Mine Countermeasures Research Articles

AUTOMATIC MINE COUNTER MEASURE MISSION CONTROL FOR AUV SYSTEMS

Future AUV products must have a real autonomy, that is, must be able to navigate and fulfill a Mine Counter Measure (MCM) surveillance mission with high reliability without any operator control. The first step toward this product is a vehicle programmed on a defined trajectory, that records data and reports to the sonar operator when coming back to the recovery point. This step is currently under development. The second step is giving the AUV more autonomy for analysis and decision, to allow it to re-plan its trajectory in order to best fulfill its MCM mission. Besides, sonar systems, designed to detect stealthy mines, will now also hand over to the classification process many more small non-mine bottom objects (NOMBO) to be discrimined from Mine Like Contact (MILCO). This is the challenge of Automatic Target Recognition processing. In this paper, we show how data generated by Automatic Target Recognition processing can help to perform robust Concurrent Navigation and Mapping. Associated with Bottom Characterization, Mission Analysis and Re-Planning Strategy, Concurrent Navigation and Mapping constitute the Mission Control Module. We also discuss Re-Planning strategy in order to increase the efficiency of MCM mission in terms of reliability and precision.

A Probabilistic Expert System Approach for Sea Mine Burial Prediction

Knowledge of the extent of burial of bottom sitting sea mines is critical to mine detection due to the significantly degraded capabilities of mine-hunting systems when the mines are buried. To provide an enhanced capability for predicting mine burial in support of U.S. Navy mine countermeasure (MCM) operations, an expert system approach to predicting sea mine burial has been developed. This expert system serves as a means to synthesize previous and current research on sea mine burial due to impact upon deployment and subsequently due to scour, the two dominant burial mechanisms in littoral waters. Prediction systems for impact and scour burial have been implemented as simple Bayesian networks whose probabilistic basis provides means of accounting for the inherent uncertainties associated with mine deployment methods, simplified physics-based burial models, and environmental variability. Examples of burial predictions and comparisons to results from field experiments are illustrated. In addition, a proposed risk metric is developed and applied to provide a geospatial mapping of mine burial probability.

Mine Countermeasures (MCM) Tactical Decision Aids (TDAs), A Historical Review

Mine Countermeasures (MCM) Tactical Decision Aids (TDAs), A Historical Review

Modeling nonlinear acoustics in shallow water

Lessons learned in modeling nonlinear acoustics and weak shock propagation in deep water are helpful in application to shallow water (mine countermeasures in particular), but the medium is much more complicated. Numerous improvements are needed; Joe Blue’s work touched on several of them. First is the need to treat higher propagation angles. Second is the presence of bubbles near the surface and possibly in the bottom. Finally, there are problems introduced by nonlinear propagation in granular sediments. These include greatly increased nonlinearity parameter and time‐domain formulation of frequency—linear attenuation. Recent progress in the application of the NPE model [McDonald and Kuperman, ‘‘Time domain formulation for pulse propagation including nonlinear behavior at acoustic,’’ J. Acoust. Soc. Am. 81, 1406–1417 (1987)] to mine countermeasures will be outlined. [Work supported by the Office of Naval Research.]

Autonomous underwater vehicles for scientific and naval operations

Recognizing the potential of autonomous underwater vehicles for scientific and military applications, in 1997 MIT and the NATO Undersea Research Centre initiated a Joint Research Project (GOATS), for the development of environmentally adaptive robotic technology applicable to mine counter measures (MCM) and rapid environmental assessment (REA) in coastal environments. The August 2001 GOATS Conference marked the end of this 5 years project, but did not mark the end of the work. The Centre initiated in 2002 a new long-term programme to explore and demonstrate the operational benefits and performances of AUV for covert preparation of the battlespace. Recently the work addressed the evaluation of commercial off-the-shelf (COTS) AUV technology for MCM operations in response to terrorist mining of port. The paper summarizes the work performed and refers to the scientific publications derived from the AUV programme at the NATO Undersea Research Centre.

Multi-agent immune recognition of water mine model

It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune neural network (INN) along with water mine model recognition system based on multi-agent system is proposed. A modified clonal selection algorithm for constructing such an INN is presented based on clonal selection principle. The INN is a two-layer Boolean network whose number of outputs is asion, and the affinity threshold also can control the capability of noise tolerance.

A comparison of mine counter measure performance models

Mine counter measure (MCM) sonar systems perform the task of detection and classification of marine mines that are typically laid in shallow water environments. Currently, there are several MCM performance models in use that can predict the performance of MCM sonars. This paper gives a brief description of some these models and gives a comparison of their performance predictions for several shallow water scenarios. All the models examined are self contained packages that can model the entire problem—the sonar, the environment, and the target. They are considered to be energy models in that only the intensity of sound received from various parts of the environment is modeled while phase calculations are ignored. The results show that the models can give good agreements with each other for some scenarios. In some other scenarios the agreement is not so good and reasons are given to show why this happens.

Modeling acoustic nonlinearities in marine sediments

Investigations into the theoretical and numerical treatment of acoustic nonlinearities in marine sediments are motivated by mine countermeasures and other Naval interests related to explosions in shallow water. Agreement between theory and data for the nonlinearity parameter B/A has been demonstrated in early papers concerning saturated sands. In the more general case involving varying depth profiles of air and silt contents, however, it is observed that B/A values vary so greatly that deterministic nonlinear modeling approaches may have to be augmented to address environmental uncertainty. Comparisons are given between B/A values derived from static consolidation tests and available in situ data. Numerical profiles from the NPE shock propagation model are given to demonstrate the effects of environmental uncertainty. [Work supported by the ONR.]

Autonomous underwater vehicles for scientific and naval operations

Recognizing the potential of autonomous underwater vehicles for scientific and military applications, in 1997 MIT and the NATO Undersea Research Centre initiated a Joint Research Project (GOATS), for the development of environmentally adaptive robotic technology applicable to Mine Counter Measures (MCM) and Rapid Environmental Assessment in coastal environments. The August 2001 GOATS Conference marked the end of this 5 years project, but did not mark the end of the work. The Centre initiated in 2002 a new long term programme to explore and demonstrate the operational benefits and limitations of AUV for covert preparation of the battlespace. Recently the work addressed the evaluation of COTS (Commercial Off-The-Shelf) AUV technology for MCM operations in response to terrorist mining of port. The paper summarizes the work performed and refers to the scientific publications derived from the AUV programme at the NATO Undersea Research Centre.

Terrain Navigation for Underwater Vehicles Using the Correlator Method

In many autonomous underwater vehicle (AUV) applications of long duration, there is a need to accurately determine the AUV's position in an effective way, in terms of both cost and energy consumption. Such situations may occur in reconnaissance operations, mine counter measure operations, and when an AUV is sampling the characteristics of the environment along a track. Since underwater maps are rare, there also is a need for navigational methods that can accommodate very infrequent sampling in terms of time and space. This work describes a new method to solve the above problem by using a multibeam sonar for three-dimensional sampling of the bottom topography and a linear Kalman filter in a nearly optimal way. The proposed method is very accurate, robust, and computationally efficient compared to other methods that are used for terrain navigation. This method is also suitable for continuous navigation.

A framework of concurrent navigation and seabottom targets detection using acoustic sensors on AUVs

The use of Autonomous Underwater Vehicles (AUVs) for Mine Counter Measures (MCMs) is an area of active recent research. The excellent mobility of AUVs allows for multi-aspect sonar view of the targets for improved detection, tracking, and classification. However, the uncertainty of the platforms and associated target localization degrade the detection ability by AUVs. Furthermore, the weak signals from buried targets is another severe problem making detection by a single measurement impossible. A new acoustic sensing framework is proposed for detection and tracking seabottom targets based on the track-before-detect (TBD) technique. In contrast to the traditional methods, TBD tracks possible targets before the detection is declared. There are several advantages by using this framework: (1) Compared to the traditional method of detection followed by tracking, higher detection probability is achieved for dim target detection due to the integrated detection metric of TBD. (2) Compared to the multiple hypothesis tracker (MHT) method, instead of searching a diverge hypotheses tree, TBD speeds up the searching and decreases the computational load, which makes onboard implementation feasible. (3) The stochastic models of uncertainties of targets and AUVs are based on the Bayesian framework, and thus, it is easy to apply various recursive estimators such as the Kalman filter or particle filter for tracking individual targets as well as the AUV platforms. Results of a successful application of this method in the GOATS2002 experiment are demonstrated. [Work supported by ONR and NATO Undersea Research Centre.]

AUVs as integrated, adaptive acoustic sensors for ocean exploration

Autonomous underwater vehicles (AUV) are rapidly being transitioned into operational systems for national defense, offshore exploration, and ocean science. AUVs provide excellent sensor platform control, allowing for, e.g., accurate acoustic mapping of seabeds not easily reached by conventional platforms, such as the deep ocean. However, the full potential of the robotic platforms is far from exhausted by such applications. Thus, for example, most seabed-mapping applications use imaging sonar technology, the data volume of which cannot be transmitted back to the operators in real time due to the severe bandwidth limitation of the acoustic communication. The sampling patterns are therefore in general being preprogramed and the data are being stored for postmission analysis. This procedure is therefore associated with indiscriminate distribution of the sampling throughout the area of interest, irrespective of whether features of interest are present or not. However, today’s computing technology allows for a significant amount of signal processing and analysis to be performed on the platforms, where the results may then be used for real-time adaptive sampling to optimally concentrate the sampling in area of interest, and compress the results to a few parameters which may be transmitted back to the operators. Such adaptive sensing concepts combining environmental acoustics, signal processing, and robotics are currently being developed for concurrent detection, localization, and classification of buried objects, with application to littoral mine countermeasures, deep ocean seabed characterization, and marine archeology. [Work supported by ONR and NATO Undersea Research Center.]

Bistatic scattering from flush and partially buried targets in shallow water

GOATS’98 experiment had as one of its objectives to explore the possibility of vastly increasing the coverage rate of shallow water mine countermeasures (MCM), especially for buried targets using subcritical seabed penetration. The evanescent incident field combined with 3D bistatic configuration brought about a rich and intricate set of physical phenomena occurring in the target scattering and radiation process. Resonance of manmade elastic targets is a pivotal concept distinguishing targets from rocks or other clutter. Nevertheless, burial in sediment results in a variety of modifications to the scattered response caused by different physical mechanisms, geometric constraints, and intrinsic sediment properties. It is the goal of this work to identify, analyze, and explain the fundamental effects of the outer sediment and the proximity of the seabed interface on the scattering from elastic shells insonified at subcritical incident angles in a bistatic configuration. Using time-frequency and spectral analysis, a new, more comprehensive, understanding of GOATS’98 experimental data was obtained distinguishing the effects of the acoustics environment from the resonant signature of buried elastic targets. To achieve this, and to further investigate the details of the scattering process a new target scattering module of OASES-3D modeling framework was used. [Work supported by ONR.]

Mine countermeasures HTS magnet

American Superconductor has designed, manufactured, and tested a model high-temperature superconducting (HTS) magnet system for airborne mine countermeasures (MCM) for the Office of Naval Research. The magnet has a magnetic moment of 80 kA-m/sup 2/, or about one-fourth that of the full-scale magnet. The magnet is a solenoid consisting of 16 layers of laminated Bi-2223 HTS wire. The coil was manufactured at Everson Electric and tested at American Superconductor. The coil has an inside diameter of 455 mm, an outside diameter of 476 mm, and is 914 mm in length. The magnet was successfully ramped to its operating current of 193 A at 30 K. It was also successfully modulated with /spl plusmn/26 A current at 0.5 Hz. The magnet is conduction-cooled with a single-stage GM cryocooler. The design, manufacture, and test results of the magnet will be presented.

An automatic approach to the detection and extraction of mine features in sidescan sonar

Mine detection and classification using high-resolution sidescan sonar is a critical technology for mine counter measures (MCM). As opposed to the majority of techniques which require large training data sets, this paper presents unsupervised models for both the detection and the shadow extraction phases of an automated classification system. The detection phase is carried out using an unsupervised Markov random field (MRF) model where the required model parameters are estimated from the original image. Using a priori spatial information on the physical size and geometric signature of mines in sidescan sonar, a detection-orientated MRF model is developed which directly segments the image into regions of shadow, seabottom-reverberation, and object-highlight. After detection, features are extracted so that the object can be classified. A novel co-operating statistical snake (CSS) model is presented which extracts the highlight and shadow of the object. The CSS model again utilizes available a priori information on the spatial relationship between the highlight and shadow, allowing accurate segmentation of the object's shadow to be achieved.

Measurements and modeling of acoustic scattering from partially and completely buried spherical shells.

The use of low-frequency sonars (2-15 kHz) is explored to better exploit scattering features of buried targets that can contribute to their detection and classification. Compared to conventional mine countermeasure sonars, sound penetrates better into the sediment at these frequencies, and the excitation of structural waves in the targets is enhanced. The main contributions to target echo are the specular reflection, geometric diffraction effects, and the structural response, with the latter being particularly important for man-made elastic objects possessing particular symmetries such as bodies of revolution. The resonance response derives from elastic periodic phenomena such as surface circumferential waves revolving around the target. The GOATS'98 experiment, conducted jointly by SACLANTCEN and MIT off the island of Elba, involved controlled monostatic measurements of scattering by spherical shells which were partially and completely buried in sand, and suspended in the water column. The analysis mainly addresses a study of the effect of burial on the dynamics of backscattered elastic waves, which can be clearly identified in the target responses, and is based on the comparison of measurements with appropriate scattering models. Data interpretation results are in good agreement with theory. This positive result demonstrates the applicability of low-frequency methodologies based on resonance analysis to the classification of buried objects.

Bistatic synthetic aperture imaging of proud and buried targets from an AUV

The use of autonomous underwater vehicles (AUVs) for the detection of buried mines is an area of current interest to the Mine CounterMeasures (MCM) community. AUVs offer the advantages of lower cost, stealth, reduced operator risk, and potentially improved coverage rates over more traditional mine hunters. However, AUVs also come with their own set of difficulties, including significant error in navigation and low communication rates with the mother platform and each other. In the case of bistatic detection scenarios, AUVs will therefore have difficulty knowing where exactly in space they are and the trigger time of sources on other platforms, be they ships or other AUVs. However, the potential improvement in detection and coverage rates offered by bistatic sonar concepts makes resolution of these issues a high priority. In this paper, the problems of inaccurate navigation and source timing information are addressed for the Generic Oceanographic Array Technology data set. In this experiment, conducted off Marciana Marina during June 1998, a MIT AUV with a SACLANTCEN acoustic array and acquisition system was used together with a TOPAS parametric sonar to explore issues of buried target detection using AUVs. In this paper, solutions to the navigation and timing problems are proposed which enable the effective use of bistatic synthetic aperture sonar (SAS) concepts for the detection of buried objects in the mid-frequency regime of 2-20 kHz.

Imaging sonar development for mine countermeasure applications

Over the past decade the Office of Naval Research (ONR) has sponsored research to improve the mine countermeasures (MCM) community’s ability to detect, classify, reacquire, and identify mines. In the first stage of wide area detection and classification, the single biggest problem is the ability to distinguish mines from clutter with side-scan sonar assets. In the reacquire-identify stage, divers employ a single-beam aural sonar for guidance to close proximity for visual identification of targets. Current sonar research efforts in wide-area search focus on clutter rejection through high-resolution imaging by synthetic aperture processing and cuing from broadband response characteristics. For reacquisition and identification, research has focused on compact, multibeam imagers. ONR’s focus on transition from towbodies and divers to numbers of small, unmanned underwater vehicles (UUVs) to improve MCM clearance rates has had a major impact on sensor development as well. The presentation will provide an introduction to the session by providing a brief history of the development of navy imaging sonars, how they are employed, and an overview of the current thrusts that will lead to the next generation of Navy MCM sonars.

Multi-platform sonar concepts for buried target detection and classification

Buried target classification is of paramount importance in mine countermeasures (MCM) applications. The Generic Oceanographic Array Technology Sonar (GOATS) project approaches this fundamental problem by exploiting the assets of autonomous underwater vehicles (AUVs). Recent developments in unmanned vehicle technology have opened the door for new sonar design concepts that may be applied to create alternative target detection and classification methods in complex environments. Adaptive vehicle behaviors provide the potential for the sonar system to adjust its geometry for optimal performance. The vehicles can also access very shallow water environments, which allows for more complete multi-aspect views of targets of interest than are possible with remote towed array systems. In this paper, it is demonstrated that the multi-platform system can provide improved detection and classification capability, while at the same time reducing the computational requirements. Data from prior GOATS experiments (1998 and 2000) are used to illustrate the effectiveness of the multi-platform sonar concepts, and real-time simulations are used to show the planned implementation of these techniques on-board the AUVs for GOATS’02.

Buried target classification with bistatic synthetic aperture sonar

Buried target classification is of paramount importance in mine countermeasures (MCM) applications. Traditional methods use optimal detection techniques, e.g., monostatic synthetic aperture sonar (SAS) imaging, to classify objects by target shape. The shape of a target, however, does not necessarily indicate whether it is manmade (mine) or natural (rock), thus creating the possibility of an unacceptably high false alarm rate. Furthermore, the limited resolution available at the low frequencies required for seabed penetration may prevent the shape-based classification altogether, as the imaging wavelength is typically on the order of the target size. For these reasons, additional information about the character of the target is required. The current work investigates the use of frequency and aspect dependence of the target scattering for classification of canonical minelike targets, using a bistatic AUV-borne sonar receiver to interrogate spheres and cylinders in various burial conditions. Experimental evidence from goats98, an at-sea experiment performed off the coast of Elba Island, and supporting evidence from oases−3d models are used to demonstrate clear distinctions between these canonical targets, and to illustrate the potential of a multi-static system for rapid and robust MCM. [Work supported by ONR and SACLANT.]