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 advanced development 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 under a Phase I & Phase II SBIR for PMS-485. A data dependent hole-fill algorithm “CHRP-D” is currently being implemented in real-time hardware for use in ICP, but has much broader applications than SURTASS, and can be used with any array that contain equally spaced channels.

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. This beamformer is currently being used for the MFTA array in the AN/SQQ-89A(V)15 program. We have also developed and implemented a class of conventional beamformer for arrays with arbitrary shapes, including options for length pruning, sub-aperture selection/formation, 3 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 with a Phase I and Phase II SBIR for the SURTASS program 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). 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 5 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 4-array full-scale evaluation test (FET). This ABF uses an iterative 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, processing of a high-frequency acoustic intercept array for the AN/SQQ-89 program, and was implemented in late 2005 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 a 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 that is now transitioning to a Phase II Development, and also for a torpedo defense active beamforming application for ONR. The success of STABB comes from its ability to rapidly adapt. 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.

In Phase I we demonstrated, with in-water MF active test data, an order of magnitude improvement in vertical localization capability using our Short-Time Broadband Adaptive Beamformer (STABB) as compared to conventional Beamforming (CBF). In addition, STABB was demonstrated to provide up to 20 dB more rejection against highangle near-field reverberation than does CBF. This is shown in the significantly improved vertical resolution in the ABF data, as well as elimination of early bottom returns that are apparent in the CBF data.

Failed Channel Recovery (CHRP-D)

In 2003 Adaptive Methods was awarded a Phase I SBIR to develop methods to recover performance due to failed channels in ULAs. This lead to a Phase II award in 2004 that is ongoing. The focus of that work has been to develop algorithms to synthesize data for failed channels to recover array gain and sidelobe 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 do to poor sidelobe 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.