study from the North China Sea. J Ocean Tech, 2014, 33: 1-5 [张杰, 曹丛华, 郭敬天, 等. 海洋环境观测预报技术需求与 ``十三五'' 发展重点. 海洋技术学报, 2014, 33: 1-5]. Google Scholar

[171] Nowlin W D, Malone T C. Research and GOOS. Mar Technol Soc J, 2003, 37: 42-46 CrossRef Google Scholar

[172] Mecca V F, Krolik J L. Slow-time MIMO STAP with improved power efficiency. In: Proceedings of the 41st Asilomar Conference on Signals, Systems and Computers, Pacific Grove, 2007. 202-206. Google Scholar

[173] Wu J, Wang T, Zhang L, et al. Range-dependent clutter suppression for airborne sidelooking radar using MIMO technique. IEEE Trans Aerosp Electron Syst, 2012, 48: 3647-3654 CrossRef Google Scholar

[174] Velotto D, Soccorsi M, Lehner S. Azimuth ambiguities removal for ship detection using full polarimetric X-band SAR data. IEEE Trans Geosci Remote Sens, 2014, 52: 76-88 CrossRef Google Scholar

[175] Burkholder R J, Pino M R, Obelleiro F. A Monte Carlo study of the rough-sea-surface influence on the radar scattering from two-dimensional ships. IEEE Antennas Propag Mag, 2001, 43: 25-33 CrossRef Google Scholar

[176] Diao G, Xu X, Ni H, et al. Synthetic aperture radar signal simulation of ships on sea surface. J Syst Simul, 2015, 27: 1989-2007 [刁桂杰, 许小剑, 倪虹, 等. 海面舰船目标 SAR 回波信号仿真. 系统仿真学报, 2015, 27: 1989-2007]. Google Scholar

[177] Yuan M. Development of remote sensing satellite and its business model. Satellite Appl, 2015, 15-19 [原民辉. 遥感卫星及其商业模式的发展. 卫星应用, 2015, 15-19]. Google Scholar

[178] Durack P J, Wijffels S E, Matear R J. Ocean salinities reveal strong global water cycle intensification during 1950 to 2000. Science, 2012, 336: 455-458 CrossRef Google Scholar

[179] Brown C J, Smith S J, Lawton P, et al. Benthic habitat mapping: a review of progress towards improved understanding of the spatial ecology of the seafloor using acoustic techniques. Estuar Coast Shelf Sci, 2011, 92: 502-520 CrossRef Google Scholar