Mission Systems

Fusion & Display

As the Navy modernizes its ASW platforms, integrates additional sensor capabilities and strives to improve overall war fighting capabilities, companies such as Adaptive Methods are providing state-of-the-art, innovative solutions to effectively unravel the complex at-sea Battle Space environment.

Adaptive Methods is the designer, developer, and integrator of the Data Fusion Functional Segment (DFFS) that provides centralized sonar operator workstation for all sensors. DFFS provides interfaces with new high-performance ASW sensors and improved target detection/classification/tracking performance, while reducing operator workload. Introducing DFFS within the modern surface ship USW COTS-based architecture provides a rapid and affordable fleet transition of a unified operator analysis workstation on DDG and CG platforms.

We have built a successful record of integrating Fusion, Contact Management, and Display concepts into working Data Fusion Systems. Our technologies and system architecture are used in: the Navy’s Improved Performance Sonar (IPS) Data Fusion Functional Segment (DFFS) to provide active and passive acoustic sensor contact association with various organic and off board sensor tracks; the SQQ-89 A(V)15 Build 2 as the DFFS, which provides TMA and Contact Management functionality; and the Littoral Combat Ship (LCS) ASW Mission Package Data Fusion and Contact Management (DFCM) System for inter Mission Module contact association and management.

• Open Architecture compatible
• Distributed data fusion architecture
• Federated system display integration techniques
• FORCEnet compatible backend
• Fusion Engine
• Display Engine
• Pluggable distributed interface gateways

Products

JavaGEO

GEO is an open source Java package for rendering geographic map data and overlays of user specified data. Our typical application is ASW contact tracking displays

Modeling & Simulation

The Modeling and Simulation Group at Adaptive Methods is a leader in the research and development of underwater acoustic simulation-based tools for the Navy. Members of the Adaptive Methods ModSim Group are recognized experts in the fields of underwater acoustic modeling, especially modeling for multi-statics. Adaptive Methods is the designer, developer, and integrator of the Active System Performance Estimate Computer Tool (ASPECT), the multi-static sensor mission planning tactical decision aid (TDA) for fleet use for both the Extended Echo Ranging (EER) and the Improved EER (IEER) systems. Adaptive Methods is also integrating advanced Java-based ASPECT mission planning modules into the NITES II OOR architecture for Air ASW mission planning in the Tactical Support Centers.

Adaptive Methods served as the leaders of the software development effort for the Tactical Acoustic Measurement and Decision Aid (TAMDA) system, a next-generation measurement and processing system for rapid at-sea environmental adaptation.

Products:

GAMUT

GAMUT is the Generic Acoustic Modeling Universal Toolkit. Originally conceived and developed at Adaptive Methods, GAMUT is a toolkit of reusable objects that can be easily interconnected to create acoustic modeling and simulation applications. GAMUT components are written in Java.

FORCEnet ASPECT - Active System Performance Estimate Computer Tool

FORCEnet ASPECT is the next-generation mission planning tool developed at Adaptive Methods. It is based on the Active System Performance Estimate Computer Tool (ASPECT), the Multi-Static TDA. FORCEnet ASPECT will be initially developed as a standalone product with concurrent integration into the Naval Integrated Tactical Environmental Subsystem II Object Oriented Re-design (NITES II OOR) product. FORCEnet ASPECT is being developed to be compatible for interoperation with other FORCEnet-compatible entities.

ASSESS - Active Source / Safe Environment Simulation Software

The objectives of this software tool will be to provide "the end user visibility into the environmental impacts and alternate courses of action that would mitigate any proposed action". The development of this tool will require:

• Design and development of a comprehensive marine mammal database to include such information as location and migration specifications, frequency dependent hearing sensitivity, communication frequencies, and (to assess impact of explosive sources) tissue density measurements;
• Use of state-of-the-art, validated acoustic models, environmental databases, and methods for evaluating the potential impact of active sonars and sonobuoys in complex sub-littoral and other coastal environments; and
• Design of well thought out software to allow for: efficient implementation of future Navy systems, minimal effort on the part of the end user, broad-based access from multiple hardware platforms in various locations, and adaptation to similar veins of research.

EMP - Environmental Mission Planner

To support the planning, deployment and operation of environmental sensors, a total system solution is needed for the software to support the sensor. This software must address three important phases of the mission associated with the environmental sensor. First, the software will be used to plan the deployment strategy for the sensors. Next, the software will be used during deployment and operation of the sensors, to receive and process information from the sensors, and to reassess tactical performance and planning based on the information received. Finally, the software will be required to perform post-mission analysis of the data and to provide mechanisms for the data from the sensor to be properly archived for later use and analysis.

ESSS - Environmental Sensor Simulation System

The proposed Environmental Sensor Simulation System (ESSS) will accurately represent the spatial, azimuthal and temporal dependencies that exist in the ocean environment. The bottom sediment, which is so important in shallow water active acoustics, will also be represented. ESSS’s role will be as a dynamic ocean model that other processes will use, such as inversion algorithms and sensor placement computations.

Legacy ASPECT

ASPECT is the Active System Performance Estimate Computer Tool, the Multi-Static TDA (Tactical Decision Aid). It computes estimates of system performance for active underwater acoustic sensors. ASPECT is written primarily in C and interfaces with a number of Navy standard models and databases. ASPECT will eventually be superseded by FORCEnet ASPECT-- an application developed using modules from the Generic Acoustic Modeling Universal Toolkit (GAMUT).

 

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Advanced Development

Adaptive Methods has performed advanced development work for the U.S. Navy and prime contractors since its incorporation in 1973. Our advanced development goals are to transition new signal and information processing technologies to fleet operational systems. Our products are comprised mainly of sonar signal processing algorithms such as conventional and adaptive beamformers for passive and active applications, detection and classification algorithms, tactical decision aids, sensor-array shape estimation algorithms, and multi-sensor data fusion algorithms. In addition, the Advanced Development Group provides systems engineering services, hydrodynamic modeling, tow body design and fabrication, and test & evaluation support to the U.S. Navy and prime contractors.

Signal Processing Developments

Adaptive Methods’ advanced development algorithms and technologies are integrated into broadly applicable software applications that support a variety of Navy programs. Many of these algorithms are developed in a peer-review environment, providing an opportunity for our developers to interact with leading experts in the field.

Adaptive Methods has developed & implemented a variety of conventional beamformer (CBF) algorithms with wide applications in uniformly spaced line arrays (ULAs) and many other array designs. These beamformers include real-time array shape estimation (ASE), array shape correction (ASC), and range focusing. We have developed and implemented a number of adaptive beamformer (ABF) algorithms for Navy technology demonstrations and fleet systems.

The Robust Estimate and Plug (REAP) ABF algorithm was initially developed for the Advanced Deployable System (ADS) program and later used for a SURTASS TwinLine TB-29 demonstration test in conjunction with the Submarine Superiority Program. It is also being used in a torpedo defense application for small high-frequency volumetric arrays such as the ACI, AACI, and SPVA.

Another ABF algorithm developed at Adaptive Methods that has been applied in a wide range of Navy programs is the Short-Time Adaptive Broadband Beamformer, or STABB. This novel frequency-domain algorithm can adapt to the in-situ noise field in a single spectral update, making it suitable for adaptive spatial processing of highly dynamic signal and noise fields such as active pings in reverberation, and close passive engagement scenarios.

Adaptive Methods also developed a highly efficient beam-based ABF (TwinLine AIC) for the SURTASS TwinLine program that is currently integrated into the ARCI(I) system and in fleet use. We also integrated this algorithm into a beamformer we provided for the IUSS Common Processor (ICP) program for PMS-485. To recover lost performance due to dead sensors in uniformly spaced line-arrays (ULAs) but without resorting to the large increase in processor horsepower necessary with ABF, Adaptive Methods has developed a series of adaptive “hole-fill” techniques for PMS-485.

CBF

Adaptive Methods has developed a number of CBF algorithms with a variety of options that support a wide range of array designs. We are constantly improving beamforming algorithms to maintain a competitive edge. We have developed and implemented a frequency-wavenumber DeMuth beamformer for long ULA’s with highly efficient array shape correction (ASC), range focusing, and true-bearing stabilization options. In the DeMuth beamformer, ASC is implemented as a wavenumber domain convolution, saving significant processing power vs. a conventional dot product beamformer. We have also developed and implemented a class of conventional beamformers for arrays with arbitrary shapes, including options for length pruning, sub-aperture selection/formation, three-dimensional steering, pitch/roll compensation, and true-bearing stabilization. The AN/SQS-53C hull array beamformer Adaptive Methods has provided for A(V)15 Build-0 is a good example implementation of this type of beamformer. Lastly, as part of the ICP program for SURTASS mobile arrays, we implemented a length-pruned conventional beamformer with real-time array shape correction. This is followed by a beam-space adaptive beamformer, which is described in other sections.

Array Shape Estimation (ASE)

Adaptive Methods has been active in the area of ASE algorithm development for many years, beginning in the 1980’s, where we developed algorithms as well as compared a variety of different methods using beamformer output metrics. Later we developed ASE algorithms for SURTASS TwinLine (1993-1996), and Ardent (1999-2004), and have been active in developing and implementing ASE algorithms for the AN/SQQ-89 program. For TwinLine and Ardent, the shape is estimated from heading, depth, and acoustic Shape Measurement Units (SMUs). As an example, TwinLine shape is shown below using modeled data -- with and without errors. As the logical next step, we developed and implemented shape correction algorithms in several conventional beamformers, including SURTASS TwinLine. For details, see the CBF section.

Robust Estimate and Plug ABF (REAP)

In the late 1990’s Adaptive Methods (then Applied Hydro-Acoustics Research, Inc.) participated in an ABF algorithm development for the Advanced Deployable Systems (ADS) program sponsored by PMW-182. There was a competition among five organizations, all of whom brought an ABF to the table. After an 18-month competition, it came down to two algorithms with essentially the same performance, and one was REAP. Given the efficiency of the algorithm, REAP was chosen and implemented in real-time hardware for a four-array, full-scale evaluation test (FET). This ABF uses an interactive white noise gain constraint to control main-lobe shape and sensitivity to mismatch. The implementation for ADS has the noise gain capability of a single gain constraint MVDR with the main-lobe control of a multi-point constraint algorithm, and only a 10% increase in processing load vs. a MVDR adaptive beamformer without white noise gain control. This algorithm, and variants, has been used for several advanced developments including a SURTASS TwinLine TB-29 demonstration acoustic trial and processing of a high-frequency acoustic intercept array for the AN/SQQ-89 program. The algorithm was implemented in real-time hardware with an exact hard-constraint option for a torpedo defense project. The figure shows how REAP controls the main-lobe and side-lobe response to loud contact for various white noise gain control settings.

Short-Time Adaptive Broadband Beamformer (STABB)

The Short-Time Adaptive Broadband Beamformer (STABB) was initially developed by Adaptive Methods for an active AN/SQS-53C hull array application under a Navy SBIR program, but STABB has now been successfully applied for AN/SQS-53C hull array passive beamforming in the IPS program, submarine broadband high-resolution noise source localization for NSWC-CD in the Source Localization and Analysis Work Station (SLAWS), high-resolution vertical localization in an active sonar application for mine-avoidance and also for a torpedo defense active beamforming application for ONR. The success of STABB comes from its ability to adapt rapidly. Implemented in the frequency-domain, STABB uses bandwidth (not time) for covariance estimation, allowing for extremely rapid adaptation. In addition, built-in rank reduction lets the algorithm be tailored for each application – trading degrees of freedom for execution speed. An integral robustness constraint is used to control the width of the main-beam, and the response to sources of mismatch. The ability of STABB to improve localization is dramatic. An example is shown in the figure below.

Failed Channel Recovery (CHRP-D)

Adaptive Methods has been focusing their efforts in developing algorithms to synthesize data for failed channels to recover array gain and side-lobe control. The most promising of these methods was a data-dependent channel repair method called CHRP-D. This algorithm adaptively estimates and fills dead channels using a linear least-squares estimator. The plot below shows a cumulative distribution of beam noise levels from a good ULA, a ULA with 10% of the channels dead, and ULA performance with CHRP-D hole-fill. Beam noise levels in quiet regions are filled in due to poor side-lobe control with dead channels, and this performance is recovered with CHRP-D. Adaptive Methods is currently implementing this algorithm in real-time hardware for inclusion in a future ICP build.