Search and Rescue Optimal Planning System SAROPS Search and Rescue Optimal Planning System

Applied Science Associates, Inc.(ASA), Narragansett, RI SAROPS Technologies for Search, Assistance, and Rescue Seminar, Le Quartz, Brest, France, 18 – 20 October 2004 Malcolm L. Spaulding Applied Science Associates, Inc.(ASA), Narragansett, RI

SAROPS Team United States Coast Guard Northrop Grumman Applied Science Associates (ASA) Metron

ASA - SARMAP Model System

Search & Rescue Problem Create a SAR case when alerted Gather data, estimate uncertainties Use model to determine search area Estimate resource availability and capability Plan the next search Promulgate the search plan Perform the search plan Evaluate the completed search Repeat above until survivors are found and rescued

USCG Transition SARTools Joint Automated Worksheet (JAWS) Near-shore search planning Based on 1950’s paper & pencil technology Computer Assisted Search Planning (CASP) Offshore search planning Based on 1970’s technology SAROPS Technologically current software tool Near-shore and offshore search planning Extensible to land-based search planning

SAROPS Goals To provide fast, simple Search & Rescue predictions Minimize data entry and potential for error Automate data linkages Environmental data inputs Search Action Plan outputs Simple visualization of results

SAROPS Scenario Types Voyage scenario where object can pass through or loiter in a number of locations (positions or areas) using any combination of great circle and rhumb line routes Initial Position (with bivariate normal uncertainty) and time uncertainty for an event, plus an offset for initial location and time of distress Positions obtained from COSPAS-SARSAT, other GMDSS Lines of Bearing (from Radio Direction Finding, Flare Sightings, Loran, and others) Areas defined by polygons “Reverse Drift” scenarios Scenarios may be “weighted” COSPAS-SARSAT – Satellite based emergency beacon locator for search and rescue, GMDSS – Global Marine Distress Safety System

Probable Error of Turn Point Position Example Scenario Home Port Fishing Area A Fishing Area B Probable Error of Turn Point Position A Sample Voyage

SAROPS Components Graphical User Interface/ (GUI) Environmental Data Server (EDS) Simulator (SIM)

GUI Requirements Deployable on ESRI® GIS mapping engine (C/JMTK) Wizard based interface Minimize keystrokes Chart support (vector/raster) Display environmental data Animated display capabilities Display recommended search plans/areas/patterns Display probability maps (by scenario, object type or combined) Reporting C/JMTK – Commercial/Joint Mapping Tool Kit

GUI ENV. DATA SERVER Wind Data SRU Deployment Tools Current Data Simulator (SIM) Wind Data User Defined Point/Gridded Fields Regional Global Current Data Results SRU Deployment Tools ENV. DATA SERVER

SIM Requirements “Monte Carlo” (particle) simulation (random walk/flight) Simulate pre-distress motion & fixed hazards Simulate distress incidents and outcomes Simulate post-distress motion (drift) Calculate near-optimal search plan (max POS) Simulate simultaneous SRU and search object motion (use POD vs. range at CPA on each leg) Compute cumulative POS Account for effects of previous unsuccessful searching when recommending subsequent search plans. POD- probability of detection, POS- probability of success, SRU- search rescue unit, CPA –closest point of approach

SIM Particle Filter Sample Paths t1 t3 t2 Example Below: 10,000 particles, only 5 shown. Time t1 red ellipse Time t2 lavender ellipse Time t3 blue ellipse t1 t3 t2

EDS Requirements Surface current data Surface wind data Other (visibility, cloud cover, sea state, etc) Automatically accommodate variable spatial scales/resolution Select best data available Global land database Expansion of data products and uses

EDS Common File Format (netCDF) Gridded Point Finite Element SIM

How do they communicate? ASA Profile How do they communicate? GUI SIM Sarops COM Extension “launch process” SaropsSim Java NetCDF XML DBF all on same machine SIM->ENV tightly coupled SHP/ DBF EDS .NET Web Services

ArcGIS Mapping Framework ArcGIS based Architecture - Conceptual WWW C O P EXT ArcGIS Mapping Framework TMS GEBASE EDS Maptech MORE EXT’S 3D Analyst SAROPS Extension GUI SIM SAR Tools Extension Flares, Patterns, Etc Spatial - A GeoStat - A WeatherFlow * COP – Common Operational Picture, GEBASE – USCG GIS data distribution system C-Map Other…

SAROPS Screens (Initial Development)

SAROPS-EDS (COASTMAP) Currents:. User specified SAROPS-EDS (COASTMAP) Currents: * User specified * NOAA/NOS tidal currents * Global atlas * Navy global ocean hydrodynamic model * Lake, coastal, and estuarine hydrodynamic models * HF radar systems Winds: * User specified * Navy global meteorological model * NOAA/NWS station forecasts

Short and Long Range HF Radar Systems

Short range HF radar

NOAA Great Lakes Environmental Research Laboratory, Hydrodynamic Forecasting System

Narragansett Bay estuarine hydrodynamics model

Global, atlas based currents

ASA Profile C2 = sense, decide, act. --LT Thompson along with the SAROPS system had performed the SENSE function. Now he had to decide where to search and how best to search. --He fed the situational information into the SAROPS Wizard which included things like search object type (42’ deep keel s/v, 6 per liferaft*) the MST etc…SAROPS then produces a probability map of where the search objects are computed to be. The SARSAT hit implies the vessel may have been lost --Success means looking in the right place, finding the search object and rescuing in time. Mathematically this equates to POS=POC x POD within a period of survivability. DECIDE --SAROPS has an optimizer to compute how to maximize POS given a particular probability density distribution and set of rescue resources. In this case there was a helo, a c-130 and WPB. The solution was to break the area into halves and search with a/c while keeping the WPB on scene to assist. ACT -- Today was a good day, the helo spotted AMERICAN under partail sail on its second leg. The helo handed off watch to the C-130 until the WPB arrived to escort AMERICAN under Capt Herndon’s control back to port.

Related Development Demonstration of linkage of SAROPS/ SARMAP to high frequency radar surface current data Sponsor: US Coast Guard, Research and Development Center Project Team: Anteon, ASA, University of RI and CT, and Rutgers University

Major Study Components Link HF radar (Block Island Sound(BIS) and Mid Atlantic Bight (MAB)) to SARMAP/SAROPS Extend development of short term forecasting system to include wind forcing Compare random walk and random flight model predictions, using HF radar as input, to observed trajectories of 7 drifting buoys deployed in BIS and MAB Demonstration of integrated system in operational setting for USCG