Enhanced detection, localisation and identification of sand-covered naval mines using novel hybrid signal processing methods

Project Member(s): Halkon, B., Oberst, S., Fitch, R.

Funding or Partner Organisation: NSW Department of Industry (NSW Defence Innovation Network)
NSW Department of Industry (NSW Defence Innovation Network)
NAVAL GROUP PACIFIC PTY LIMITED

Start year: 2021

Summary: DIN PP 2020 Problem Statement: Using existing sonar (acoustic) information from typical Unmanned Underwater Vehicle (UUV) or Remotely Operated Vehicle (ROV) sonars, can new types of analysis provide more information than common frequency domain methods to detect features of buried mines? What new sensors could be deployed on UUV or ROV for buried mine detection? How can detection be improved using data fusion methods by combining data from different sensors and measurement techniques?

Publications:

Milton, J, Halkon, B, Oberst, S, Chiang, YK & Powell, D 1970, 'SONAR-BASED BURIED OBJECT DETECTION VIA STATISTICS OF RECURRENCE PLOT QUANTIFICATION MEASURES', Proceedings of the International Congress on Sound and Vibration, International Congress on Sound and Vibration, Society of Acoustics, Singapore, Singapore, pp. 1-8.

Halkon, B, Milton, J, Oberst, S, Powell, D, Chiang, YK & Phung, SL UTS 2022, Enhanced detection, localisation and identification of sand-covered naval mines using novel hybrid signal processing methods, UTS.

Milton, J, Hall, M, Chiang, YK, Halkon, B, Oberst, S & Powell, D 1970, 'Exploring the effect of underwater burial on the resonant behaviour of simplified shell geometries', Annual Conference of the Australian Acoustical Society 2021: Making Waves, AAS 2021, Australian Acoustics Society - Acoustics 2021, Wollongong, pp. 15-22.

FOR Codes: Mechanical Engineering not elsewhere classified, Emerging Defence Technologies