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Formal Reports

Report of results of completed projects or major milestones either in scientific terms or in terms acceptable to a wider audience. Note: Unless linked to the full text, reports are only available to NATO member nations from designated distribution centres. 

Documents

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A comparison of measured and modelled acoustic signal excess during Noble Mariner 2012 A comparison of measured and modelled acoustic signal excess during Noble Mariner 2012

Date added: 11/26/2014
Date modified: 11/26/2014
Filesize: Unknown

A comparison of measured and modelled acoustic signal excess during Noble Mariner 2012. Jiang, Yong Min; Strode, Christopher. CMRE-FR-2014-022. November 2014.

In September 2012, mid-frequency acoustic signal excess measurements were conducted in the Gulf of Lions to validate the sonar performance of the Multistatic Tactical Planning Aid. Owing to the fact that the validity of an acoustic model and the quantity and quality of the environmental information have almost equal impact on the fidelity of sonar performance predictions, this study carries out a measurement and model comparison of the acoustic signal excess by using different categories of rapid environmental assessment inputs. Specifically, five different categories of ocean environmental information have been used, including 1) climatology, 2) a high-resolution regional ocean model, 3) a high-resolution regional ocean model initialized by survey ship data collection, 4) a high-resolution regional ocean model updated by assimilation of glider data and 5) gray-ship equivalent on-scene for an operation. The bathymetric data used were either from climatology or collected by a multi-beam system for the scientific validation. The comparison was performed on the data collected along both range dependent and range independent tracks, seven source-target ranges for each track, two source depths at each source-target range and three different receiver depths. The impacts of varying degrees of fidelity of environmental information, as well as the conditions/configurations for setting up the acoustic model, on signal-excess predictions are summarized.

A Comprehensive Autonomy Architecture for MCM AUVs A Comprehensive Autonomy Architecture for MCM AUVs

Date added: 06/01/2008
Date modified: 06/21/2012
Filesize: Unknown

A Comprehensive Autonomy Architecture for MCM AUVs. Williams, P.D.; Evans, B.S.

NURC-FR-2008-018. June 2008.

A comprehensive autonomy framework for MCM AUV missions is presented. The approach is a flexible solution that allows information collected during the mission to be immediately exploited in the remainder of the mission. This adaptive nature of the resulting autonomous mission route can result in improvements over pre-planned routes. The proposed system is comprised of six behaviors, each of which deals with a fundamental component of the vehicle’s functionality. Thirteen performance measures that represent more specific objectives of the mission fall under the purview of the six behaviors. Operator-defined weights on these performance measures are used to compute the value of an objective function, which in turn determines the optimal vehicle settings to select. Example simulations that demonstrate the promise of the autonomy architecture, as well as the effects of different performance-measure weight settings, are shown. Quantitative comparisons of the autonomy approaches with standard pre-planned routes are also provided.

A Fast Detection Algorithm for Autonomous Mine Countermeasures A Fast Detection Algorithm for Autonomous Mine Countermeasures

Date added: 10/20/2011
Date modified: 08/10/2012
Filesize: Unknown

A Fast Detection Algorithm for Autonomous Mine Countermeasures. Williams, D.P.; Groen, J.; Fox, W.L.J. NURC-FR-2011-006. October 2011.

A new algorithm for the detection of underwater mines in sonar imagery is proposed. One particularly novel component of the algorithm also detects the presence of, and estimates the orientation of, sand ripples. The overall algorithm is made extremely fast by employing a cascaded architecture and by exploiting integral-image representations. As a result, the method makes real-time detection of mines in streaming sonar data collected by an autonomous underwater vehicle (AUV) feasible. No training data are required because the proposed method is adaptively tailored to the environmental characteristics of the sensed data that are collected in situ. The flexible yet rigorous approach also addresses and overcomes four major limitations that plague the most popular detection algorithms that are in common use. Moreover, the proposed algorithm achieves superior performance across a variety of seabed types on a large, challenging data set of real sonar data collected at sea. Ways to exploit the findings and adapt AUV surveys for optimized detection performance are also suggested.

A large-scale analysis of MCM detection performance for surrogate targets in SAS imagery A large-scale analysis of MCM detection performance for surrogate targets in SAS imagery

Date added: 12/16/2013
Date modified: 12/16/2013
Filesize: Unknown

A large-scale analysis of MCM detection performance for surrogate targets in SAS imagery. Williams, David P. CMRE-FR-2013-020. December 2013.

A large-scale study is undertaken to assess the capability of detecting underwater mines in sonar imagery. The data used in the analysis are synthetic aperture sonar (SAS) imagery containing various surrogate targets. The data were collected with the MUSCLE autonomous underwater vehicle (AUV) during six large sea trials, conducted between 2008 and 2012, in different geographical locations with diverse environmental conditions. The detection algorithm for which performance is assessed is the cascaded, integral-image-based approach described in [1]. The analysis examines detection performance for specific target types as a function of target aspect, range, image quality, and seabed environment. To our knowledge, this study - based on nearly 30000 SAS images collectively covering approximately 160 square kilometers of seabed, and involving over 1100 target detection opportunities - represents the most extensive such systematic, quantitative assessment of target detection performance with SAS data.The analysis reveals the variables that have the largest impact on mine detection performance, namely image quality and environmental conditions on the seafloor. The results of the study can be exploited to construct performance planning and evaluation models and to optimize adaptive surveys conducted with an AUV.

A method for sea floor clutter suppression in side scan sonar images A method for sea floor clutter suppression in side scan sonar images

Date added: 02/01/2007
Date modified: 06/22/2012
Filesize: Unknown

A method for sea floor clutter suppression in side scan sonar images. R. Grasso, F. Spina. NURC-FR-2007-002. February 2007.

A clutter suppression algorithm for improving detection of unknown spatially distributed small targets on a textured sea floor background in side scan sonar images is analysed and tested. The algorithm is based on a multi-resolution transform of the sonar data and a projection pursuit (PP) algorithm, which is used to enhance signal-to-clutter ratio in the multi-resolution space. The sea floor background in a sub-image is modelled by a set of texture features estimated from the image data by a two dimensional un-decimated wavelet transform. Each image sample is associated with a vector of features which are composed by the local mean energy resulting from a bank of multi-resolution oriented bandpass filters. The target points in the feature space appear as a small set of outliers compared to the feature vector distribution of the background. The feature vector data set is projected, by a PP algorithm, along the direction of kurtosis maximisation of the data which is sensitive to the outliers in a data set. The projected signal is used in a threshold test for detecting anomalies in sea floor background signals. An ad hoc gradient algorithm to maximise the kurtosis iteratively was studied and developed. An efficient procedure to find a first guess solution to initialise the gradient algorithm was proposed and tested on a side scan sonar data set acquired during the NURC BP02 cruise by a ship towed sensor. The improvement in the signal-to-clutter ratio observed in this case ranges between 5 and 8 dB.

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