Cooperative robotic networks for underwater surveillance: an overview

Gabriele Ferri*; Andrea Munafò*; Alessandra Tesei; Paolo Braca; Florian Meyer; Konstantinos Pelekanakis; Roberto Petroccia; João Alves; Christopher Strode; Kevin LePage

Cooperative robotic networks for underwater surveillance: an overview

View Fulltext

Author(s): Gabriele Ferri* ¹¹ ; Andrea Munafò* ²² ; Alessandra Tesei ¹¹ ; Paolo Braca ¹¹ ; Florian Meyer ³³ ; Konstantinos Pelekanakis ¹¹ ; Roberto Petroccia ¹¹ ; João Alves ¹¹ ; Christopher Strode ¹¹ ; Kevin LePage ¹¹
- Affiliations: 1: NATO STO-Centre for Maritime Research and Experimentation (CMRE), Viale San Bartolomeo 400, 19127 La Spezia (SP), Italy ;
  2: Marine Autonomous & Robotic Systems (MARS), National Oceanography Centre, University of Southampton Waterfront Campus, European Way, Southampton SO14 3ZH, UK ;
  3: Laboratory for Information & Decision Systems (LIDS), Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
Source: Volume 11, Issue 12, December 2017, p. 1740 – 1761
DOI: 10.1049/iet-rsn.2017.0074 , Print ISSN 1751-8784, Online ISSN 1751-8792

Received 21/02/2017, Accepted 19/06/2017, Revised 22/05/2017, Published 05/07/2017

Underwater surveillance has traditionally been carried out by means of surface and undersea manned vessels equipped with advanced sensor systems. This approach is often costly and manpower intensive. Marine robotics is an emerging technological area that enables the development of advanced networks for underwater surveillance applications. In contrast with the use of standard assets, these advanced networks are typically composed of small, low-power, and possibly mobile robots, which have limited endurance, processing and wireless communication capabilities. When deployed in a region of interest, these robots can cooperatively form an intelligent network achieving high performance with significant features of scalability, adaptability, robustness, persistence and reliability. Such networks of robots can be the enabling technology for a wide range of applications in the maritime domain. However, they also introduce new challenges for underwater distributed sensing, data processing and analysis, autonomy and communications. The main thrust of this study is to review the underwater surveillance scenario within a framework of four research areas: (i) underwater robotics, (ii) acoustic signal processing, (iii) tracking and distributed information fusion, and (iv) underwater communications networks. Progress in each of these areas as well as future challenges is presented.

References

1. 1)
  - 226. Reid, D.B.: ‘An algorithm for tracking multiple targets’, IEEE Trans. Autom. Control, 1979, 24, (6), pp. 843–854.
2. 2)
  - 191. Grimmett, D., Plate, R.: ‘Temporal and Doppler coherence limits for the underwater acoustic channel during the LCAS'15 high duty cycle sonar experiment’. OCEANS 2016 MTS/IEEE Monterey, 2016.
3. 3)
  - 229. Mazor, E., Averbuch, A., Bar-Shalom, Y., et al: ‘Interacting multiple model methods in target tracking: A survey’, IEEE Trans. Aerosp. Electron. Syst., 1998, 34, (1), pp. 103–123.
4. 4)
  - 133. Kulkarni, I., Pompili, D.: ‘Task allocation for networked autonomous underwater vehicles in critical missions’, IEEE J. Sel. Areas Commun., 2010, 28, p. 5.
5. 5)
  - 134. Ferri, G., Munafò, A., Tesei, A., et al: ‘A market-based task allocation framework for autonomous underwater surveillance networks’. OCEANS 2017, Aberdeen, UK(under review), 2017.
6. 6)
  - 210. Uhlmann, J.: ‘Algorithms for multiple-target tracking’, Am. Sci., 1992, 80, (2), pp. 128–141.
7. 7)
  - 302. Petroccia, R., Spaccini, D.: ‘A back-seat driver to remotely control the experiments in an underwater acoustic sensor network’. Proc. MTS/IEEE OCEANS 2013, Bergen, Norway, 10–13 June 2013.
8. 8)
  - 128. Krieger, M., Billeter, J.: ‘The call of duty: self-organized task allocation in a population of up to twelve mobile robots’, Robot. Auton. Syst., 2000, 30, pp. 1–2.
9. 9)
  - 195. Murphy, S.M., Scrutton, J.G.E., Hines, P.C.: ‘Experimental implementation of an echo repeater for continuous active sonar’, IEEE J. Ocean. Eng., 2016, 42, (2), pp. 289–297.
10. 10)
  - 13. Howard, J.: ‘Fixed sonar systems: the history and future of the underwater silent sentinel’, Submar. Rev., 2011, pp. 1–12.
11. 11)
  - 263. Kar, S., Tandon, R., Poor, H.V., et al: ‘Distributed detection in noisy sensor networks’. Proc. ISIT–11, Saint Petersburg, Russia, July 2011, pp. 2856–2860.
12. 12)
  - 97. Kim, T., Yuh, J.: ‘Development of a real-time control architecture for a semi-autonomous underwater vehicle for intervention missions’, Control Eng. Pract., 2004, 12, (12), pp. 1521–1530. Available at http://www.sciencedirect.com/science/article/pii/S0967066103002909.
13. 13)
  - 262. Coraluppi, S.: ‘Multistatic sonar localization’, IEEE J. Ocean. Eng., 2006, 31, (4), pp. 964–974.
14. 14)
  - 24. LePage, K.D., Goldhahn, R., Alves, J., et al: ‘Autonomous networked antisubmarine warfare research and development at CMRE’. OCEANS 2015 – Genova, May 2015, pp. 1–6.
15. 15)
  - 38. Sinha, A., Ding, Z., Kirubarajan, T., et al: ‘Track quality based multitarget tracking approach for global nearest-neighbor association’, IEEE Trans. Aerosp. Electron. Syst., 2012, 48, (2), pp. 1179–1191.
16. 16)
  - 52. Burian, E., Yoerger, D., Bradley, A., et al: ‘Gradient search with autonomous underwater vehicles using scalar measurements’. Proc. AUV 96, Monterey, CA, USA, 1996, pp. 86–98.
17. 17)
  - 160. Sharaga, N., Tabrikian, J.: ‘Optimal adaptive transmit beamforming for cognitive MIMO sonar in a shallow water waveguide’. 22nd European Signal Processing Conf. (EUSIPCO), 2014, vol. 145, pp. 1960–1964.
18. 18)
  - 254. Braca, P., Goldhahn, R., LePage, K., et al: ‘Cognitive multistatic AUV networks’. Proc. FUSION-14, Salamanca, Spain, July 2014.
19. 19)
  - 156. Abraham, D., Lyons, A.: ‘Reverberation envelope statistics and their dependence on sonar bandwidth and scattering patch size’, IEEE J. Ocean. Eng., 2004, 29, (1), pp. 126–137.
20. 20)
  - 66. Wang, H., Yao, K., Estrin, D.: ‘Information-theoretic approaches for sensor selection and placement in sensor networks for target localization and tracking’, J. Commun. Netw., 2005, 7, (4), pp. 438–449.
21. 21)
  - 231. Chang, K.-C., Bar-Shalom, Y.: ‘Joint probabilistic data association for multitarget tracking with possibly unresolved measurements and maneuvers’, IEEE Trans. Autom. Control, 1984, 29, (7), pp. 585–594.
22. 22)
  - 237. Mahler, R.: ‘Statistical multisource-multitarget information fusion’ (Artech House, Norwood, MA, USA, 2007).
23. 23)
  - 1. Zimmer, W.M.X.: ‘Passive acoustic monitoring of cetaceans’ (Cambridge University Press, Cambridge, 2011). Available at https://www.cambridge.org/core/books/passive-acoustic-monitoring-of-cetaceans/8D59083194B2634B9F490635EAF23653.
24. 24)
  - 225. Singer, R., Sea, R., Housewright, K.: ‘Derivation and evaluation of improved tracking filter for use in dense multitarget environments’, IEEE Trans. Inf. Theory, 1974, 20, (4), pp. 423–432.
25. 25)
  - 271. Bajovic, D., Jakovetic, D., Moura, J.M.F., et al: ‘Large deviations performance of consensus+innovations distributed detection with non-Gaussian observations’, IEEE Trans. Signal Process., 2012, 60, (11), pp. 5987–6002.
26. 26)
  - 261. Coraluppi, S., Carthel, C.: ‘Distributed tracking in multistatic sonar’, IEEE Trans. Aerosp. Electron. Syst., 2005, 41, (3), pp. 1138–1147.
27. 27)
  - 314. Luo, Y., Pu, L., Peng, Z., et al: ‘RSS-based secret key generation in underwater acoustic networks: advantages, challenges and performance improvements’, IEEE Commun. Mag., 2016, 54, (2), pp. 32–38.
28. 28)
  - 100. Goldberg, D.: ‘Huxley: A flexible robot control architecture for autonomous underwater vehicles’. OCEANS 2011 IEEE – Spain, June 2011, pp. 1–10.
29. 29)
  - 233. Pulford, G.W.: ‘Taxonomy of multiple target tracking methods’, Proc. IEE Radar Sonar Navig., 2005, 152, (5), pp. 291–304.
30. 30)
  - 228. Blackman, S.S.: ‘Multiple hypothesis tracking for multiple target tracking’, IEEE Trans. Aerosp. Electron. Syst., 2004, 19, pp. 5–18.
31. 31)
  - 161. Haralabus, G., Baldacci, A.: ‘Unambiguous triplet array beamforming and calibration algorithms to facilitate an environmentally adaptive active sonar concept’. IEEE OCEANS Conf., January 2006, vol. 23, (1), pp. 30–40.
32. 32)
  - 295. Li, N., Martínez, J.-F., Meneses Chaus, J.M., et al: ‘A survey on underwater acoustic sensor network routing protocols’, Sensors, 2016, 16, (3), p. 414.
33. 33)
  - 15. Curtin, T., Bellingham, J., Catipovic, J., et al: ‘Autonomous oceanographic sampling networks’, Oceanography, 1993, 6, pp. 86–94. doi.org/10.5670/oceanog.1993.03.
34. 34)
  - 20. Topal, S., Erkmen, I., Erkmen, A.: ‘Towards the robotic avatar: an extensive survey of the cooperation between and within networked mobile sensors’, Future Internet, 2010, 2, pp. 363–387.
35. 35)
  - 132. Deng, Y., Beaujean, P., An, E., et al: ‘Task allocation and path planning for collaborative AUVs operating through an underwater acoustic network’. OCEANS 2010, 2010.
36. 36)
  - 64. Ferri, G., Cococcioni, M., Alvarez, A.: ‘Mission planning and decision support for underwater glider networks: A sampling on-demand approach’, Sensors, 2016, 16, (1), p. 28. Available at http://www.mdpi.com/1424-8220/16/1/28.
37. 37)
  - 90. Ferri, G., Munafò, A., LePage, K.: ‘On data-driven control strategies for AUVs to track targets in sonar surveillance scenarios’, J. Oceanic Eng. (under review), 2017, pp. 1–25.
38. 38)
  - 240. Vo, B.-T., Vo, B.-N., Cantoni, A.: ‘The cardinality balanced multi-target multi-Bernoulli filter and its implementations’, IEEE Trans. Signal Process., 2009, 57, (2), pp. 409–423.
39. 39)
  - 245. Kschischang, F.R., Frey, B.J., Loeliger, H.-A.: ‘Factor graphs and the sum-product algorithm’, IEEE Trans. Inf. Theory, 2001, 47, (2), pp. 498–519.
40. 40)
  - 260. Meyer, F., Braca, P., Hlawatsch, F., et al: ‘Scalable adaptive multitarget tracking using multiple sensors’. Proc. GLOBECOM, Washington, DC, December 2016.
41. 41)
  - 23. Munafò, A., Ferri, G.: ‘An acoustic network navigation system’, J. Field Robot., 2017, pp. 1–20.
42. 42)
  - 200. Glegg, S.A., Olivieri, M.P., Coulson, R.K., et al: ‘A passive sonar system based on an autonomous underwater vehicle’, IEEE J. Ocean. Eng., 2001, 26, (4), pp. 700–710.
43. 43)
  - 189. Hines, P.C., Murphy, S.M., Abraham, D.A., et al: ‘The dependence of signal coherence on sea-surface roughness for high and low duty cycle sonars in a shallow-water channel’, IEEE J. Ocean. Eng., 2016, 42, (2), pp. 298–318.
44. 44)
  - 266. Viswanathan, R., Varshney, P.: ‘Distributed detection with multiple sensors Part–I. Fundamentals’, Proc. IEEE, 1997, 85, (1), pp. 54–63.
45. 45)
  - 140. Myers, V., Williams, D.: ‘Adaptive multiview target classification in synthetic aperture sonar images using a partially observable Markov decision process’, IEEE J. Ocean. Eng., 2012, 37, (1), pp. 45–55.
46. 46)
  - 88. Goldhahn, R., LePage, K., Braca, P., et al: ‘Environmentally sensitive AUV behaviors for collaborative multistatic surveillance networks’. Underwater Acoustic Signal Processing Workshop, West Greenwich, RI, USA, 16–18 October 2013.
47. 47)
  - 278. Sandell, N.F., Olfati-Saber, R.: ‘Distributed data association for multi-target tracking in sensor networks’. Proc IEEE CDC-08, Cancun, Mexico, December 2008, pp. 1085–1090.
48. 48)
  - 232. Koch, J.W.: ‘Bayesian approach to extended object and cluster tracking using random matrices’, IEEE Trans. Aerosp. Electron. Syst., 2008, 44, (3), pp. 1042–1059.
49. 49)
  - 188. Hines, P.C., Hicks, K., Murphy, S.M., et al: ‘Measurements of signal coherence for high and low duty cycle sonars in a shallow water channel’. IEEE/MTS OCEANS 2015 - Genova, 2015, pp. 1–5.
50. 50)
  - 65. Nakamura, Y.: ‘Data fusion in robotics and machine intelligence’, 1992, ch. Geometric Fusion: Minimizing Uncertainty Volumes, pp. 457–480.
51. 51)
  - 84. Bertsekas, D.: ‘Dynamic programming and optimal control’ (Athena Scientific, 2007).
52. 52)
  - 150. Dahl, P.: ‘High-frequency forward scattering from the sea surface: the characteristic scales of time and angle spreading’, IEEE J. Oceanic Eng., 2002, 26, (1), pp. 141–151.
53. 53)
  - 215. Witrisal, K., Meissner, P., Leitinger, E., et al: ‘High-accuracy localization for assisted living: 5G systems will turn multipath channels from foe to friend’, IEEE Signal Process. Mag., 2016, 33, (2), pp. 59–70.
54. 54)
  - 183. Collins, T., Atkins, P.: ‘Doppler-sensitive active sonar pulse designs for reverberation processing’, IEE Proc. Radar Sonar Navig., 1998, 145, (6), pp. 347–353.
55. 55)
  - 96. Carreras, M., Batlle, J., Ridan, P., et al: ‘An overview on behaviour-based methods for AUV control’. IFAC Conf., 1999, pp. 141–146.
56. 56)
  - 110. Grasso, R., Braca, P., Fortunati, S., et al: ‘Dynamic underwater glider network for environmental field estimation’, IEEE Trans. Aerosp. Electron. Syst., 2016, 52, (1), pp. 379–395.
57. 57)
  - 216. Leitinger, E., Meyer, F., Meissner, P., et al: ‘Belief propagation based joint probabilistic data association for multipath-assisted indoor navigation and tracking’. Proc. IEEE ICL-GNSS-16, Barcelona, Spain, June 2016.
58. 58)
  - 58. Hero, A.O., Cochran, D.: ‘Sensor management: past, present, and future’, IEEE Sens. J., 2011, 11, (12), pp. 3064–3075.
59. 59)
  - 190. Plate, R., Grimmett, D.: ‘High duty cycle (HDC) sonar processing interval and bandwidth effects for the TREX'13 dataset’. IEEE/MTS OCEANS 2015 - Genova, 2015, pp. 1–10.
60. 60)
  - 309. Moriconi, C., Cupertino, G., Betti, S., et al: ‘Hybrid acoustic/optic communications in underwater swarms’. OCEANS 2015 – Genova, May 2015, pp. 1–9.
61. 61)
  - 284. Petrioli, C., Petroccia, R., Potter, J.R., et al: ‘The SUNSET framework for simulation, emulation and at-sea testing of underwater wireless sensor networks’, Ad Hoc Netw., 2015, 34, pp. 224–238.
62. 62)
  - 103. Furfaro, T., Alves, J.: ‘An application of distributed long baseline-node ranging in an underwater network’. Underwater Communications and Networking (UComms), 2014, pp. 1–5.
63. 63)
  - 180. Gianelli, C., Xu, L., Li, J.: ‘Active sonar systems in the presence of strong direct blast’. OCEANS 2015 – Genova, May 2015, pp. 1–10.
64. 64)
  - 234. Bar-Shalom, Y., Li, X.-R.: ‘Multitarget-multisensor tracking: principles and techniques’ (Yaakov Bar-Shalom, Storrs, CT, USA, 1995).
65. 65)
  - 242. Vo, B.-N., Vo, B.-T., Phung, D.: ‘Labeled random finite sets and the Bayes multi-target tracking filter’, IEEE Trans. Signal Process., 2014, 62, (24), pp. 6554–6567.
66. 66)
  - 6. Caiti, A., Calabrò, V., Andrea, M., et al: ‘Mobile underwater sensor networks for protection and security: field experience at the UAN11 experiment’, J. Field Robot., 2013, 30, (2), pp. 237–253. Available at http://dx.doi.org/10.1002/rob.21447.
67. 67)
  - 201. Gebbie, P.N.J., Siderius, M., Miller, J.: ‘Passive localization of noise-producing targets using a compact volumetric array’, J. Acoust. Soc. Am., 2014, 136, (1), pp. 80–89.
68. 68)
  - 256. Braca, P., Willett, P., LePage, K., et al: ‘Bayesian tracking in underwater wireless sensor networks with port-starboard ambiguity’, IEEE Trans. Signal Process., 2014, 62, (7), pp. 1864–1878.
69. 69)
  - 182. Haykin, S., Xue, Y., Davidson, T.N.: ‘Optimal waveform design for cognitive radar’. 2008 42nd Asilomar Conf. Signals, Systems and Computers, 2008, pp. 3–7.
70. 70)
  - 243. Cappe, O., Godsill, S., Moulines, E.: ‘An overview of existing methods and recent advances in sequential Monte Carlo’, Proc. IEEE, 2007, 95, (5), pp. 899–924.
71. 71)
  - 8. Nootz, G., Jarosz, E., Dalgleish, F., et al: ‘Quantification of optical turbulence in the ocean and its effects on beam propagation’, Appl. Opt., 2016, 55, (31), pp. 8813–8820.
72. 72)
  - 286. NATO, STANAG 4748 Ed. A ver. 1: ‘Digital underwater signalling standard for network node discovery & interoperability’, https://nso.nato.int/nso/zPublic/ap/PROM/ANEP-87%20EDA%20V1%20E.pdf, accessed April 2017.
73. 73)
  - 224. Bar-Shalom, Y., Tse, E.: ‘Tracking in a cluttered environment with probabilistic data association’, Automatica, 1975, 11, (5), pp. 451–460.
74. 74)
  - 293. Petrioli, C., Petroccia, R., Potter, J.: ‘Performance evaluation of underwater mac protocols: From simulation to at-sea testing’. Proc. IEEE/OES OCEANS 2011, Santander, Spain, 6–9 June 2011.
75. 75)
  - 141. Williams, D.-P., Myers, V., Silvious, M.S.: ‘Mine classification with imbalanced data’, IEEE Geosci. Remote Sens. Lett., 2009, 6, (3), pp. 528–532.
76. 76)
  - 9. Karagianni, E.A.: ‘Electromagnetic waves under sea: bow-tie antenna design for Wi-Fi underwater communications’, Prog. Electromagn. Res., 2015, 41, p. 189198.
77. 77)
  - 56. Alvarez, A., Mourre, B.: ‘Optimum sampling designs for a glider-mooring observing network’, J. Atmos. Oceanic Technol., 2012, 29, pp. 601–612.
78. 78)
  - 227. Kirubarajan, T., Bar-Shalom, Y.: ‘Probabilistic data association techniques for target tracking in clutter’, Proc. IEEE, 2004, 92, (3), pp. 536–557.
79. 79)
  - 250. Williams, J.L.: ‘Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA and association-based MeMBer’, IEEE Trans. Aerosp. Electron. Syst., 2015, 51, (3), pp. 1664–1687.
80. 80)
  - 75. Schmaedeke, W.W.: ‘Information-based sensor management’. Proc. Meeting of Int. Society for Optical Engineering (SPIE), 1993, vol. 156.
81. 81)
  - 277. Hlinka, O., Hlawatsch, F., Djuric, P.: ‘Distributed particle filtering in agent networks: a survey, classification, and comparison’, IEEE Signal Process. Mag., 2013, 30, (1), pp. 61–81.
82. 82)
  - 148. Jensen, F.B., Kuperman, W.A., Porter, M.B., et al: ‘Computational ocean acoustics’ (Springer, New York, NY, USA, 2011).
83. 83)
  - 106. Moreno-Salinas, D., Pascoal, A., Aranda, J.: ‘Sensor networks for optimal target localization with bearings-only measurements in constrained three-dimensional scenarios’, Sensors, 2013, 13, pp. 10386–10417.
84. 84)
  - 203. Gebbie, J., Siderius, M., Nielsen, P., et al: ‘Small boat localization using adaptive three-dimensional beamforming on a tetrahedral and vertical line array’. Proc. Meetings on Acoustics, 2013, vol. 19.
85. 85)
  - 220. Fortmann, T., Bar-Shalom, Y., Scheffe, M.: ‘Sonar tracking of multiple targets using joint probabilistic data association’, IEEE J. Ocean. Eng., 1983, 8, (3), pp. 173–184.
86. 86)
  - 120. Antonelli, G., Arrichiello, F., Chiaverini, S.: ‘The null-space-based behavioral control for mobile robots’. IEEE Computational Intelligence in Robotics and Automation (CIRA2005), 2005.
87. 87)
  - 298. Basagni, S., Petrioli, C., Petroccia, R., et al: ‘CARP: a channel-aware routing protocol for underwater acoustic wireless networks’, Ad Hoc Netw., 2015, 34, pp. 92–104.
88. 88)
  - 30. Potter, J.R., Alves, J., Green, D., et al: ‘The JANUS underwater communications standard’. Proc. 2nd IEEE OES Int. Conf. on Underwater Communications and Networking, ser. UComms'14, Sestri Levante, Italy, 3–5 September 2014.
89. 89)
  - 213. Genovesio, A., Liedl, T., Emiliani, V., et al: ‘Multiple particle tracking in 3-D+t microscopy: method and application to the tracking of endocytosed quantum dots’, IEEE Trans. Image Process., 2006, 15, (5), pp. 1062–1070.
90. 90)
  - 54. Ferri, G., Munafò, A., Alves, J., et al: ‘A data-driven control strategy in synergy with continuous active sonar for littoral underwater surveillance’. OCEANS 2016 MTS/IEEE Monterey, September 2016, pp. 1–7.
91. 91)
  - 139. Williams, D., Fakiris, E.: ‘Exploiting environmental information for improved underwater target classification in sonar imagery’, IEEE Trans. Geosci. Remote Sens., 2014, 52, (10), pp. 6284–6297.
92. 92)
  - 126. Parker, L.E.: ‘ALLIANCE: an architecture for fault-tolerant multi-robot cooperation’, IEEE Trans. Robot. Autom., 1998, 14, (2), pp. 220–240.
93. 93)
  - 166. Le Chevalier, F., Montecot, M., Doisy, Y., et al: ‘STAP developments in Thales’. Radar Conf., 2009. EuRAD 2009. European, 2009, pp. 53–56.
94. 94)
  - 317. Lal, C., Petroccia, R., Conti, M., et al: ‘Secure underwater acoustic networks: current and future research directions’. Proc. 3rd IEEE OES Int. Conf. on Underwater Communications and Networking, ser. UComms16, Lerici, Italy, 30 August–1 September 2016.
95. 95)
  - 174. Cox, H.: ‘Fundamentals of bistatic active sonar’, in ‘Underwater acoustic data processing’ (Springer, 1989), pp. 3–24.
96. 96)
  - 221. Bar-Shalom, Y., Willett, P.K., Tian, X.: ‘Tracking and data fusion: a handbook of algorithms’ (Yaakov Bar-Shalom, Storrs, CT, USA, 2011).
97. 97)
  - 164. Li, W., Chen, G., Blasch, E., et al: ‘Cognitive MIMO sonar based robust target detection for harbor and maritime surveillance applications’. IEEE Aerospace Conf., March 2009, vol. 54, (3), pp. 1–9.
98. 98)
  - 80. Kreucher, C., Kastella, K., Hero, A.O.: ‘Information based sensor management for multitarget tracking’. Meeting of Int. Society for Optical Engineering (SPIE), San Diego, 2003.
99. 99)
  - 102. Allotta, B., Caiti, A., Chisci, L., et al: ‘An unscented kalman filter based navigation algorithm for autonomous underwater vehicles’, Mechatronics, 2016, 39, pp. 185–195.
100. 100)
  - 318. Pelekanakis, K., Cazzanti, L., Zappa, G., et al: ‘Decision tree-based adaptive modulation for underwater acoustic communications’. IEEE OES Third Underwater Communications and Networking Conf., ser. UComms'16, 30 August–1 September 2016, pp. 1–5.
101. 101)
  - 118. Lagoudakis, M., Markakis, E., Kempe, D., et al: ‘Auction-based multi-robot routing’. Robotics: Science and Systems, 2005.
102. 102)
  - 87. Bertsekas, D.: ‘Dynamic programming and suboptimal control: a survey from ADP to MPC’. Proc. of the Conf. Decision and Control, 2005.
103. 103)
  - 5. Caiti, A., Munafò, A., Vettori, G.: ‘A geographical information system (GIS)-based simulation tool to assess civilian harbor protection levels’, IEEE J. Ocean. Eng., 2012, 37, (1), pp. 85–102.
104. 104)
  - 244. Morelande, M.R., Kreucher, C.M., Kastella, K.: ‘A Bayesian approach to multiple target detection and tracking’, IEEE Trans. Signal Process., 2007, 55, (5), pp. 1589–1604.
105. 105)
  - 251. Meyer, F., Braca, P., Willett, P., et al: ‘Scalable multitarget tracking using multiple sensors: a belief propagation approach’. Proc. FUSION-15, Washington, DC, USA, July 2015, pp. 1778–1785.
106. 106)
  - 114. Caiti, A., Munafò, A., Viviani, R.: ‘Adaptive on-line planning of environmental sampling missions with a team of cooperating autonomous underwater vehicles’, Int. J. Control, 2007, 80, (7), pp. 1151–1168.
107. 107)
  - 57. Lermusiaux, P., Tapovan, L., Haley, P., et al: ‘Handbook of ocean engineering’ (Springer Dordrecht Heidelberg London New York, 2016), ch. Science of autonomy: Time-Optimal Path Planning and Adaptive Sampling for Swarms of Ocean Vehicles.
108. 108)
  - 125. Werger, B., Mataric, M.: ‘Broadcast of local eligibility: behavior-based control for strongly cooperative robot teams’. 4th Int. Conf. Autonomous Agents (AGENTS 2000), 2000.
109. 109)
  - 89. LePage, K., Hamilton, M., Kemna, S.: ‘Autonomous underwater vehicles for active multistatic undersea surveillance’. Proc. 4th Int. Conf. Underwater Acoustic Measurements: Technologies and Results, Kos, Greece, June 2011, pp. 1471–1478.
110. 110)
  - 94. Balch, T., Arkin, R.: ‘Behavior-based formation control for multi-robot teams’, IEEE Trans. Robot. Autom., 1998, 14, (6), pp. 926–939.
111. 111)
  - 47. Pebody, M.: ‘Autonomous underwater vehicle collision avoidance for under-ice exploration’, Proc. IME M J. Eng. Marit. Environ., 2009, 222, pp. 53–66.
112. 112)
  - 33. Burgard, W., Moors, M., Stachniss, C., et al: ‘Coordinated multi-robot exploration’, IEEE Trans. Robot., 2005, 21, (3), pp. 376–386.
113. 113)
  - 307. Incio, S.I., Pereira, M.R., Santos, H.M., et al: ‘Dipole antenna for underwater radio communications’. 2016 IEEE Third Underwater Communications and Networking Conf. (UComms), August 2016, pp. 1–5.
114. 114)
  - 36. Antonelli, G., Arrichiello, F., Casalino, G., et al: ‘Harbour protection strategies with multiple autonomous marine vehicles’ (Springer International Publishing, Cham, 2014), pp. 241–261. doi: 10.1007/978-3-319-13823-722.
115. 115)
  - 28. Schmidt, H., Benjamin, M., Petillo, S., et al: ‘Handbook of ocean engineering’ (Springer Dordrecht Heidelberg London New York, 2016), ch. Nested autonomy for distributed ocean sensing, pp. 459–479.
116. 116)
  - 275. Olfati-Saber, R.: ‘Distributed Kalman filtering for sensor networks’. Proc IEEE CDC-07, New Orleans, LA, USA, December 2007, pp. 5492–5498.
117. 117)
  - 235. Mahler, R.P.S.: ‘Multitarget Bayes filtering via first-order multitarget moments’, IEEE Trans. Aerosp. Electron. Syst., 2003, 39, (4), pp. 1152–1178.
118. 118)
  - 165. Krim, H., Viberg, M.: ‘Two decades of array signal processing research: the parametric approach’, IEEE Signal Process. Mag., 1996, 13, (4), pp. 67–94.
119. 119)
  - 303. Pontbriand, C., Farr, N., Preisig, J.W.J., et al: ‘Diffuse high-bandwidth optical communications’. Proc. MTS/IEEE OCEANS 2008, Quebec City, QC, Canada, 15–18 September 2008.
120. 120)
  - 197. Tesei, A., Fioravanti, S., Grandi, V., et al: ‘Localization of small surface vessels through acoustic data fusion of two tetrahedral arrays of hydrophones’. Proc. of Meetings on Acoustics, 2012, vol. 17.
121. 121)
  - 222. Sittler, R.W.: ‘An optimal data association problem in surveillance theory’, IEEE Trans. Military Electron., 1964, 8, (2), pp. 125–139.
122. 122)
  - 291. Chitre, M., Shahabudeen, S., Stojanovic, M.: ‘Underwater acoustic communications and networking: recent advances and future challenges’, Mar. Technol. Soc. J., 2008, 42, (1), pp. 103–116.
123. 123)
  - 163. Baldacci, A., Haralabus, G.: ‘Signal processing for an active sonar system suitable for advanced sensor technology applications and environmental adaptation schemes’. 14th European Signal Processing Conf., 2006, pp. 1–5.
124. 124)
  - 10. Gerken, L.: ‘ASW versus submarine technology battle’ (A. S. Corp, Ed., 1987).
125. 125)
  - 294. Di Valerio, V., Lo Presti, F., Petrioli, C., et al: ‘A self-adaptive protocol stack for underwater wireless sensor networks’. Proc. MTS/IEEE OCEANS 2016, Shanghai, China, 10–13 April 2016, pp. 1–8.
126. 126)
  - 158. Kincaid, T.: ‘Optimum waveforms for correlation detection in the sonar environment: noiselimited conditions’, J. Acoust. Soc. Am., 1968, 43, (2), pp. 258–268.
127. 127)
  - 281. Sendra, S., Lloret, J., Jimenez, J.M., et al: ‘Underwater acoustic modems’, IEEE Sens. J., 2016, 16, (11), pp. 4063–4071.
128. 128)
  - 155. Catipovic, J.: ‘Performance limitations in underwater acoustic telemetry’, IEEE J. Ocean. Eng., 1990, 15, (3), pp. 205–216.
129. 129)
  - 223. Bar-Shalom, Y.: ‘Tracking methods in a multitarget environment’, IEEE Trans. Autom. Control, 1978, 23, (4), pp. 618–626.
130. 130)
  - 184. Kershaw, D.J., Evans, R.J.: ‘Optimal waveform selection for tracking systems’, IEEE Trans. Inf. Theory, 1994, 40, (5), pp. 1536–1550.
131. 131)
  - 299. Braga, J., Martins, R., Petrioli, C., et al: ‘Cooperation and networking in an underwater network composed by heterogeneous assets’. Proc. of MTS/IEEE OCEANS 2016, Monterey, CA, USA, 19–23 September 2016, pp. 1–9.
132. 132)
  - 4. Cresta, M., Storti, E., Simetti, E., et al: ‘Archimede: integrated network-centric harbour protection system’. 2010 Int. WaterSide Security Conf., November 2010, pp. 1–4.
133. 133)
  - 123. Bertsekas, D.: ‘Dynamic programming and suboptimal control: a survey from ADP to MPC’, Eur. J. Control, 2005, 11, pp. 310–334.
134. 134)
  - 159. Haykin, S.: ‘Cognitive radar: a way of the future’, IEEE Signal Process. Mag., 2006, 23, (1), pp. 30–40.
135. 135)
  - 43. Murphy, R.: ‘Introduction to AI robotics’ (MIT Press, 2000).
136. 136)
  - 98. Evans, J., Sotzing, C.C., Patrón, P., et al: ‘Cooperative planning architectures for multi-vehicle autonomous operations’. Proc. of the 1st SEAS DTC Technical Conf., 2006.
137. 137)
  - 59. Dias, M., Stentz, A.: ‘A market approach to multirobot coordination’. CMU-RI-TR-01-26, Technical Report, The Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania, 2001.
138. 138)
  - 39. Ferri, G., Munafò, A., Goldhahn, R., et al: ‘Towards fully autonomous underwater vehicles in ASW scenarios: an adaptive, data driven AUV mission manager layer’. OCEANS 2015, Genova, Italy, 18–21 May 2015.
139. 139)
  - 249. Williams, J.L., Lau, R.: ‘Approximate evaluation of marginal association probabilities with belief propagation’, IEEE Trans. Aerosp. Electron. Syst., 2014, 50, (4), pp. 2942–2959.
140. 140)
  - 308. Farr, N., Bowen, A., Ware, J., et al: ‘An integrated, underwater optical/acoustic communications system’. Proc. IEEE OCEANS 2010, Sydney, Australia, 24–27 May 2010, pp. 1–9.
141. 141)
  - 17. Webb, D.C., Simonetti, P.J., Jones, C.P.: ‘SLOCUM: an underwater glider propelled by environmental energy’, IEEE J. Ocean. Eng., 2001, 26, (4), pp. 447–452.
142. 142)
  - 236. Vo, B.-N., Singh, S., Doucet, A.: ‘Sequential Monte Carlo methods for multitarget filtering with random finite sets’, IEEE Trans. Aerosp. Electron. Syst., 2005, 41, (4), pp. 1224–1245.
143. 143)
  - 246. Yedidia, J., Freeman, W.T., Weiss, Y.: ‘Constructing free-energy approximations and generalized belief propagation algorithms’, IEEE Trans. Inf. Theory, 2005, 51, (7), pp. 2282–2312.
144. 144)
  - 207. Meyer, F., Braca, P., Willett, P., et al: ‘A scalable algorithm for tracking an unknown number of targets using multiple sensors’, IEEE Trans. Signal Process., 2017, 65, pp. 3478–3493. Available at http://arxiv.org/abs/1607.07647v1.
145. 145)
  - 157. Abraham, D.A., Willett, P.K.: ‘Active sonar detection in shallow water using the page test’, IEEE J. Ocean. Eng., 2002, 27, (1), pp. 35–46.
146. 146)
  - 121. Mosteo, A.R., Montano, L.: ‘A survey of multi-robot task allocation’. AMI-009-10-TEC, Technical Report, University of Zaragoza, 2010.
147. 147)
  - 142. Bittle, M., Duncan, A.: ‘A review of current marine mammal detection and classification algorithms for use in automated passive acoustic monitoring’. Proc. Acoustics, 2013, vol. 2013.
148. 148)
  - 267. Blum, R., Kassam, S., Poor, V.: ‘Distributed detection with multiple sensors Part–II. Advanced topics’, Proc. IEEE, 1997, 85, (1), pp. 64–79.
149. 149)
  - 296. Alves, J., Petroccia, R., Potter, J.R.: ‘MPR: multi-point relay protocol for underwater acoustic networks’. Proc. 9th ACM Int. Conf. on Underwater Networks and Systems, ser. WUWNet'14, Rome, Italy, 12–14 November 2014.
150. 150)
  - 112. Paley, D.: ‘Cooperative control of collective motion for ocean sampling with autonomous vehicles’. PhD dissertation, Princeton University, 2007.
151. 151)
  - 44. Rajan, K.: ‘The role of deliberation (and AI) in marine robots’. Workshop on Marine Robotics: Looking into the Crystal Ball, Eurocast 2013, Gran Canaria, Spain, 11–13 February 2013.
152. 152)
  - 310. Campagnaro, F., Guerra, F., Favaro, F., et al: ‘Simulation of a multimodal wireless remote control system for underwater vehicles’. Proc. 10th ACM Int. Workshop on UnderWater Networks, ser. WUWNet'15, Washington DC, USA, 22–24 October 2015.
153. 153)
  - 92. Munafò, A., Ferri, G., LePage, K.: ‘AUV active perception; exploiting the water column’. OCEANS 2017, Aberdeen, UK, 2017.
154. 154)
  - 194. Abraham, D.A., Hines, P.C.: ‘Effect of pulse duration on echo matched-filter statistics in a shallow-water channel’, IEEE J. Ocean. Eng., 2016, 42, (2), pp. 319–334.
155. 155)
  - 287. Petroccia, R., Alves, J., Zappa, G.: ‘Fostering the use of JANUS in operationally-relevant underwater applications’. Proc. 3rd IEEE OES Int. Conf. on Underwater Communications and Networking, ser. UComms16, Lerici, Italy, 30 August–1 September 2016.
156. 156)
  - 230. Kirubarajan, T., Barshalom, Y., Pattipati, K., et al: ‘Ground target tracking with variable structure IMM estimator’, IEEE Trans. Aerosp. Electron. Syst., 2000, 36, (1), pp. 26–46.
157. 157)
  - 241. Vo, B.-T., Vo, B.-N.: ‘Labeled random finite sets and multi-object conjugate priors’, IEEE Trans. Signal Process., 2013, 61, (13), pp. 3460–3475.
158. 158)
  - 252. Meyer, F., Braca, P., Willett, P., et al: ‘Tracking an unknown number of targets using multiple sensors: a belief propagation method’. Proc. FUSION-16, Heidelberg, Germany, July 2016.
159. 159)
  - 168. Kim, K.M., Lee, C., Youn, D.H.: ‘Adaptive processing technique for enhanced CFAR detecting performance in active sonar systems’, IEEE Trans. Aerosp. Electron. Syst., 2000, 36, (2), pp. 693–700.
160. 160)
  - 74. Manyika, J.M., Durrant-Whyte, H.F.: ‘Information-theoretic approach to management in decentralized data fusion’. Proc. Meeting of Int. Soc. for Optical Engineering (SPIE), 1992, vol. 202.
161. 161)
  - 264. Bajovic, D., Jakovetic, D., Xavier, J., et al: ‘Distributed detection via Gaussian running consensus: large deviations asymptotic analysis’, IEEE Trans. Signal Process., 2011, 59, (9), pp. 4381–4396.
162. 162)
  - 192. Murphy, S., Hines, P.: ‘Sub-band processing of continuous active sonar signals in shallow water’. OCEANS 2015 - Genova, 2015.
163. 163)
  - 151. Siderius, M., Porter, M.B.: ‘Modeling broadband ocean acoustic transmissions with time-varying sea surfaces’, J. Acoust. Soc. Am., 2008, 124, (1), pp. 137–150.
164. 164)
  - 217. Urmson, C., Anhalt, J., Bagnell, D., et al: ‘Autonomous driving in urban environments: boss and the urban challenge’, J. Field Robot., 2008, 25, (8), pp. 425–466.
165. 165)
  - 135. Nielsen, R.: ‘Sonar signal processing’ (Artech House, Inc., 1991).
166. 166)
  - 205. Watkins, W., Schevill, W.: ‘Four hydrophone array for acoustic threedimensional location’. Technical Report Rep 71-60, Woods Hole Oceanographic Institute, October 1971.
167. 167)
  - 255. Kay, S.M.: ‘Fundamentals of statistical signal processing: estimation theory’ (Prentice-Hall, Upper Saddle River, NJ, USA, 1993).
168. 168)
  - 154. Knight, W.C., Pridham, R.G., Kay, S.M.: ‘Digital signal processing for sonar’, Proc. IEEE, 1981, 69, (11), pp. 1451–1506.
169. 169)
  - 42. Ferri, G., Munafò, A., Goldhahn, R., et al: ‘A non-myopic, receding horizon control strategy for an AUV to track an underwater target in a bistatic sonar scenario’. Proc. CDC2014, Los Angeles, 15–17 December 2014.
170. 170)
  - 169. Mio, K., Chocheyras, Y., Doisy, Y.: ‘Space time adaptive processing for low frequency sonar’. OCEANS 2000 MTS/IEEE Conf. and Exhibition, 2000, vol. 2, pp. 1315–1319.
171. 171)
  - 146. Sildam, J., Ehlers, F.: ‘Supervised track classification in support of AUV decision making’. Proc. UAM 2011, 2011.
172. 172)
  - 312. van Walree, P.A., Leus, G.: ‘Robust underwater telemetry with adaptive turbo multiband equalization’, IEEE J. Ocean. Eng., 2009, 34, (4), p. 645.
173. 173)
  - 219. Reuter, S., Dietmayer, K.: ‘Pedestrian tracking using random finite sets’. Proc. FUSION-11, Chicago, IL, USA, July 2011.
174. 174)
  - 34. Hollinger, G., Sukhatme, G.: ‘Sampling-based robotic information gathering algorithms’, Int. J. Robot. Res., 2014, 33, (9), pp. 1271–1287.
175. 175)
  - 78. Charrow, B., Liu, S., Kumar, V., et al: ‘Information-theoretic mapping using cauchy-schwarz quadratic mutual information’. 2015 IEEE Int. Conf. Robotics and Automation (ICRA), May 2015, pp. 4791–4798.
176. 176)
  - 131. Tsiogkas, N., Papadimitriou, G., Saigol, Z., et al: ‘Efficient multi-AUV cooperation using semantic knowledge representation for underwater archaeology missions’. Oceans – St. John's 2014, 2014.
177. 177)
  - 7. ‘The navy unmanned undersea vehicle UUV master plan’. Technical Report, US Navy, 2004.
178. 178)
  - 72. Kangsheng, T., Zhu, G.: ‘Sensor management based on fisher information gain’, J. Syst. Eng. Electron., 2006, 17, (3), pp. 531–534.
179. 179)
  - 290. Melodia, T., Khulandjian, H., Kuo, L.-C., et al: ‘Advances in underwater acoustic networking’, in Basagni, S., Conti, M., Giordano, S., Stojmenovic, I. (Eds.): ‘Mobile ad hoc networking: cutting edge directions’ (John Wiley & Sons, Inc., Hoboken, NJ, 2013), ch. 23, pp. 804–852.
180. 180)
  - 179. Grimmett, D.: ‘Automatic identification of specular detections in multistatic sonar systems’. OCEANS 2009, 2009, pp. 1–10.
181. 181)
  - 147. Canepa, G., Munafò, A., Micheli, M., et al: ‘Real-time continuous active sonar processing’. IEEE/MTS OCEANS 2015 – Genova, 2015, pp. 1–6.
182. 182)
  - 265. Braca, P., Marano, S., Matta, V.: ‘Single-transmission distributed detection via order statistics’, IEEE Trans. Signal Process., 2012, 60, (4), pp. 2042–2048.
183. 183)
  - 162. Claussen, T., Nguyen, V.: ‘Real-time cognitive sonar system with target-optimized adaptive signal processing through multi-layer data fusion’. IEEE Int. Conf. Multisensor Fusion and lntegration for Intelligent Systems (MFI), September 2006.
184. 184)
  - 274. Matta, V., Braca, P., Marano, S., et al: ‘Distributed detection over adaptive networks: refined asymptotics and the role of connectivity’, IEEE Trans. Signal Inf. Process. Netw., 2016, 2, (4), pp. 442–460.
185. 185)
  - 257. Schuhmacher, D., Vo, B.-T., Vo, B.-N.: ‘A consistent metric for performance evaluation of multi-object filters’, IEEE Trans. Signal Process., 2008, 56, (8), pp. 3447–3457.
186. 186)
  - 300. Fall, K.: ‘A delay-tolerant network architecture for challenged internets’. Proc. 2003 Conf. on Applications, Technologies, Architectures, and Protocols for Computer Communications, ser. SIGCOMM'03, 25–29 August 2003, pp. 27–34.
187. 187)
  - 301. Merani, D., Berni, A., Potter, J., et al: ‘An underwater convergence layer for disruption tolerant networking’. 2011 Baltic Congress on Future Internet and Communications, 16–18 February 2011, pp. 103–108.
188. 188)
  - 311. Park, J.H.: ‘LPI techniques in the underwater acoustic channel’. Military Communications Conf. – Communications-Computers: Teamed for the 90's, 1986. MILCOM 1986. IEEE, October 1986, vol. 1, pp. 10.5.1–10.5.5.
189. 189)
  - 117. Stentz, A., Dias, B.: ‘A free market architecture for coordinating multiple robots’. CMURI-TR-99-42, Technical Report, 1999.
190. 190)
  - 14. Stommel, H.: ‘The Slocum mission’, Oceanography, 1989, 2, pp. 22–25.
191. 191)
  - 11. Stojanovic, M.: ‘On the relationship between capacity and distance in an underwater acoustic communication channel’. Proc. 1st ACM Int. Workshop on Underwater Networks, ser. WUWNet ‘06, New York, NY, USA, 2006, pp. 41–47. doi: 10.1145/1161039.1161049.
192. 192)
  - 306. Che, X., Wells, I., Dickers, G., et al: ‘Re-evaluation of rf electromagnetic communication in underwater sensor networks’, IEEE Commun. Mag., 2010, 48, (12), pp. 143–151.
193. 193)
  - 104. Munafò, A., Furfaro, T., Ferri, G., et al: ‘Supporting auv localisation through next generation underwater acoustic networks: Results from the field’. 2016 IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), October 2016, pp. 1328–1333.
194. 194)
  - 70. Munafò, A., Sliwka, J., Alves, J.: ‘Dynamic placement of a constellation of surface buoys for enhanced underwater positioning’. OCEANS 2015, Genova, 18–21 May 2015.
195. 195)
  - 35. Portugal, D., Rocha, R.: ‘A survey on multi-robot patrolling algorithms’. Proc. Second IFIP WG 5.5/SOCOLNET Doctoral Conf. Computing, Electrical and Industrial Systems, DoCEIS 2011, Costa de Caparica, Portugal, 21–23 February 2011.
196. 196)
  - 82. Zhang, G., Ferrari, S., Qian, M.: ‘An information roadmap method for robotic sensor path planning’, J. Intell. Robotic Syst., 2009, 56, (1), pp. 69–98.
197. 197)
  - 208. Lo, K., Ferguson, B., Gao, Y., et al: ‘Dynamic Cramér-Rao bound for target tracking in clutter’, IEEE Trans. Aerosp. Electron. Syst., 2003, 39, (1), pp. 259–268.
198. 198)
  - 145. Murphy, P., Hines, S.M., Dunphy, K.: ‘Classifying continuous active sonar echoes for target recognition’. Proc. 2nd Int. Conf. and Exhibition on Underwater Acoustics, 2014, pp. 811–818.
199. 199)
  - 45. Wynn, R.B., Huvenne, V.A., Bas, T.P.L., et al: ‘Autonomous underwater vehicles (AUVs): their past, present and future contributions to the advancement of marine geoscience’, Mar. Geol., 2014, 352, pp. 451–468, 50th Anniversary Special Issue. Available at http://www.sciencedirect.com/science/article/pii/S0025322714000747.
200. 200)
  - 313. Lai, L., Liang, Y., Poor, H.V.: ‘A unified framework for key agreement over wireless fading channels’, IEEE Trans. Inf. Forensics Sec., 2012, 7, (2), pp. 480–490.
201. 201)
  - 173. Hamilton, M.J., Kemna, S., Hughes, D.: ‘Antisubmarine warfare applications for autonomous underwater vehicles: the GLINT09 sea trial results’, J. Field Robot., 2010, 27, (6), pp. 890–902.
202. 202)
  - 273. Matta, V., Braca, P., Marano, S., et al: ‘Diffusion-based adaptive distributed detection: steady-state performance in the slow adaptation regime’, IEEE Trans. Inf. Theory, 2016, 62, (8), pp. 4710–4732.
203. 203)
  - 2. Polmar, N., Whitman, E.: ‘Hunters and killers: volume 2: anti-submarine warfare from 1943’ (Naval Institute Press, 2016).
204. 204)
  - 85. Page, S.: ‘Multiple-objective sensor management and optimisation’. PhD dissertation, University of Southampton, Southampton, UK, 2009.
205. 205)
  - 199. André, M.: ‘Ocean noise: composing soundscapes from real-time acoustic data streams’, Introducing Noise into the Marine Environment – What Are the Requirements for an Impact Assessment, 2014, 6, p. 95.
206. 206)
  - 111. Leonard, N., Paley, D., Davis, R., et al: ‘Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in Monterey Bay’, J. Field Robot., 2010, 27, (6), pp. 718–740.
207. 207)
  - 115. Garau, B., Bonet, M., Alvarez, A., et al: ‘Path planning for autonomous underwater vehicles in realistic oceanic currents field: application to gliders in the western Mediterranean sea’, J. Marit. Res., 2009, 6, (2), pp. 5–22.
208. 208)
  - 316. Dini, G., Duca, A.L.: ‘A secure communication suite for underwater acoustic sensor networks’, Sensors, 2012, 12, (11), pp. 15133–15158.
209. 209)
  - 79. Grocholsky, B.: ‘Information-theoretic control of multiple sensor platforms’. PhD dissertation, Australian Centre for Field Robotics, 2002.
210. 210)
  - 25. http://liquidr.com/.
211. 211)
  - 238. Braca, P., Marano, S., Matta, V., et al: ‘Asymptotic efficiency of the PHD in multitarget/multisensor estimation’, IEEE J. Sel. Topics Signal Process., 2013, 7, (3), pp. 553–564.
212. 212)
  - 268. Boyd, S., Ghosh, A., Prabhakar, B., et al: ‘Randomized gossip algorithms’, IEEE Trans. Inf. Theory, 2006, 52, (6), pp. 2508–2530.
213. 213)
  - 248. Chen, Z., Chen, L., Cetin, M., et al: ‘An efficient message passing algorithm for multi-target tracking’. Proc. FUSION-09, Seattle, WA, USA, July 2009, pp. 826–833.
214. 214)
  - 113. Paley, D., Zhang, F., Leonard, N.: ‘Cooperative control for ocean sampling: The glider coordinated control system’, IEEE Trans. Control Syst. Technol., 2008, 16, (4), p. 735744.
215. 215)
  - 185. Doisy, Y., Deruaz, L., van IJsselmuide, S.P., et al: ‘Reverberation suppression using wideband Doppler-sensitive pulses’, IEEE J. Ocean. Eng., 2008, 33, (4), pp. 419–433.
216. 216)
  - 63. Chhetri, A.S., Morrell, D., Papandreou-Suppappola, A.: ‘Nonmyopic sensor scheduling and its efficient implementation for target tracking applications’, EURASIP J. Appl. Signal Process., 2006, 2006, pp. 1–18.
217. 217)
  - 86. Thrun, S., Burgard, W., Fox, D.: ‘Probabilistic robotics’ (The MIT Press, Cambridge, MA, USA, 2005).
218. 218)
  - 218. Levinson, J., Askeland, J., Becker, J., et al: ‘Towards fully autonomous driving: systems and algorithms’. Proc. IEEE IV 2011, Baden-Baden, Germany, June 2011, pp. 163–168.
219. 219)
  - 171. Klemm, R.: ‘Principles of space-time adaptive processing’ (IET, 2002), no. 159.
220. 220)
  - 214. Mullane, J., Vo, B.-N., Adams, M., et al: ‘Random finite sets for robot mapping and SLAM – new concepts in autonomous robotic map representations’ (Springer, 2011), vol. 72, ser. Springer Tracts in Advanced Robotics.
221. 221)
  - 3. Williams, D., Couillard, M.: ‘Efficient dense sonar surveys with an autonomous underwater vehicle’. Proc. 11th European Conf. on Underwater Acoustics (ECUA), 2012.
222. 222)
  - 22. Ferri, G., Munafò, A., Goldhahn, R., et al: ‘Results from COLLAB13 sea trial on tracking underwater targets with AUVs in bistatic sonar scenarios’. Oceans – St. John's, 2014, September 2014, pp. 1–9.
223. 223)
  - 99. McGann, C., Py, F., Rajan, K., et al: ‘A deliberative architecture for AUV control’. ICRA 2008, Pasadena, CA, 2008.
224. 224)
  - 253. Coraluppi, S., Grimmett, D., Theije, P.D.: ‘Benchmark evaluation of multistatic trackers’. Proc. FUSION-06, Florence, Italy, July 2006.
225. 225)
  - 55. Ferri, G., Jakuba, M., Yoerger, D.: ‘A novel trigger-based method for hydrothermal vents prospecting using an autonomous underwater robot’, Auton. Robots, 2010, 29, (1), pp. 67–83.
226. 226)
  - 315. Huang, Y., Zhou, S., Shi, Z., et al: ‘Channel frequency response-based secret key generation in underwater acoustic systems’, IEEE Trans. Wirel. Commun., 2016, 15, (9), pp. 5875–5888.
227. 227)
  - 21. Hughes, D.T., Baralli, F., Kemna, S., et al: ‘Collaborative multistatic ASW using AUVs: demonstrating necessary technologies’. Technical Report, Nato Undersea Research Centre, 2009.
228. 228)
  - 167. van Ijsselmuide, S., Deruaz, L., Been, R., et al: ‘Sonar waveforms for reverberation rejection, part IV: adaptive processing’. UDT Europe-Conf. Proc. Undersea Defence Technology, La Spezia, Italy, 18–21 June 2002.
229. 229)
  - 116. Caiti, A., Fabbri, T., Fenucci, D., et al: ‘Potential games and AUVs cooperation: First results from the THESAURUS project’. 2013 MTS/IEEE OCEANS – Bergen, June 2013, pp. 1–6.
230. 230)
  - 212. Adrian, R.J.: ‘Particle-imaging techniques for experimental fluid mechanics’, Annu. Rev. Fluid Mech., 1991, 23, (1), pp. 261–304.
231. 231)
  - 279. Battistelli, G., Chisci, L., Fantacci, C., et al: ‘Consensus CPHD filter for distributed multitarget tracking’, IEEE J. Sel. Topics Signal Process., 2013, 7, (3), pp. 508–520.
232. 232)
  - 101. Benjamin, M.R., Schmidt, H., Newman, P.M., et al: ‘Nested autonomy for unmanned marine vehicles with MOOS-IVP’, J. Field Robot., 2010, 27, (6), pp. 834–875. doi: 10.1002/rob.20370.
233. 233)
  - 175. Mozzone, L., Bongi, S., Filocca, F.: ‘Diversity in multistatic active sonar’. MTS/IEEE OCEANS'99. IEEE, 1999, vol. 2, pp. 1058–1063.
234. 234)
  - 283. Potter, J.R., Alves, J., Furfaro, T., et al: ‘Software defined open architecture modem development at CMRE’. Proc. of the 2nd IEEE OES Int. Conf. on Underwater Communications and Networking, ser. UComms'14, Sestri Levante, Italy, 3–5 September 2014.
235. 235)
  - 297. Jurdak, R., Ruzzelli, A.G., O'Hare, G.M.P.: ‘Design considerations for deploying underwater sensor networks’. Proc. of SensorComm 2007, 14–20 October 2007, pp. 227–232.
236. 236)
  - 153. Costas, J.: ‘Medium constraints on sonar design and performance’, IEEE Trans. Aerosp. Electron. Syst., 1975, 11, (5), pp. 973–973..
237. 237)
  - 280. Pelekanakis, K., Baggeroer, A.B.: ‘Exploiting space-time-frequency diversity with mimo-ofdm for underwater acoustic communications’, IEEE J. Ocean. Eng., 2011, 36, (4), pp. 502–513.
238. 238)
  - 292. Chen, K., Ma, M., Cheng, E., et al: ‘A survey on mac protocols for underwater wireless sensor networks’, IEEE Commun. Surv. Tutor., 2014, 16, (3), pp. 1433–1447.
239. 239)
  - 108. Alvarez, A., Mourre, B.: ‘Oceanographic field estimates from remote sensing and glider fleets’, J. Atmos. Ocean. Technol., 2012, 29, (11), pp. 1657–1662.
240. 240)
  - 48. McPhail, S.: ‘Autosub6000: a deep diving long range AUV’, J. Bionic Eng., 2009, 6, pp. 55–62.
241. 241)
  - 239. Vo, B.-T., Vo, B.-N., Cantoni, A.: ‘Analytic implementations of the cardinalized probability hypothesis density filter’, IEEE Trans. Signal Process., 2007, 55, (7), pp. 3553–3567.
242. 242)
  - 258. Braca, P., Goldhahn, R., Ferri, G., et al: ‘Distributed information fusion in multistatic sensor networks for underwater surveillance’, IEEE Sens. J., 2016, 16, (11), pp. 4003–4014.
243. 243)
  - 152. Wenz, G.: ‘Acoustic ambient noise in the ocean: spectra and sources’, J. Acoust. Soc. Am., 1962, 34, (12), pp. 1936–1956.
244. 244)
  - 93. Armbrust, C., Cubber, G.D., Berns, K.: ‘Field and assistive robotics – advances in systems and algorithms’ (Shaker Verlag), ch. ICARUS Control Systems for Search and Rescue Robots, pp. 1–16.
245. 245)
  - 81. Kreucher, C., Kastella, K., Hero, A.O.: ‘A Bayesian method for integrated multitarget tracking and sensor management’. Proc. 6th Int. Conf. Information Fusion, Cairns, QLD, Australia, 2003, pp. 132–139.
246. 246)
  - 172. Zimmerman, M., Coolidge, M., Lapisky, E.: ‘3-D sonar system’. US Patent App. 11/581,626, October 2006.
247. 247)
  - 26. Bellingham, J.: ‘Handbook of ocean engineering’ (Springer Dordrecht Heidelberg London New York, 2016), ch. Autonomous Underwater Vehicle Docking, pp. 387–422.
248. 248)
  - 186. Doisy, Y., Deruaz, L., Beerens, S.P., et al: ‘Target Doppler estimation using wideband frequency modulated signals’, IEEE Trans. Signal Process., 2000, 48, (5), pp. 1213–1224.
249. 249)
  - 37. Sildam, J., LePage, K., Braca, P., et al: ‘On unsupervised track classification based on entropy distribution estimated along track related detections’. 1st Int. Conf. and Exhibition on Underwater Acoustics, Corfu, Greece, 2013.
250. 250)
  - 16. ‘Background links for ups experiment (underwater persistent surveillence)’, Available at http://www3.mbari.org/MB2006/UPS/mb2006-ups-links.htm, accessed 11 May 2017.
251. 251)
  - 204. Hassad, J., Boucher, R.: ‘Optimum estimation of time delay by a generalized correlator’, IEEE Trans. Acoust. Speech Signal Process., 1979, 27, (4), pp. 373–380.
252. 252)
  - 196. Pailhas, Y., Petillot, Y.: ‘Neither PAS nor CAS: MIMO’. IEEE OCEANS 2016 - Shanghai, 2016, pp. 1–4.
253. 253)
  - 198. Soares, C., Jesus, S., Hursky, P., et al: ‘Random array of drifting acoustic receivers (RADAR'07)’. CINTAL – SiPLAB, Technical Report Rep 04/07, December 2007.
254. 254)
  - 202. Tesei, A., Been, R., Troiano, L., et al: ‘Small vessel detection through the use of an underwater glider’. Proc. 2nd Int. Conf. Underwater Acoustics, 2014.
255. 255)
  - 247. Horridge, P., Maskell, S.: ‘Real-time tracking of hundreds of targets with efficient exact JPDAF implementation’. Proc. FUSION-06, Florence, Italy, July 2006.
256. 256)
  - 178. Preston, J.R., Abraham, D.A.: ‘Statistical analysis of multistatic echoes from a shipwreck in the Malta Plateau’, IEEE J. Ocean. Eng., 2015, 40, (3), pp. 643–656.
257. 257)
  - 46. Munafò, A., Simetti, E., Turetta, A., et al: ‘Autonomous underwater vehicle teams for adaptive ocean sampling: a data-driven approach’, Ocean Dyn., 2011, 61, (11), p. 19811994. doi: 10.1007/s10236-011-0464-x.
258. 258)
  - 61. Chhetri, A.S.: ‘Sensor scheduling and efficient algorithm implementation for target tracking’. PhD dissertation, Arizona State University, 2006.
259. 259)
  - 67. Ryan, A., Durrant-Whyte, H., Hendrick, J.: ‘Information-theoretic sensor motion control for distributed estimation’. ASME 2007 Int. Mechanical Engineering Congress and Exposition, 2007, pp. 725–734.
260. 260)
  - 272. Cattivelli, F., Sayed, A.: ‘Distributed detection over adaptive networks using diffusion adaptation’, IEEE Trans. Signal Process., 2011, 59, (5), pp. 1917–1932.
261. 261)
  - 31. Waite, A.: ‘SONAR for practising engineers’ (Wiley, 2002, 3rd edn.).
262. 262)
  - 76. Huber, M.: ‘Probabilistic framework for sensor management’. PhD dissertation, Universitat Karlsruhe (TH), 2009.
263. 263)
  - 18. Eriksen, C.C., Osse, T.J., Light, R.D., et al: ‘Seaglider: a long-range autonomous underwater vehicle for oceanographic research’, IEEE J. Ocean. Eng., 2001, 26, (4), pp. 424–436.
264. 264)
  - 83. Bullo, F., Cortes, J., Martinez, S.: ‘Distributed control of robotic networks: a mathematical approach to motion coordination algorithms’ (Princeton University Press, Princeton, NJ, USA, 2009).
265. 265)
  - 51. Brito, M.P., Griffiths, G.: ‘Handbook of ocean engineering’ (Springer Dordrecht Heidelberg London New York, 2016), ch. Autonomy: risk assessment, pp. 4527–4543.
266. 266)
  - 41. Kemna, S., Hamilton, M.J., Hughes, D.T., et al: ‘Adaptive autonomous underwater vehicles for littoral surveillance: the GLINT10 field trial results’, Intelligent service robotics, 2011, 4, (4), pp. 245–258.
267. 267)
  - 77. Hoffmann, G.M., Tomlin, C.J.: ‘Mobile sensor network control using mutual information methods and particle filters’, IEEE Trans. Autom. Control, 2010, 55, (1), pp. 32–47.
268. 268)
  - 27. Martin, A.Y.: ‘Unmanned maritime vehicles: Technology evolution and implications’, J. Mar. Technol. Soc., 2013, 47, (5), pp. 72–83.
269. 269)
  - 282. Chitre, M., Freitag, L., Sozer, E., et al: ‘An architecture for underwater networks’. Proc. of MTS/IEEE OCEANS 2006, Singapore, 16–19 May 2006.
270. 270)
  - 127. Agassounon, W., Martinoli, A.: ‘Efficiency and robustness of threshold-based distributed allocation algorithms in multi-agent systems’. Proc. of the Int. Joint Conf. Autonomous Agents and Multiagent Systems, 2002.
271. 271)
  - 40. Ferri, G., Djapic, V.: ‘Adaptive mission planning for cooperative autonomous maritime vehicles’. 2013 IEEE Int. Conf. on Robotics and Automation, May 2013, pp. 5586–5592.
272. 272)
  - 19. Fossum, T.: ‘Intelligent autonomous underwater vehicles’. Technical Report, Norwegian University of Science and Technology, 2016.
273. 273)
  - 176. Fishler, E., Haimovich, A., Blum, R.S., et al: ‘Spatial diversity in radars-models and detection performance’, IEEE Trans. Signal Process., 2006, 54, (3), pp. 823–838.
274. 274)
  - 305. Cossu, G., Corsini, R., Khalid, A.M., et al: ‘Experimental demonstration of high speed underwater visible light communications’. 2013 2nd Int. Workshop on Optical Wireless Communications (IWOW), October 2013, pp. 11–15.
275. 275)
  - 144. Tesei, A., Been, R., Williams, D., et al: ‘Passive acoustic surveillance of surface vessels using tridimensional array on an underwater glider’. OCEANS 2015 – Genova, May 2015, pp. 1–8.
276. 276)
  - 119. Stone, P., Veloso, M.: ‘Task decomposition and dynamic role assignment for real-time strategic teamwork’, Intelligent Agents V: Agent Theories, Architectures, and Languages: 5h International Workshop, ATAL’98 Paris, France, 1998, pp. 293–308.
277. 277)
  - 62. Kalandros, M., Pao, L.Y.: ‘Covariance control for multisensor system’, IEEE Trans. Aerosp. Electron. Syst., 2002, 38, (4), pp. 1138–1157.
278. 278)
  - 91. Harrison, C.H.: ‘Fast bistatic signal-to-reverberation-ratio calculation’, J. Comput. Acoust., 2005, 13, (2), pp. 317–340.
279. 279)
  - 109. Leonard, N.: ‘Handbook of ocean engineering’ (Springer Dordrecht Heidelberg London New York, 2016), ch. Cooperative vehicle environmental monitoring, pp. 441–458.
280. 280)
  - 95. Brooks, R.: ‘Intelligence without representation’, Artif. Intell., 1991, 47, (13), pp. 139–159.
281. 281)
  - 270. Braca, P., Marano, S., Matta, V.: ‘Enforcing consensus while monitoring the environment in wireless sensor networks’, IEEE Trans. Signal Process., 2008, 56, (7), pp. 3375–3380.
282. 282)
  - 29. Li, X., Martinez, J., Rodriguez-Molina, J., et al: ‘A survey on intermediation architectures for underwater robotics’, 2016.
283. 283)
  - 170. Klemm, R.: ‘Comparison between monostatic and bistatic antenna configurations for STAP’, IEEE Trans. Aerosp. Electron. Syst., 2000, 36, (2), pp. 596–608.
284. 284)
  - 50. Shafer, A.J., Benjamin, M.R., Leonard, J.J., et al: ‘Autonomous cooperation of heterogeneous platforms for sea-based search tasks’. OCEANS 2008, September 2008, pp. 1–10.
285. 285)
  - 107. Savla, K., Notarstefano, G., Bullo, F.: ‘Maintaining limited-range connectivity among second-order agents’, SIAM J. Control Optim, 2009, 48, pp. 187–205.
286. 286)
  - 138. Streilein, W.W., Gaudiano, P., Carpenter, G.A.: ‘A neural network for object recognition through sonar on a mobile robot’. Intelligent Control (ISIC), 1998. Held jointly with IEEE Int. Symp. on Computational Intelligence in Robotics and Automation (CIRA), Intelligent Systems and Semiotics (ISAS), Proc. IEEE, 1998, pp. 271–276.
287. 287)
  - 68. MartíNez, S., Bullo, F.: ‘Optimal sensor placement and motion coordination for target tracking’, Automatica, 2006, 42, (4), pp. 661–668. doi: 10.1016/j.automatica.2005.12.018.
288. 288)
  - 12. Caiti, A., Munafò, A., Vettori, G.: ‘System performance tradeoff in underwater harbour protection’. Proc. UAM 2009, 2009.
289. 289)
  - 269. Braca, P., Marano, S., Matta, V., et al: ‘Asymptotic optimality of running consensus in testing statistical hypotheses’, IEEE Trans. Signal Process., 2010, 58, (2), pp. 814–825.
290. 290)
  - 206. Abdi, H.: ‘The method of least squares’, ‘Encyclopedia of measurement and statistics’ (Thousand Oaks, CA, USA, 2007).
291. 291)
  - 288. Alves, J., Furfaro, T., LePage, K., et al: ‘Moving janus forward: a look into the future of underwater communications interoperability’. Proc. MTS/IEEE OCEANS 2016, Monterey, CA, USA, 19–23 September 2016.
292. 292)
  - 136. Van Trees, H.: ‘Detection, estimation, and modulation theory’ (John Wiley & Sons, 2004).
293. 293)
  - 129. Porta, J., Spaan, M., Vlassis, N.: ‘Robot planning in partially observable continuous domains’. Robotics: Science and Systems, 2005.
294. 294)
  - 130. Viguria, A.: ‘Market-based distributed task allocation methodologies applied to multi-robot exploration’. PhD dissertation, University of Seville, 2009.
295. 295)
  - 32. Paull, L., Saeedi, S., Seto, M., et al: ‘AUV navigation and localization: a review’, IEEE J. Ocean. Eng., 2014, 39, (1), pp. 131–149.
296. 296)
  - 53. Li, W., Farrell, J., Pang, S., et al: ‘Moth-inspired chemical plume tracing on an autonomous underwater vehicle’, IEEE Trans. Robot., 2006, 22, (2), pp. 292–307.
297. 297)
  - 211. Rasmussen, C., Hager, G.D.: ‘Probabilistic data association methods for tracking complex visual objects’, IEEE Trans. Pattern Anal. Mach. Intell., 2001, 23, (6), pp. 560–576.
298. 298)
  - 60. Korsah, G., Stentz, A., Dias, M.: ‘A comprehensive taxonomy for multi-robot task allocation’, Int. J. Robotics Res., 2013, 35, pp. 514–527.
299. 299)
  - 289. Kilfoyle, D.B., Baggeroer, A.B.: ‘The state of the art in underwater acoustic telemetry’, IEEE J. Ocean. Eng., 2000, 25, (1), pp. 4–27.
300. 300)
  - 73. Hero, A.O., Castan, D., Cochran, D., et al: ‘Foundations and applications of sensor management’ (Springer Publishing Company, Incorporated, 2010, 1st edn.).
301. 301)
  - 193. Murphy, S.M., Coffin, M., Hines, P.C., et al: ‘Testing the feasibility of a concurrent comparison of continuous and pulsed active sonar’, J. Acoust. Soc. Am., 2016, 140, (4), pp. 3285–3285.
302. 302)
  - 177. Grimmett, D.J., Sullivan, S., Alsup, J.: ‘Modeling specular occurrence in distributed multistatic fields’. OCEANS 2008-MTS/IEEE Kobe Techno-Ocean, 2008, pp. 1–8.
303. 303)
  - 285. Smerdon, A., Bustamante, F., Baker, M.: ‘The swigacoustic standard: an acoustic communication standard for the offshore energy community’. 2016 IEEE Third Underwater Communications and Networking Conf. (UComms), August 2016, pp. 1–4.
304. 304)
  - 49. German, C., Yoerger, D., Jakuba, M., et al: ‘Hydrothermal exploration with the Autonomous Benthic Explorer’, Deep Sea Res., 2008, I, 55, pp. 203–219.
305. 305)
  - 276. Hlinka, O., Sluciak, O., Hlawatsch, F., et al: ‘Likelihood consensus and its application to distributed particle filtering’, IEEE Trans. Signal Process., 2012, 60, (8), pp. 4334–4349.
306. 306)
  - 149. Kuperman, W., Ingenito, F.: ‘Attenuation of the coherent component of sound propagating in shallow water with rough boundaries’, J. Acoust. Soc. Am., 1977, 61, (5), pp. 1178–1187.
307. 307)
  - 122. Gerkey, B., Mataric, M.: ‘A formal analysis and taxonomy of task allocation in multirobot systems’, Int. J. Robot. Res., 2004, 23, (9), pp. 939–954.
308. 308)
  - 124. Yan, Z., Jouandeau, N., Cherif, A.: ‘A survey and analysis of multi-robot coordination’, Int. J. Adv. Robotic Syst., 2013, 10, pp. 1–18.
309. 309)
  - 71. Hernandez, M.L., Kirubarajan, T., Bar-Shalom, Y.: ‘Multisensor resource deployment using posterior Cramr-Rao bounds’, IEEE Trans. Aerosp. Electron. Syst., 2004, 40, (2), pp. 399–416.
310. 310)
  - 187. Doisy, Y., Le Chevalier, F.: ‘Airborne radar and shipborne sonar: recent advances and compared solutions’. 2009 Int. Radar Conf. Surveillance for a Safer World (RADAR 2009), 2009, pp. 1–6.
311. 311)
  - 181. Jauffret, C., Perez, A.-C., Blanc-Benon, P., et al: ‘Doppler-only target motion analysis in a high duty cycle sonar system’. Proc. 19th Int. Conf. Information Fusion – Heidelberg, 2016.
312. 312)
  - 259. Papa, G., Braca, P., Horn, S., et al: ‘Multisensor adaptive bayesian tracking under time-varying target detection probability’, IEEE Trans. Aerosp. Electron. Syst., 2016, 52, (5), pp. 2193–2209.
313. 313)
  - 143. Kang, C., Zhang, X., Zhang, A., Lin, H.: ‘Underwater acoustic targets classification using welch spectrum estimation and neural networks’. Advances in Neural Networks-ISNN 2004, 2004, pp. 930–935.
314. 314)
  - 137. Stewart, J.-M., Jiang, M., Marra, M.: ‘A neural network approach to classification of sidescan sonar imagery from a midocean ridge area’, IEEE J. Ocean. Eng., 1994, 19, (2), pp. 214–224.
315. 315)
  - 69. Cover, T.M., Thomas, J.A.: ‘Elements of information theory (Wiley series in telecommunications and signal processing)’ (Wiley-Interscience, 2006).
316. 316)
  - 105. Moreno-Salinas, D., Pascoal, A., Aranda, J.: ‘Optimal sensor placement for multiple underwater target localization with acoustic range measurements’. Proc. of IFAC World Conf., 2011.
317. 317)
  - 209. Mallick, M., Vo, B.N., Kirubarajan, T., et al: ‘Introduction to the issue on multitarget tracking’, IEEE J. Sel. Topics Signal Process., 2013, 7, (3), pp. 373–375.
318. 318)
  - 304. Doniec, M., Rus, D.: ‘Bidirectional optical communication with aquaoptical ii’. 2010 IEEE Int. Conf. Communication Systems, November 2010, pp. 390–394.

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Cooperative robotic networks for underwater surveillance: an overview

References

Related content