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Home > Technologies >Mission Planning > Search Optimization > AMP Decision Support System Testbed
Acoustic Mission Planner (AMP) Acoustic
Optimization for MH-60R Multi-Mission Helicopter
Lockheed Martin Systems Integration-Owego awarded Wagner Associates
a multimillion dollar contract to develop an Acoustic Mission
Planner (AMP) for the Navy's new MH-60R Multi-Mission Helicopter and AMP is
currently undergoing flight testing. AMP is embedded in the MH-60R avionics software and
also in the shipboard Mission Planning Station (MPS). The dynamic
search optimization algorithm utilized in AMP is based on Wagner's NORDA Environmentally Sensitive Sonobuoy Tactic (NESST) algorithm.
In AMP this NESST optimization algorithm works in concert with Wagner's Non-Gaussian
Data Fusion Module (NGDFM). The NGDFM, a Monte Carlo non-Gaussian tracker,
more accurately estimates target positions at any time of interest
than a Gaussian Kalman filter. NGDFM is used
to generate a space-time target probability distribution, using
Monte Carlo target motion models and Bayesian statistical models,
that is updated in real-time for both "positive" contact
reports and "negative" search information from non-detection
of the target. NGDFM also uses estimates of target tactics and the
presence of obstacles (such as land when the target is a submarine or ship),
and accurately projects target location into the future based on the fusion of
all available data. The optimization algorithm combines a global optimization
scheme for using the dipping sonar and dropping sonobuoys, based
on Brown's algorithm, with a local heuristic for flight path
selection.
In operational use the AMP optimizer computes a
complete route with search locations for the helicopter at the
beginning of the mission. Each deployment of the dipping sonar,
or of an expendable bathythermograph (XBT), will return environmental
data that will be used to update the estimate of sensor performance. Based on this new data, the embedded system will re-run the optimization
algorithm, improving overall mission performance in the latter
portion of the search.
Why
Non-Gaussian Methods?
Non-Gaussian methods are necessary since they allow the estimated
target position to be represented as an arbitrary probability
distribution, and after applying negative information the target
distribution is rarely a multi-variate normal Gaussian ellipsoid.
In addition, the NGDFM utilizes non-Gaussian techniques when
processing contact reports which contain target location information
that is not well represented by a Gaussian ellipsoid. For example,
the NGDFM processes a line-of-bearing (LOB) using all available
information such as transmission loss (TL) along the LOB and
system performance along the LOB. In the case of a passive acoustic
detection obtained on a particular beam, this could involve generating
range-dependent TLs, using, for example, the Acoustic System
Performance Model (ASPM), and then calculating the Figure-of-Merit
(FOM) on the beam. The FOM computation uses measured or computed
beam noise, the best available estimate of target source level,
and a recognition differential (RD) based on the types of processing
and analysis being used to analyze data on the beam.
Processing all of the available data related to targets of
interest using non-Gaussian techniques is the only way to extract
the maximum amount of information concerning target location,
at any time of interest, from the huge quantity of available
data. Since NGDFM processes all of this data as accurately as
possible, taking into account all available information concerning
target identification, the true non-Gaussian nature of the contact
data, non-homogeneous environmental conditions, and sensor capabilities,
it produces a very accurate estimate of target location. In addition,
its estimates of target location are used as inputs to optimal
resource allocation tools, which allows us to optimize the utilization
of both active and passive signal processing resources
Example
of Sensor Optimization
The example is based on a target that is initially
detected in an ellipse, is moving randomly, and is at one of
four target depths (25, 150, 300, 500). The Advanced Low-Frequency
Sonar (ALFS) can be placed at any of three sensor depths (25,
150, 500). Figure 10 shows the recommended ALFS search plan against
the target, given 100 minutes to search and a SH-60R starting
point in the center of the ellipse. This plan achieves a Cumulative
Detection Probability (CDP) of .86.
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The algorithms used in AMP were originally
developed for the SH-60R Decision Support System Testbed (DSST),
under the sponsorship of the Naval Air Systems Command, as part
of a NSWC-DD Phase III SBIR contract. A government point of contact
for this work is James P. Lynch, III of NSWC-DD, who can be reached
at (540) 653-5426 or by email at jlynch@nswc.navy.mil.
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