1. from http://www.dodsbir.net/solicitation/pdf/navy041.pdf
SBIR N04-022 TITLE: Airborne and Air-Deployed Multi-Sensor Search Optimization
TECHNOLOGY AREAS: Sensors, Electronics, Battlespace
ACQUISITION PROGRAM: Air ASW Systems
OBJECTIVE: Develop the capability to optimize over-water and over-land searches for multiple
stationary and moving targets conducted using multiple sensor technologies either on or
deployed from maritime patrol aircraft and unmanned air vehicles.
DESCRIPTION: The most common practice for planning antisubmarine warfare (ASW) search
operations (a legacy of deep-water World War II submarine-hunting strategy) is to use sensor
performance predictions based on historical environmental data (sometimes enhanced by a few
in-situ measurements) and from them calculate the “R50 range-of-the-day,” i.e., the estimated
range where the probability of detection is 50 percent. A single ship steams along ladder tracks
spaced at twice R50 or an aircraft lays a standard sonobuoy pattern with spacing of 1.5 times
R50. However, search operations are now required and conducted in near-shore, littoral regions
(where water and sediment properties and local oceanographic features are very complex) and
onshore regions (which are even more complex) for many more target types than in the past.
Environmental complexity can cause R50 detection ranges to vary dramatically from point to
point and in various directions from a single point, thus violating the homogeneous, isotropic
assumptions underpinning standard tactics. Legacy ladder search patterns and equally spaced
sonobuoys tend to significantly under-perform in comparison with more advanced search
planning concepts in complex environments because they allocate effort nonoptimally; i.e., too
much effort in some areas and too little effort in other areas.
Modern reconnaissance aircraft typically carry a variety of sensors on board and can deploy
other sensors at will (until the supply is exhausted). These sensors often have dramatically
different sensitivities at different altitudes and under different meteorological conditions: what is
good for sensor A is marginal for sensor B and precludes use of sensor C. These sensitivity
envelopes also vary depending on the target being searched. Unsurprisingly, it is very difficult
for even an expert tactician to provide an optimal search plan for a single target in a complex
area or a variety of targets in a simpler area, and almost impossible for multiple targets using
multiple sensors in a complex area. The Navy is seeking algorithms that can integrate several
types of information and form near-optimal search plans. Algorithms must interface with
networks to gather information from accurate range-dependent sensor prediction tools for a
variety of acoustic and nonacoustic sensors using real environmental data under a variety of
flight conditions (altitude, airspeed, etc.) They must accurately account for mutual interference
problems when sensors operate simultaneously. They must also account for platform location,
capability (speed, ability to turn, sensors carried, etc.), and availability (e.g., deployable sensors
such as sonobuoys are limited to storage capacity). The algorithms’ objective function (their
measure of effectiveness (MOE) such as maximized cumulative probability of detection,
minimized time elapsed to meet a detection probability threshold, maximized probability of
survival, etc. and combinations thereof) must be general (i.e., not hardwired), so that the user can
tailor them to suit present needs. Consideration should be given to true probabilities to prevent

2. double counting of detections; various target characteristics; expected distributions in the search
area; likely behavior of each once it detects the attempt to search for it. The algorithms must
perform these tasks for any arbitrary set of targets conjointly.
PHASE I: Design a conceptual approach, with sufficient mathematical, operations analysis, and
statistical support, that contains a variety of sensor types and mission parameters. Simulate sets
of controlled, but realistic, sensor performance data and evaluate the validity of the proposed
concept. Show the value of optimal search planning and the need for joint sensor usage.
PHASE II: The design must be compatible with ongoing Navy software architecture goals under
the Seapower 21 vision. Build a prototype tactical decision aid system that exploits
environmental, sensor, and threat information to make maximal use of available sensors. The
prototype system should be moderately user-friendly and contain innovative displays that
facilitate the decision process.
PHASE III: Enhance the system for efficiency, integrate it with naval coastal warfare
architectures, and improve the interfaces to allow use and evaluation by Fleet operators in a
laboratory environment.
PRIVATE SECTOR COMMERCIAL POTENTIAL: Applications of this technology include
commercial fishing, search and recovery missions, ocean monitoring, seismic studies, mineral
prospecting, and oil exploration.
REFERENCES:
1. Koopman, B.O. Search and Screening. Operations Evaluation Group Report 56, Navy
Department, 1946. Reprinted (with additions) as Search and Screening: General Principles with
Historical Applications. Pergamon Press, 1980.
2. SEAPOWER 21 Vision, Offices of: Chief of Naval Operations, Secretary of the Navy, and
Commandant of the Marine Corps, 2002.
3. Common Undersea Picture Top Level Requirements Document, Revision 15, October 2002
(PEO(IWS5)).
KEYWORDS: Search Planning; Decision Aids; Acoustic Sensors; Nonacoustic Sensors;
Bayesian Statistics; Data Fusion
TPOC: Electronics Engineer
Phone: (301)-342-2494
Fax: (301)-342-2098
2nd TPOC: Electrical Engineer
Phone: (301)-342-2050
Fax: (301)-342-2098