Numerica excels at the processing of non-resolved imagery collected by visual and infrared sensors, both day and night.

Numerica’s patented optimization-based approach to multiple hypothesis target tracking, entitled Multiple Frame Assignment (MFA), delivers robust real-time performance in stressful scenarios

Resource Management

Numerica has worked in the area of resource management (i.e., sensor management and battle management) for over a decade.

Positioning, Navigation and Timing

Positioning, Navigation, and Timing (PNT) is a critical capability to the United States military, government services, and commercial sector.

Technical Papers and Patents

Read some of our peer-reviewed papers to see why we’re regarded as thought leaders in Air, Missile & Space Defense

Non-traditional data collection and exploitation for improved geo ssa via a global network of heterogeneous sensors

J. Aristoff, A. Ferris, A. Larson, A. Hariri, N. Singh, J. Horwood, J. Shaddix, K. Wilson, T. Lyons, and N. Dhingra, “Non-traditional data collection and exploitation for improved GEO SSA via a global network of heterogeneous sensors,” in Proc. of the 2018 Advanced Maui Optical and Space Surveillance Technologies Conference, (Wailea, HI), Sept. 2018.

Covariance and uncertainty realism in space surveillance and tracking

A.B. Poore, J. M. Aristoff, and J. T. Horwood, “Covariance and uncertainty realism in space surveillance and tracking.” Astrodynamics Innovation Committee. Tech. Rep. AD1020892, 2016

KRATOS: Kollision Risk Assessment Tool in Orbital Element Spaces

J. T. Horwood, N. Singh, J. M. Aristoff, and A. Bhopale, “KRATOS: Kollision Risk Assessment Tool in Orbital Element Spaces.” Proceedings of the 2016 Advanced Maui Optical and Space Surveillance Technologies Conference, Wailea, HI, September 2016

Athena: a data-driven anomaly detection and space object classification tool for SSA

Singh, J. T. Horwood, J. M. Aristoff, and J. Murray-Krezan, “Athena: a data-driven anomaly detection and space object classification tool for SSA,” in Proceedings of the 26th AAS/AIAA Space Flight Mechanics Meeting, Napa, CA, February 2016

Multiple frame assignment space tracker (mfast): results on UCT processing

M. Aristoff, D. J. C. Beach, P. A. Ferris, J. T. Horwood, A. D. Mont, N. Singh, and A. B. Poore, “Multiple Frame Assignment Space Tracker (MFAST): results on UCT processing,” in Proceedings of the 2015 AIAA/AAS Astrodynamics Specialist Conference, Vail

implicit runge-kutta-based methods for fast, precise, and scalable uncertainty propagation

M. Aristoff, J. T. Horwood, and A. B. Poore, “Implicit Runge-Kutta-based methods for fast, precise, and scalable uncertainty propagation,” Celestial Mechanics and Dynamical Astronomy, Vol. 122, pp. 169-182, 2015

Gauss von Mises distribution for improved uncertainty realism in space situational awareness

J. T. Horwood and A. B. Poore, “Gauss von Mises distribution for improved uncertainty realism in space situational awareness,” SIAM Journal of Uncertainty Quantification, Vol. 2, pp. 276-304, 2014

nonlinear uncertainty propagation in orbital elements and transformation to cartesian space without loss of realism

J. M. Aristoff, J. T. Horwood, N. Singh, and A. B. Poore, “Nonlinear uncertainty propagation in orbital elements and transformation to Cartesian space without loss of realism,” in Proceedings of the 2014 AAS/AIAA Astrodynamics Specialist Conference, San Diego CA, August 2014

beyond covariance realism: a new metric for uncertainty realism

T. Horwood, J. M. Aristoff, N. Singh, A. B. Poore, and M. D. Hejduk, “Beyond covariance realism: a new metric for uncertainty realism,” in Proceedings of the SPIE, Signal and Data Processing of Small Targets, Vol. 9092, Baltimore, MD, May 2014

a comparative study of new non-linear uncertainty propagation methods for space surveillance

T. Horwood, J. M. Aristoff, N. Singh, and A. B. Poore, “A comparative study of new non-linear uncertainty propagation methods for space surveillance,” in Proceedings of the SPIE, Signal and Data Processing of Small Targets, Vol. 9092, Baltimore, MD, May 2014

Orbit and uncertainty: a comparison of Gauss-legendre-, dormand-prince-, and chebyshev-picard-based approaches

M. Aristoff, J. T. Horwood, and A. B. Poore, “Orbit and uncertainty propagation: a comparison of Gauss-Legendre-, Dormand-Prince-, and Chebyshev-Picard-based approaches,” Celestial Mechanics and Dynamical Astronomy, Vol. 117, pp. 13-28, 2013

space object maneuver detection via a joint optimal control and multiple hypothesis tracking approach

N. Singh, J. T. Horwood, and A. B. Poore, “Space object maneuver detection via a joint optimal control and multiple hypothesis tracking approach,” in Proceedings of the 22nd AAS/AIAA Space Flight Mechanics Meeting, Charleston, SC, January 2012

Gaussian sum filters for space surveillance: theory and simulations

J.T. Horwood, N. D. Aragon, and A. B. Poore, “Gaussian sum filters for space surveillance: theory and simulations,” Journal of Guidance, Control, and Dynamics, Vol. 34, pp. 1839-1851, 2011

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,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, Vol. 7698, April 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,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, Vol. 7698, April 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

J. Slocumb, D. L. Macumber, “Surveillance radar range-bearing centroid processing, Part II: merged measurements,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, Vol. 6236, May 2006.

Complexity Reduction in MHT/MFA Tracking: Part II, Hierarchical Implementation and Simulation Results

Complexity Reduction in MHT/MFA Tracking: Part II, Hierarchical Implementation and Simulation Results”-MFA_tracking_2006

Short-term ambiguity assessment to augment tracking data association information

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,” 8th International Conference on Information Fusion, Philadelphia PA, July 2005

A multiple model SNR/RCS likelihood ratio score for radar-based feature-aided tracking

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

Frame Building Algorithm for Electronically Scanned Array Radar

J. Slocumb, M. E. Klusman III, “Frame-building algorithm for electronically scanned array radar,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, Vol. 5913, September 2005

Multiple hypothesis clustering and multiple frame assignment tracking

M. Gadaleta, A. B. Poore, S. E. Roberts, and B. J. Slocumb, “Multiple hypothesis clustering and multiple frame assignment tracking,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, Vol. 5428, August 2004

pixel-cluster decomposition tracking for multiple IR-sensor surveillance

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

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,”Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, 2003

Maximum likelihood narrowband radar data segmentation and centroid processing

B. J. Slocumb, W. D. Blair, “Maximum likelihood narrowband radar data segmentation and centroid processing,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, Vol. 5204, 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,” Proceedings of the 2002 IEEE Aerospace Conference, Vol. 4, pp. 4-1543 – 4-1550, 2002

Multiple frame cluster tracking

S. Gadaleta, M. Klusman, A. B. Poore, and B. J. Slocumb, “Multiple frame cluster tracking,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small targets, Vol. 4728, 2002

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,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, Vol. 4728, August 2002

Surveillance radar range-bearing centroid processing

B. J. Slocumb, “Surveillance radar range-bearing centroid processing,” Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets, Vol. 4473, 2001

On covariance structure in noisy, big data

“On covariance structure in noisy, big data”, Proc. SPIE 8857, Signal and Data Processing of Small Targets 2013, 88570E (September 30, 2013)

Space-time Signal Processing for Distributed Pattern Detection in Sensor Networks

“Space-time Signal Processing for Distributed Pattern Detection in Sensor Networks,” R. Paffenroth, P. du Toit, R. Nong, L. Scharf, A. Jayasumana and V. Bandara, IEEE Journal of Selected Topics in Signal Processing, issue on Anomalous Pattern Discovery

Robust Probabilistic Prediction for Sense and Avoid

J. Adaska, K. Obermeyer, E. Schmidt, “Robust Probabilistic Prediction for Sense and Avoid.” Proc. of American Control Conference, June 2014

Computing Risk for Unmanned Aircraft Self Separation with Maneuvering Intruders

J. Adaska, “Computing Risk for Unmanned Aircraft Self Separation with Maneuvering Intruders,” Proceedings of 31st Digital Avionics Systems Conference, October 2012

Patents

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

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

method and system for determining a track of an object through multi-dimensional space

J. T. Horwood, “Method and system for determining a track of an object through a multi-dimensional space.” U.S. Patent Publication Number US8909586 B2, Issued on 9 December 2014

Core Technologies

Image Processing

Tracking and Data Fusion