Numerica's Core Technologies

Numerica’s Core Technologies

Innovation for the Most Challenging Environments

Numerica solutions provide new levels of actionable information to decision makers, and our advanced algorithms and software are deployed in systems around the world. As a non-traditional small business defense contractor, Numerica employs world-class scientists, engineers and software architects deliver state-of-the-art technology.

MULTI-HYPOTHESIS CORRELATION FOR C2BMC

With Multiple-Hypothesis Correlation (MHC) and full integration to Command-and-Control Battle Management Communications (C2BMC) track correlator, users gain a more accurate and complete integrated system track picture. Accurately determine the severity of threats through ambiguity assessment, Joint Association and Bias Estimation (JABE) and flight phase analysis.

BALLISTIC LAUNCH ESTIMATION ALGORITHM (BLEA)

Through sophisticated algorithms, users can now track launch events into families including multiple flight phases, interceptors, and BOA processing track data from sensors within the C2BMC enterprise. Gain superior situational awareness with the ability to resolve closely spaced launch activity on both boosting and midcourse ballistic objects.

BSTAR

BSTAR is C2BMC’s next-generation batch track correlation solution with the ability to fuse complex evolving scenes and maintain custody of sensor discrimination data. With feature-aided track correlation, users can view sensor data for advanced discrimination support.

RESOURCE MANAGEMENT

Originally developed for the Missile Defense Agency (MDA) under multiple Small Business Innovative Research (SBIR) awards and deployed to automate Numerica’s Telescope Network (NTN), Numerica offers an optimization-based approach for the adaptive allocation of limited sensor and weapon resources. Online replanning adapts to dynamically evolving threats and allows graceful degradation even during the most stressful situations, such as raids. This includes joint Sensor Resource Management (SRM) and Battle Management (BM), allowing users to optimize for peak performance.

TRACK-BEFORE-DETECT (TbD)

Numerica’s innovative approach to multi-target detection in multi-frame image data, improves sensor performance through enhanced detection of dim maneuvering targets with low false alarms and rapidly resolve closely spaced targets. Demonstrated in Overhead Persistent Infrared (OPIR) Image processing on Hypersonic and Ballistic Tracking Space Sensor Satellites (HBTSS)/Mission Data Processing Application Provider (MDPAP), as well as Electro-Optical (EO) image processing on NTN data, Numerica has also deployed TbD on Its Spyglass Short Range Air Defense (SHORAD) radar, resulting in a significant increase in detection range without an increase in transmit power.

DISTRIBUTED TRACKING AND SENSOR FUSION

Offering fully distributed tracking and multi-sensor fusion for threats across all domains and sensor modalities on both fixed and moving platforms. Successfully deployed in Integrated Air and Missile Defense Battle Command System (IBCS), other Integrated Air and Missile Defense (IAMD) programs, as well as Numerica’s MIMIR C2 software and Spyglass radar system.

JOINT TRACK MANAGEMENT CAPABILITY (JTMC) BRIDGE

Numerica’s team has extensive experience in developing cross-network composite tracking and joint engagement technologies. Included in this technology portfolio is an implementation of the Joint Track Management Capability Bridge interface that enables integrated multi-sensor composite tracking across diverse DoD sensor networks.

AUTOMATIC SENSOR ALIGNMENT

Fully distributed and automated, multi-sensor alignment software ensures an accurate and common representation of all sensor data critical to achieving high precision and integrated fire control.

ELECTRONIC PROTECTION

Offering new algorithms for mitigating electronic attacks on distributed sensor networks, Numerica provides cutting-edge capabilities for electronic protection of distributed sensor networks.

Credibility

Read some of our peer-reviewed papers to see why we’re regarded as thought leaders in air defense, missile defense, & image processing.

 

Our growing list of patents demonstrates our contribution to the state of the art in Air and Missile Defense.

 

INFORMATION-BASED DATA PRIORITIZATION IN DISTRIBUTED TRACKING SYSTEMS

N. Coult, J. N. Knight, W. Leed, S. Danford, R. Paffenroth, and A. Poore, “Information-based data prioritization in distributed tracking systems,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 8393, Apr. 2012.

AMBIGUOUS DATA ASSOCIATION AND ENTANGLED ATTRIBUTE ESTIMATION

D. Trawick, P. C. Du Toit, R. C. Paffenroth, and G. J. Norgard, “Ambiguous data association and entangled attribute estimation,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 8393, Apr. 2012.

NETWORK-CENTRIC ANGLE ONLY TRACKING USING RANK-DEFICIENT FILTERING

N. Coult and J. N. Knight, “Network-centric angle only tracking using rank-deficient filtering,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 7698, Apr. 2010.

ASSOCIATION AMBIGUITY MANAGEMENT IN MIXED DATA DIMENSION TRACKING PROBLEMS

J. R. Thornbrue, J. N. Knight, and B. J. Slocumb, “Association ambiguity management in mixed data dimension tracking problems,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 7698, Apr. 2010.

A TRACKER ADJUNCT PROCESSING SYSTEM FOR RECONSIDERATION OF FIRM TRACKER DECISIONS

D. Trawick, B. Slocumb, and R. Paffenroth, “A tracker adjunct processing system for reconsideration of firm tracker decisions,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 7698, Apr. 2010.

A DISTRIBUTED DATABASE VIEW OF NETWORK TRACKING SYSTEMS

J. R. Thornbrue, J. N. Knight, and B. J. Slocumb, “Association ambiguity management in mixed data dimension tracking problems,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 7698, Apr. 2010.

MULTIPLE HYPOTHESIS CORRELATION IN TRACK-TO-TRACK FUSION MANAGEMENT

A. B. Poore, S. M. Gadaleta, and B. J. Slocumb, “Multiple hypothesis correlation in track-to-track fusion management,” Handbook on Modeling for Discrete Optimization (International Series in Operations Research & Management Science), Gautam Appa, Leonidas, (Boston, MA), 2006.

SURVEILLANCE RADAR RANGE-BEARING CENTROID PROCESSING, PART II: MERGED MEASUREMENTS

B. J. Slocumb and D. L. Macumber, “Surveillance radar range-bearing centroid processing, part II: merged measurements,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 6236, May 2006.

COMPLEXITY REDUCTION IN MHT/MFA TRACKING: PART II, HIERARCHICAL IMPLEMENTATION AND SIMULATION RESULTS

B. J. Slocumb and A. B. Poore, “Complexity reduction in MHT/MFA tracking: part II, hierarchical implementation and simulation results,” in Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 6236, Apr. 2006

SHORT-TERM AMBIGUITY ASSESSMENT TO AUGMENT TRACKING DATA ASSOCIATION INFORMATION

S. M. Gadaleta, S. M. Herman, S. A. Miller, F. Obermeyer, B. J. Slocumb, A. B. Poore, M. Levedahl, and B. Brewington, “Short-term ambiguity assessment to augment tracking data association information,” Proc. of the 8th International Conference on Information Fusion, (Philadelphia, PA), Jul. 2005.

A MULTIPLE MODEL SNR/RCS LIKELIHOOD RATIO SCORE FOR RADAR-BASED FEATURE-AIDED TRACKING

B. J. Slocumb and M. E. Klusman III, “A multiple model SNR/RCS likelihood ratio score for radar-based feature-aided tracking,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 5913, Sep. 2005.

FRAME BUILDING ALGORITHM FOR ELECTRONICALLY SCANNED ARRAY RADAR

B. J. Slocumb, M. E. Klusman III, “Frame-building algorithm for electronically scanned array radar,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 5913, Sep. 2005.

BATCH MAXIMUM LIKELIHOOD (ML) AND MAXIMUM A POSTERIORI (MAP) ESTIMATION WITH PROCESS NOISE FOR TRACKING APPLICATIONS

A. B. Poore, B. J. Slocumb, B. J. Suchomel, F. H. Obermeyer, S. M. Herman, and S. M. Gadaleta, “Batch maximum likelihood (ML) and maximum a posteriori (MAP) estimation with process noise for tracking applications,”Proc. of the SPIE, Signal and Data Processing of Small Targets, 2003.

TRACKING CLOSELY-SPACED, POSSIBLY UNRESOLVED, RAYLEIGH TARGETS: IDEALIZED RESOLUTION

W. D. Blair, B. J. Slocumb, G. C. Brown, and A. H. Register, “Tracking closely-spaced, possibly unresolved, Rayleigh targets: idealized resolution,” Proc. of the 2002 IEEE Aerospace Conference, vol. 4, 2002.

MULTIPLE FRAME CLUSTER TRACKING

S. Gadaleta, M. Klusman, A. B. Poore, and B. J. Slocumb, “Multiple frame cluster tracking,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 4728, 2002.

Our growing list of patents demonstrates our contribution to the state of the art in Image Processing.

 

PIXEL-CLUSTER DECOMPOSITION TRACKING FOR MULTIPLE IR-SENSOR SURVEILLANCE

S. M. Gadaleta, A. B. Poore, and B. J. Slocumb, “Pixel-cluster decomposition tracking for multiple IR-sensor surveillance,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 5204, 2003.

MAXIMUM LIKELIHOOD NARROWBAND RADAR DATA SEGMENTATION AND CENTROID PROCESSING

B. J. Slocumb and W. D. Blair, “Maximum likelihood narrowband radar data segmentation and centroid processing,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 5204, 2003.

EM-BASED MEASUREMENT FUSION FOR HRR RADAR CENTROID PROCESSING

B. J. Slocumb and W. D. Blair, “EM-based measurement fusion for HRR radar centroid processing,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 4728, Aug. 2002.

SURVEILLANCE RADAR RANGE-BEARING CENTROID PROCESSING

B. J. Slocumb and W. D. Blair, “EM-based measurement fusion for HRR radar centroid processing,” Proc. of the SPIE, Signal and Data Processing of Small Targets, vol. 4728, Aug. 2002.

Our growing list of patents demonstrates our contribution to the state of the art in SDA.

 

SYSTEM AND METHOD FOR SPACE OBJECT DETECTION IN DAYTIME SKY IMAGES

Jeffrey Hale Shaddix, Austin Tyler Hariri, Jeffrey Michael Aristoff, “Method and system for space object detection in daytime sky images” U.S. Patent Publication Number 10740609 B1, Issued on 11 August 2020.

METHOD AND SYSTEM FOR PREDICTING A LOCATION OF AN OBJECT IN A MULTI-DIMENSIONAL SPACE

J. T. Horwood, “Method and system for predicting a location of an object in a multi-dimensional space.” U.S. Patent Publication Number US8938413 B2, Issued on 20 January 2015.

METHODS AND SYSTEMS FOR UPDATING A PREDICTED LOCATION OF AN OBJECT IN A MULTIDIMENSIONAL SPACE

J. T. Horwood, “Methods and systems for updating a predicted location of an object in a multidimensional space.” U.S. Patent Publication Number US8909589 B2, Issued on 9 December 2014.

METHOD AND SYSTEM FOR PROPAGATING THE STATE OF AN OBJECT AND ITS UNCERTAINTY

J. M. Aristoff, “Method and system for propagating the state of an object and its uncertainty.” U.S. Patent Publication Number US20140074766 A1, Issued on 13 March 2014.

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