1. Search and Rescue Optimal Planning System
SAROPS
Search and Rescue Optimal Planning System

2. SAROPS Team United States Coast Guard Northrop Grumman
Applied Science Associates
Metron

3. 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

4. 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

5. C2PC(CG) / SAR-PC typical view…

6. CASP Typical View via C2PS/SAR Tools

7. SAROPS Prototype Display
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.

8. SAROPS Goals To provide fast, simple Search & Rescue predictions
Minimise data entry and potential for error
Automate data linkages
Environmental Data Inputs
Search Action Plan Outputs
Simple Visualization of Results

9. 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”

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

11. 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

12. 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

13. 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

14. SIM Requirements “Monte Carlo” (particle filter) simulation
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.

15. Future SIM Enhancements
Multiple-rectangle Optimal Search Plans
Optimal Survivor Search
Canadian Cold Environment Survival Model
Moving Hazards (Storms, Fronts, etc.)
Improved Detection (sensor) Modeling

16. EDS Requirements Water current data Wind data
Other (visibility, cloud cover, sea state, etc)
Accommodate scales/resolutions automatically
Global land database
Expansion of data products and uses

17. EDS
Common File Format
Gridded
Point
Finite Element
SIM

18. 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

19. 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
C-Map
Other…

20. SAROPS Prototyping

21. Example of Fixed Hazard

22. Example of Fixed Hazard

23. Example of Fixed Hazard

27. SAROPS/CODAR Estimate
Tidal Only
SAROPS/CODAR Estimate
Actual Drift

36. Thank You!