CAN UNCLASSIFIED Examination of Statistics and Modulation of Underwater Acoustic Ship Signatures Mark Trevorrow DRDC – Atlantic Research Centre Terms of Release: This document is approved for public release. Defence Research and Development Canada Scientific Report DRDC-RDDC-2021-R027 March 2021 CAN UNCLASSIFIED CAN UNCLASSIFIED IMPORTANT INFORMATIVE STATEMENTS This document was reviewed for Controlled Goods by Defence Research and Development Canada (DRDC) using the Schedule to the Defence Production Act. Disclaimer: This publication was prepared by Defence Research and Development Canada an agency of the Department of National Defence. The information contained in this publication has been derived and determined through best practice and adherence to the highest standards of responsible conduct of scientific research. 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Template in use: EO Publishing App for SR-RD-EC Eng 2021-02-11.dotm © Her Majesty the Queen in Right of Canada (Department of National Defence), 2021 © Sa Majesté la Reine en droit du Canada (Ministère de la Défense nationale), 2021 CAN UNCLASSIFIED CAN UNCLASSIFIED Abstract This Scientific Report examines ship underwater acoustic signature amplitude statistics and statistical distributions. This explores the hypothesis that ship signatures exhibit amplitude fluctuations that are different from Rayleigh-distributed ambient ocean noise. Signature measurements from two different ships conducting a variety of manoeuvres are examined, focusing on those conditions where propeller cavitation and broadband signal modulation occur, specifically during maximum speed runs, accelerations, and turning manoeuvres. A key difference for a ship signature is the amplitude modulation generated by propeller cavitation, and this is found to be associated with super-Rayleigh signal characteristics. The use of new cyclostationary processing techniques is used to estimate propeller shaft and blade rate modulation. Under conditions of stronger propeller modulation, time-series statistics scintillation index and skewness show values significantly in excess of Rayleigh-distributed values. Ship signature amplitude probability density functions were found to be better matched by a K-distribution model with small shape factor, indicating increased presence of higher-amplitude signal components. Significance to Defence and Security The ship signature statistics examined in this study quantify the acoustic texture of the signal, describing features that might be used intuitively by experienced acoustic operators to identify a ship signature and determine its operating state (e.g., steady cruising vs. manoeuvring). It is believed that this result may be useful in advanced sonar detectors and classifiers, including use in modern artificial intelligence algorithms, against surface ships and other vehicles employing propellers. Conventional active and passive sonar processors generally use detection thresholds based on the assumption of Rayleigh statistics for the background noise. When ship noise contributes to the background noise for active and passive sonars, this super-Rayleigh behaviour may generate increased false alarms, or require an increase in sonar detection thresholds thus reducing potential target detection ranges. DRDC-RDDC-2021-R027 i CAN UNCLASSIFIED CAN UNCLASSIFIED Résumé Le présent rapport scientifique porte sur les distributions statistiques et les statistiques d’amplitude de la signature acoustique sous-marine des navires. On examine l’hypothèse selon laquelle la signature des navires présente des fluctuations d’amplitude différentes du bruit océanique ambiant réparti selon la loi de Rayleigh. On étudie les mesures de la signature de deux navires distincts exécutant diverses manœuvres en s’attardant surtout aux conditions dans lesquelles on observe une cavitation des hélices et une modulation des signaux à large bande, en particulier lors de déplacements à vitesse maximale, d’accélérations et de virages. L’une des principales différences dans la signature des navires est la modulation d’amplitude produite par la cavitation des hélices, modulation qui s’avère être associée aux caractéristiques des signaux en régime super-Rayleigh. On utilise de nouvelles techniques de traitement cyclostationnaire pour déterminer la modulation de l’arbre porte-hélice et de la fréquence des pales. En cas de forte modulation de l’hélice, l’indice de scintillation et l’asymétrie de statistiques provenant de séries chronologiques affichent des valeurs nettement supérieures à celles obtenues selon la distribution de Rayleigh. Ainsi, on a constaté que les fonctions de densité de probabilités de l’amplitude de la signature des navires correspondaient davantage à un modèle de distribution K avec un faible coefficient de forme, ce qui indique la présence accrue de composantes de signaux de plus grande amplitude. Importance pour la défense et la sécurité Les statistiques sur la signature des navires examinées dans la présente étude permettent de quantifier la texture acoustique des signaux en décrivant des caractéristiques que des opérateurs acoustiques chevronnés pourraient utiliser de manière intuitive pour identifier la signature d’un navire et déterminer son état de marche (p. ex., régime de croisière stable par rapport aux manœuvres). On croit que ces résultats pourraient être utiles pour les récepteurs sonar et les classificateurs plus perfectionnés. On pourrait les utiliser notamment dans les algorithmes d’intelligence artificielle modernes, pour les navires de surface et autres véhicules à hélice. Les processeurs de sonars actifs et passifs classiques utilisent généralement des seuils de détection fondés sur l’hypothèse des statistiques de Rayleigh sur le bruit de fond. Si le bruit des navires contribue au bruit de fond des sonars actifs et passifs, ce régime super-Rayleigh peut entraîner une augmentation des fausses alarmes ou bien nécessiter un seuil accru de détection sonar, réduisant ainsi la portée de détection de cibles potentielles. ii DRDC-RDDC-2021-R027 CAN UNCLASSIFIED CAN UNCLASSIFIED Table of Contents Abstract ................................ ... i Significance to Defence and Security ......................... i Résumé ................................ ... ii Importance pour la défense et la sécurité ....................... ii Table of Contents ............................... iii List of Figures ................................ v List of Tables ................................ viii 1 Introduction ................................ 1 2 Review of Ship Signature Characteristics ...................... 3 2.1 Ship Signature Spectra .......................... 3 2.2 Propeller Modulation Effects ........................ 5 2.2.1 DEMON Processing ........................ 5 2.2.2 Cyclic Modulation Coherence (CMC) .................. 6 2.3 Ship Signature Statistical Models ...................... 6 2.3.1 Time-series Statistics ........................ 6 2.3.2 Probability Density Function (PDF) Models ............... 7 2.3.3 PDF Generation and Fitting ...................... 8 2.4 Numerical Simulations .......................... 8 2.4.1 Spectral Shaping and PDF ...................... 9 2.4.2 Time-series Statistics ....................... 12 2.4.3 Ship Signature Modulation ..................... 13 3 Instrumentation and Sea-Trials ........................ 16 3.1 Broadband Underwater Recording Buoys .................. 16 3.2 Spectral Processing .......................... 17 3.3 Lloyd’s Mirror Effects ......................... 18 3.4 Test Ships .............................. 19 3.5 Ship Manoeuvre Types ......................... 20 3.6 Sea-trial Locations ........................... 21 4 CCGS VECTOR Sea-Trials, April 2005 ..................... 22 4.1 Straight-Line Runs ........................... 22 4.1.1 Example Run 1302 Straight Pass at 11 Knots .............. 22 4.1.1.1 Spectral Levels and Lloyd’s Mirror .............. 23 4.1.1.2 Signature PDF and Statistics ................. 24 4.1.1.3 Propeller Modulation ................... 27 4.1.2 SSL and Propeller Rate Variation with Speed .............. 29 4.1.3 Variability in PDF and Statistics ................... 30 4.2 Turning Runs ............................. 31 DRDC-RDDC-2021-R027 iii CAN UNCLASSIFIED CAN UNCLASSIFIED 4.2.1 Example Run 1404: 180 Starboard Turn at 11.3 Knot In-run ........ 31 4.2.1.1 Spectral Levels through Turns ................ 33 4.2.1.2 Signature PDF and Statistics ................. 34 4.2.1.3 Propeller Modulation ................... 37 4.2.2 Example Run 1308: 110 Port Turn at 11.3 Knot In-run .......... 38 5 CFAV QUEST Sea-Trials, Sept. 2005 ...................... 42 5.1 Straight-Line Constant-Speed Runs .................... 42 5.1.1 Spectral Source Levels ...................... 42 5.1.2 Signature PDF