Fusión de datos. ISR & Data Fusion Capabilities

Transcription

1 Fusión de datos ISR & Data Fusion Capabilities

2 Amper at a glance Comprehensive technology solutions & business practices Continued investments in our capabilities & resources Increased operational efficiencies & governance model Proven expertise in Defense, Security and Communications Unique combination of Innovative Business Practices, Services and Technological Solutions, Providing a single source for Customers across key markets segments 19 COUNTRIES 38 REGIONAL OFFICES +1,800 EMPLOYEES CUSTOMERS 420 ME EST. FY11 REVENUE 2

3 Our organisation 3

4 Enabling Technology Solutions DEFENCE COMMUNICATIONS SECURITY Virtual Workspace Cloud Services Borderless Networks Developing Command and Control solutions in an international scenario, over different networks infrastructure Enabling communications & collaboration anywhere, on any device anytime Enabling new models of procurement and consumption of IT services via Private & Public Clouds Deploying a robust, scalable an secure network infrastructure to support our customer s mission critical applications Developing high tech, flexible and effective solutions, to cover our customer s security needs Command and Control Systems Military Communications Systems Communication Networks Unified Communications and Collaboration Networks Infrastructure Mobility / M2M Digital Home Mobile Communications and Connectivity Border Surveillance Systems Emergency Management Systems Force Protection Data Processing Centres New Generation Networks Mobility Systems Avionics Navigation Aids Critical Infrastructure Protection Systems Cryptosystems 4

5 Systems deployed and in use More than 200 nodes delivered (fixed, deployable, mobile and man-portable) References: Simacet, Lince, FIS HE, SMCFEX, Siacom, Simbad, Trabuco, Wat... Three main references in C4ISR: Spain, Switzerland, Arabian Gulf country 5

6 Funciones de un sistema C4ISR Data fusion is the process of combining data to refine state estimates and predictions 6

7 Problema a resolver VIDEO ndvr VIDEO STREAM IP Multicast VIDEO STREAM VIDEO STREAM REAL TIME DATA RAW DATA TACTICAL DATA WCF Net Centric Data WCF ISR Client C4I ISR Server CONSOLIDATED DATA IN DB ISR Client Synch Data Base Server TCP-IP / UDP-IP / RADIO Synch Data Base Server 7

8 Data Fusion Framework 8

9 Border Surveillance System: SIVE Spanish Case Coastal surveillance stations SPAIN Regional operation centre Illegal immigration threat Radar Coverage Drug smuggling threat MOROCCO 9

10 System Structure: External Sensor Integration and Internal Functionalities nemesis BSS integrates external sensors, processes their signals and offers a Common Operational Picture to the operator Once the threat has been detected, the C4 functionalities mobilise all resources 10

11 Integrates external sensors in the C4 system The system integrates commercial sensors: Maritime radars, ground radars, thermal cameras, long range camera Radar RAYTHEON MSTT TERMA ELTA IP / SERIE FORUNO THALES BORA Camera TAMAM GMOSP - MOSP-D35 FLIR RANGER III - TH HRC 735 INDIGO PHOENIX PVP MVSP - LMVSP JVC TK GD AXIS EOS SENTINEL OCULOS 11

12 Early developments and system design First operational unit for demo/testing purposes SIVE awarded SIVE 2 nd phase awarded SIVE 3 nd phase awarded SIVE 4 th phase awarded SERBIA project awarded SIVE 5 th phase awarded ESTONIA project awarded SIVE 6 th phase awarded European Union GLOBE project: Integrated Border Mgt awarded New network enabled C4ISR SW version interoperable with ne.on (Amper Defence) and NEC 1 compliant SIVE 7 th phase awarded References Since 1998, when the Spanish border started to be deployed, until today, Amper has secured the maritime border of Spain, the fluvial and terrestrial border of Estonia and the terrestrial border of Serbia NEC: Network Enabled Capabilities 12

13 Data Fusion Process Flow Data Information Knowledge Understanding INPUT DATA: SIGINT ELINT COMINT HUMINT Level 0: IMINT Types: PHOTO Infrared RADAR Electro optical (OPTINT) - FOV UAV JSTAR Sensor Level Processing Level 1: Entity Level Processing Real-time, Automatic Processing with Human Monitoring & Control Level 4: Level 2: Situation Assessment Process Performance Refinement Level 3: Impact Assessment (Inference) 13

14 Level 0 - Functions Sensor Level Data Processing Raw Data Processing (e.g. Pulse Correlation) Raw Data Clustering (e.g. Signal Processing) Data Improvement (e.g. Grading, Filtering) 14

15 Level 1 - Functions Entity Level Data Processing Entity Grouping (e.g. Emitter Correlation) Entity Identification (e.g. Platform Classification) Entity Tracking (e.g. GEO calculation) Entity Activity Management Sensors Data fusion based on KAPLAN algorithm with quality control based on Association and Estimation mathematical processes. 15

16 Level 2 - Functions Battle Situation Assessment Target Grouping (e.g. Correlating Different Entities) Target Identification (e.g. Hull Classification) Target Tracking (e.g. Path, Speed, Activity) Environmental Data (e.g. Weather, 3D Maps) Order of Battle Dynamic Situation Formation Information Data fusion based on AI algorithms: Temporal and Spatial alignment Clusterisation, Fuzzy Logic 16 16

17 Level 3 - Functions Threat Assessment Forces Characterization (Type, Size, Ammunition) Forces Inter-relationships (communication, Hierarchy, Doctrine) Forces Movement Trends (Current and History) Forces Anticipated Intentions (Irregular Signs) Forces Posed Threats (Zone, Threat Range) Information Analysis based on ORBAT and Enemy Assessment, Use of BTN, C-BML and A* Path finding Algorithm with dynamic maps 17

18 BTN & C-BML The system will use a CGF engine based on Behavior transition Networks and C-BML to assess: Forces Anticipated Intentions (Irregular Signs) Forces Posed Threats (Zone, Threat Range) Attrition and final situation prediction 18

19 Level 4 - Functions Process Performance Refinement Mission Management (Assigning, Prioritizing) Sensor Control (Resource Usage, Timing) Unit Monitoring (Statistics, Fault Alerting) External Knowledge (Export, Import) Process Optimization (Feedback, Intervention) Statistical functions. Record management System, Reporting 19