ADVANCED ALGORITHMS

ExoAnaltyic Solutions researchers are committed to fundamental research that is driven by our curiosity and focused on delivering solutions to the toughest problems our customers face. Using our proven technology development, testing, maturation, automation, and operational transition process, we have revolutionized missile defense and space situational awareness programs. Our mission-centric layered data model technology development structure explicitly identifies the full spectrum of data available from raw sensor data to actionable information. Further, it identifies the tools and techniques that are appropriate to use at each layer of the data model, the types of data they will be using, and the types of questions they are suitable to answer.

Our advanced algorithms span the full spectrum of missile defense, space situational awareness, and optical sensor processing challenges:

  • Image registration and calibration
  • Dim object detection / Clutter suppression
  • Closely spaced object (CSO) detection
  • Orbit determination and validation
  • Automated light curve generation
  • Signature and feature extraction
  • Target characterization / Object correlation
  • Object change detection
  • Stability and dynamics validation
  • Track updates and catalog maintenance
  • Anomaly and maneuver detection
  • Conjunction / Reachable volume warnings
  • Indications and warnings of space object events

INNOVATIVE RESEARCH

Many of our advanced algorithms are a result of our participation in Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs. These programs are designed to stimulate technology research by small businesses while providing the government with cost-effective technical and scientific solutions to challenging problems. ExoAnalytic has been awarded several SBIR and STTR contracts by the Missile Defense Agency and the Air Force.

2016 SBIR Phase I
Missile Defense Agency

Missile defense faces the challenges of rapidly maturing and evolving complex threats, possessing capabilities which require the use of all available resources to successfully detect, track and identify the lethal objects. Future performance will rely on multiple sensors such as ground and sea based radars and electro-optical and infrared sensors for target recognition. It is crucial to develop a multi-sensor framework capable of processing the wealth of information these sophisticated systems can provide while also accounting for missing, noisy, or corrupted data. ExoAnalytic Solutions has partnered with Oregon State University to develop an advanced multi-sensor, multi-information -driven classifier for robust threat identification. We propose to do this through a unique combination of innovative advances in deep, hierarchical machine learning together with recurrent Deep Learning Neural Network (DLNN) methods for sensor fusion and Dynamic Multi-Entity Bayesian Networks (MEBNs) for whole-scene and contextual reasoning. Approved for Public Release 16-MDA-8620 (1 April 16).

2015 SBIR Phase I
Air Force

As space continues to become more congested and contested, our ability to identify and mitigate man-made and natural threats to space assets becomes increasingly difficult. The detectable population of resident space objects (RSOs) is not comprehensively quantified. Detection, tracking, and classification of objects such as cubesats, nanosatellites, and space debris that threaten military and commercial satellites is particularly challenging for geosynchronous earth orbits (GEO) and near-GEO regimes. To address the challenge of characterizing the population of artificial space objects, ExoAnalytic Solutions proposes to develop DENSE. ExoAnalytic will develop an information-driven method for designing space-based EO/IR sensors and multi-sensor architectures that will provide maximum detectability and state assessment of GEO and near-GEO space objects. Sensor design will focus on parameters of optical sensors affecting minimum detectable target (ex. aperture, quantum efficiency, detection algorithms) and data collection for feature estimation (ex. size, shape, surface material properties). Architecture design will focus on critical system performance figures of merit including maximizing detections within a specified period of time.BENEFIT:The development of DENSE will be significant for SSA because it will: – Allow for a better understanding of the space debris environment in the 1-10 cm size regime – Quantitatively compare the performance of various space-based sensor design alternatives on key figures of merit including (minimum detectable target, FOV, etc.) – Quantitatively compare the performance of various space-based sensor architecture and CONOPs alternatives on key figures of merit including (maximizing target detections, catalog maintenance accuracy, space object classification accuracy) – Compile and identify the priority set of signature feature observables based on sensor spectral band, irradiation conditions, and object altitude, size, geometrical/thermal complexity, and dynamic motion – Develop algorithms SSA architectures that address some specialized sensing and identification issues that include space operator/analyst performance response time (based on single or multiple orbital pass observations) and discriminating solar glint from thruster engine burns.

2015 SBIR Phase II
Air Force

Weather, intelligence, communications, PNT…are all capabilities we have brought to the fight from the space domain and are relied upon in virtually any and every military operation. Mr. Michael Donley, Former Secretary of the Air Force. The modern warfighter requires freedom of action in space, and when necessary, defeats adversary efforts that interfere or attack US or allied space systems. Freedom of action in space is enabled by Space Situational Awareness (SSA). As space continues to become more congested and contested, our ability to identify and mitigate man-made and natural threats to space assets becomes increasingly difficult. Applying the same resources to a larger data set delays the ability to make informed decisions. With current capabilities, performing an in-depth characterization (ex. mission payload assessment) can take weeks to months, especially if the object is non-cooperative. Timely and effective resident space object (RSO) characterization is a challenge, and requires advanced data processing techniques. A critical first need is the ability to detect and identify photometric signature changes due to potential RSO changes (e.g., stability, material), and correlate these observed changes to potential behavior changes. To meet this technology need, ExoAnalytic Solutions proposes to mature Autonomous Characterization Algorithms for Change Detection and Characterization (ACDC). ACDC is significant because it utilizes cutting edge algorithms rooted in Missile Defense, anchored by a global telescope network producing millions of real-time correlated observations each month. The result is a capability to robustly assess state change detection and improve object correlation. BENEFIT: ACDC provides several key contributions to DOD. Most importantly, ACDC will provide the JSpOC with needed Threat Identifications and Warnings to accomplish its mission, as called out in the latest JMS Increment 3 RFI. The ACDC effort includes the development of a characterization and correlation framework for determining the resources necessary to properly characterize space objects. This framework can be used by JSpOC on current and future systems, and can incorporate government or additional industry algorithms. ACDCs technical approach, the algorithms and infrastructure that will be developed, and lessons learned can all be leveraged to further applied research and technology development for threat indication and warning in the ISR domain as well.

2015 SBIR Phase II
Missile Defense Agency

Future missile-defense architectures are comprised of diverse sets of sensor systems (e.g., radars, electo-optical infrared sensors) necessary for countering emerging threats. The capability to dynamically manage sensor resources would enhance the missile defense systems ability to achieve mission objectives. A key component of missile defense sensor management is determining which sensors can provide the best information for tracking and target characterization throughout the engagement timeline. Innovative algorithms are needed to characterize the battle space in terms of adverse environments and to automatically determine the sensor allocation strategy that minimizes target tracking and characterization uncertainty. In response to this technology need, ExoAnalytic Solutions is developing Rapid Environmental Scene Characterization Using Efficient MEasurements (RESCUE ME). Approved for Public Release 15-MDA-8169 (20 March 15).

2014 SBIR Phase I
Air Force

The modern warfighter requires freedom of action in space for friendly forces, and when necessary, the ability to defeat adversary efforts that interfere or attack US or allied space systems and to negate adversary space capabilities. Freedom of action in space is enabled by Space Situational Awareness (SSA). The SSA Decision Cycle information bottleneck forces warfighters to make critical decisions with old, inaccurate, or limited information on a limited number of resident space objects (RSOs). Today there is limited capability (and no real-time capability) to exploit EO/IR signatures for characterization. The inability to provide timely RSO characterization from non-resolved imagery creates gaps in our knowledge and forces reliance on more expensive and frequently less available means. The development of Autonomous Characterization Algorithms for Change Detection and Correlation (ACDC) is significant to the US Air Force and broader SSA community because it will enable automated processes to estimate the physical properties of space objects from passively collected photometric signatures. Improved understanding of RSO features (such as stability estimates, material estimates, shape estimates, and attitude estimates) will improve track custody, improve object correlations, reduce cross-tagging, and improve catalog accuracy. BENEFIT: The primary focus for commercialization of Autonomous Characterization Alogorithms for Change Detection and Correlation (ACDC) is to transition the capability to the Joint Space Operations Center (JSpOC). In particular, Team Exo will focus on ensuring a seamless integration of ACDC into ARCADE, which will enable operators to evaluate the impact of ACDC algorithms on their mission execution at JSpOC. In addition, automated characterization algorithms including stability estimation, attitude determination, and change detection have a variety of commercial and civil applications. Current and potential future uses include: detailed characterization for the intelligence community, automated asteroid detection and characterization, commercial space remote monitoring, and initial deployment identification and support for cubesats.

2014 SBIR Phase II
Missile Defense Agency

The objective of this effort is to develop and test a multi-sensor data fusion algorithm suite that will fuse information from multiple electro-optic (EO) and radio frequency (RF) sensors to estimate tracked objects physical properties and dynamics for the purpose of aiding in predicting signatures and features for system target characterization. Assessments of improvements obtainable by using the algorithm suite for target characterization will be conducted. Approved for Public Release 14-MDA-7979 (16 September14).

2014 STTR Phase II
Missile Defense Agency

In order to counter emerging threats from the Middle East and Southeast Asia, the Ballistic Missile Defense System (BMDS) is acquiring new sensor (e.g. AN/TPY-2 and PTSS type) and weapon technology (SM-3). As these new technologies are fielded, the BMDS’s Command, Control, Battle Management and Communication (C2BMC) component must be able to correlate objects between multiple sensors. Inherent in this multi-sensor data fusion problem are issues related to differences in resolution, phenomenology, and viewing geometry. To address these technical challenges, the ExoAnalytic Solutions team proposes to develop a RF/EO Track Correlation and Characterization suite (RETC2), which will perform target characterization for use in feature aided track correlation. The objective of RETC2 is to develop technology for the BMDS that will enable fusion of sensor data to provide persistent system tracking, which leads to effective discrimination and an engagement that maximizes probability of kill. RETC2’s technical approach will emphasize diversity in sensor resolution, viewing geometry and phenomenology as a means to providing accurate, timely tracking features for correlation and target characterization.

2013 SBIR Phase II
Air Force

Over the last twenty years the United States has become dependent on space technology for communications, precision tracking and many other applications. Globalization of the worlds economy, which has also dramatically increased over the past twenty years, has resulted in this same dependence in industrialized and developing nations around the world. As a result of these trends, the space domain has become both a contested and congested environment. To maintain United States space superiority, the Joint Space Operations Center (JSpOC) is responsible for tasking the Space Surveillance Network (SSN) and maintaining a catalog of over 22,000 man-made objects. This mission requires innovative technology to aggregate information from distributed, heterogeneous data sources as a means of obtaining Space Situational Awareness (SSA). To meet this technology need, ExoAnalytic Solutions, Inc. proposes to develop Semantically Enable Event Reasoning (SEER). SEER is significant because it uses semantic technology to store information on space objects and automatically discover relationships between space objects and space events. The result is a persistent state of awareness for the space domain. SEER leverages this persistent awareness to build applications that automatically quantify the degradation in space capability to rapidly regain custody of missing satellites. BENEFIT: SEER provides several key contributions to DoD. Most importantly, SEER will provide the JSpOC with a robust Level 2 fusion capability necessary for accomplishing it mission. SEER can also play a valuable systems engineering role within Air Force Space Command (AFSPC). The SEER effort includes the development of an analytical framework for assessing performance of the data fusion algorithms. This framework can be used by systems engineers to help define sensor specifications crucial to SSA and define new SSA quality of service metrics for use by JSpOC. Finally, algorithms and techniques are needed in C4ISR to fuse disparate sensor data for entity disambiguation and uncovering of terrorist networks with little to no a priori knowledge due to rapidly changing techniques of the adversary. SEERs technical approach, the inference algorithms that will be developed, and lessons learned can all be leveraged to further applied research and technology development for data fusion in the C4ISR domain, as well.

2013 SBIR Phase II
Missile Defense Agency

MDA plans to use sensors such as PTSS, SM-3, UEWR, and AN/TPY-2 to track and intercept ballistic missiles. In order to be successful, the C2BMC element must: 1) achieve and maintain stereo tracks, 2) perform target characterization, 3) prioritize and assign targets to interceptors, and 4) handover object information to the interceptor in a form that will allow it to identify the object on its focal plane. The objective of this effort is to develop and test a multi-sensor data fusion algorithm suite that will fuse information from multiple EO and RF sensors to estimate every tracked object”s physical properties and dynamics for the purpose of aiding in forward predicting signatures and features for the interceptor as well as providing useful information for system target characterization. Assessments of improvements obtainable by using the algorithm suite within the C2BMC for target characterization, correlation of tracks, and handover of object information to the interceptor will be conducted.

2013 SBIR Phase II
Missile Defense Agency

One of the primary research objectives for multi-sensor data fusion within the Ballistic Missile Defense System (BMDS) is the development of novel techniques to enable robust target discrimination. While great strides have been made in recent years to advance capabilities through the use of features available from Forward Based Radars (i.e. AN/TPY-2) and emerging optical platforms (i.e. PTSS), these algorithms remain coupled to a priori assumptions regarding the lethality characteristics of targets. In a world in which threat characteristics are constantly evolving, it is imperative to develop a target discrimination solution which explicitly separates these internal assumptions the lethal hypothesis from the estimation of physical attributes. In response to this technology need, ExoAnalytic Solutions Inc. proposes ENSPIRE: Exploitation of Networked Sensor Phenomenology Involving Robust Estimation. ENSPIRE’s overall objective is to develop robust long range discrimination technology, capable of performing against all current and future ballistic missiles and in any sensor architecture configuration.

2013 SBIR Phase II
Missile Defense Agency

Missile Defense Agency (MDA) recently adopted the Phased Adaptive Approach (PAA) to enhance the Ballistic Missile Defense System”s (BMDS) ability to counter emerging threats in the Middle East and Southeast Asia. PAA primarily focuses on fielding new sensor technology (e.g. AN/TPY-2 and PTSS) and weapon technology (e.g. SM-3). As a result of these new systems entering the BMDS, Command Control Battle Management and Communication (C2BMC) functionality requires new algorithms for sensor resource scheduling. These algorithms must be capable of real-time adaptation to account for sensor availability and changing threat scenes, as well as ensure sufficient data collection throughout an engagement (i.e. acquisition, track, discrimination, and hit/kill assessment). In response to this technology need, ExoAnalytic Solutions Inc. proposes O-SMART: Ontological Sensor Management and Real-time Tasking. The objective of O-SMART is to develop a sensor management system that leverages recent advancements in semantic technology and Information Theory, as well as over 50 man years of BMDS experience by ExoAnalytic Solutions researchers, to adaptively allocate sensor resources in a multi-raid and/or multi-target environment. O-SMART”s technical approach will emphasize diversity in sensor viewing geometry and phenomenology as a means to providing accurate, timely tracking and discrimination quality of services to BMDS weapon systems.

2012 SBIR Phase I
Air Force

Over the past twenty years, the United States and other nations around the world have become dependent on space technology for communications, precision tracking and many other applications, causing the space domain to become both contested and congested. To maintain Unites States space superiority, the Joint Space Operations Center (JSpOC) is responsible for tasking the Space Surveillance Network (SSN) and maintaining a catalog of more than 22,000 man-made objects. This mission requires innovative technology to aggregate information from distributed, heterogeneous data sources to obtain Space Situational Awareness (SSA). To meet this technology need, ExoAnalytic Solutions, Inc. proposes to develop Semantically Enabled Event Reasoning (SEER) for the space domain. The objectives of SEER are: 1) to develop multi-sensor data fusion algorithms for correlating space events across heterogeneous data sources; 2) to develop a relationship estimation algorithm based on correlated space events; 3) to provide context for the estimated relationships; and 4) to develop an analytical framework for assessing performance of SSA Level 2 fusion algorithms. BENEFIT: SEER provides several key contributions to DoD. Most importantly, SEER will provide the JSpOC with a robust Level 2 fusion capability, necessary for accomplishing its mission. SEER can also play a valuable systems engineering role within Air Force Space Command (AFSPC). The SEER effort includes developing a performance assessment framework for the data fusion algorithms. This framework can be used by systems engineers to help define sensor specifications crucial to SSA and define new SSA quality of service metrics for use by JSpOC. Finally, algorithms and techniques are needed in C4ISR to fuse disparate sensor data for entity disambiguation and for uncovering terrorist networks with little to no a priori knowledge due to the adversary”s rapidly changing techniques. SEER”s technical approach, the inference algorithms that will be developed, and lessons learned, can also be leveraged to further applied research and technology development for data fusion in the C4ISR domain.

2012 STTR Phase I
Missile Defense Agency

In order to counter emerging threats from the Middle East and Southeast Asia, the Ballistic Missile Defense System (BMDS) is acquiring new sensor (e.g. AN/TPY-2 and PTSS) and weapon technology (SM-3). As these new technologies becomes fielded, the BMDS’s Command, Control Battle Management and Communication (C2BMC) component must be able to correlate objects between multiple sensors. Inherent in this multi-sensor data fusion problem are issues related to differences in resolution, phenomenology, and viewing geometry. To addresses these technical challenges, ExoAnalytic proposes to develop a RF/EO Track Correlation and Characterization suite (RETC2) , which will perform target characterization for uses in feature aided track correlation and can adapt the techniques used depending on the spatial separation of objects and resolution of observing sensors. The objective of RETC2 is to develop technology for the BMDS that will enable fusion of sensor data to provide persistent system tracking which leads to effective discrimination and an engagement that maximizes probability of kill. RETC2’s technical approach will emphasize diversity in sensor resolution, viewing geometry and phenomenology as a means to providing accurate, timely tracking features for correlation and target characterization.

2012 SBIR Phase I
Missile Defense Agency

One of the primary research objectives for multi-sensor data fusion within the Ballistic Missile Defense System (BMDS) is the development of novel techniques to enable robust target discrimination. While great strides have been made in recent years to advance capabilities through the use of features available from Forward Based Radars (i.e. AN/TPY-2 and SBX) and emerging optical platforms (i.e. ABIR and PTSS), these algorithms remain coupled to a priori assumptions regarding the lethality characteristics of targets. In a world in which threat characteristics are constantly evolving, it is imperative to develop a target discrimination solution which explicitly separates these internal assumptions the lethal hypothesis from the estimation of physical attributes. In response to this technology need, ExoAnalytic Solutions Inc. proposes ENSPIRE: Exploitation of Networked Sensor Phenomenology Involving Robust Estimation. The objectives of ENSPIRE are: 1) to develop algorithms that adaptively define and solve hierarchical statistical models that link sensor feature data to target attributes through causal physics; 2) to develop an algorithm that combines target attribute estimates with a lethal hypothesis to perform discrimination; and 3) to leverage recent advancements in Information Theory to develop an analytical framework for conducting disciplined trade studies to assess the performance of ENSPIRE.

2012 SBIR Phase I
Missile Defense Agency

Missile Defense Agency (MDA) recently adopted the Phased Adaptive Approach (PAA) to enhance the Ballistic Missile Defense System”s (BMDS) ability to counter emerging threats in the Middle East and Southeast Asia. PAA primarily focuses on fielding new sensor technology (e.g. AN/TPY-2, ABIR, and PTSS) and weapon technology (e.g. SM-3). As a result of these new systems entering the BMDS, Command Control Battle Management and Communication (C2BMC) functionality requires new algorithms for sensor resource scheduling. These algorithms must be capable of real-time adaptation to account for sensor availability and changing threat scenes, as well as ensure sufficient data collection throughout an engagement (i.e. acquisition, track, discrimination, and hit/kill assessment). In response to this technology need, ExoAnalytic Solutions Inc. proposes O-SMART: Ontological Sensor Management and Real-time Tasking. The objective of O-SMART is to develop a sensor management system that leverages recent advancements in semantic technology and Information Theory, as well as over 50 man years of BMDS experience by ExoAnalytic Solution researchers, to adaptively allocate sensor resources in a multi-raid and/or multi-target environment. O-SMART”s technical approach will emphasize diversity in sensor viewing geometry and phenomenology as a means to providing accurate, timely tracking and discrimination quality of services to BMDS weapon systems.

2012 SBIR Phase I
Missile Defense Agency

ExoAnalytic Solutions proposes to develop a star catalog and in-band irradiance simulation by leveraging our in house star background model called STARS (Stellar Track And Radiance Simulation) v1.0 and the Exo6Sim optical focal plane scene generation simulation. STARS v1.0 uses a stellar spectrum fit to the SWIR point source data in the 2MASS database. Stellar spectra are inferred via a maximum likelihood fit to over 3,000 sample spectra in the Hubble ATLAS9 reference spectra database. To meet the requirements for this solicitation, we will develop an upgraded model called STARS v2.0 that will improve fidelity by expanding the number of databases used, take advantage of stellar spectral type databases, and render extended sources as well as point sources. We will also upgrade our spectral inference and in-band integration as required by the solicitation by identifying and resolving data gaps and including effects such as Doppler shift and interstellar medium extinction to provide the highest fidelity in-band signatures for stellar and non-stellar objects from 0.2 V 15 fYm. Validation of the model will be performed using our telescope observatory, camera and advanced algorithms and software tools. Architecture for integration into MDA simulations such as FLITES will also be developed.

2011 SBIR Phase I
Missile Defense Agency

MDA plans to use optical platforms, such as PTSS, ABIR, and SM-3, to track ballistic missiles in support of ascent phase intercepts. For success, there are a number of system level challenges that the C2BMC element must overcome. A few of these are: 1) achieve and maintain stereo tracks, 2) perform lethal object discrimination, 3) prioritize and assign lethal targets to interceptors, and 4) handover lethal object information to the interceptor in a form that will allow it to identify the lethal object on its focal plane. The objective of this proposed effort is to: 1) use SysTRAAK, ExoAnalytic’s BMDS end-to-end simulation, to demonstrate these challenges on MDA”s ability to close the fire control loop in a complex ascent phase scene and ultimately intercept the lethal payloads, 2) develop algorithms to meet these challenges, drawing upon our base of existing TRL 2-6 algorithms developed during MDA/DV funded efforts over the past 10 years, and 3) deliver the algorithms to MDA for insertion into the C2BMC element. This proposal will investigate using radiometric information to enhance the probability of correct handover with demonstrations focused on ascent phase intercept.

2011 SBIR Phase II
Missile Defense Agency

Objects tracked by optical sensors in ascent phase and midcourse are frequently obscured on the focal plane by closely spaced objects, countermeasures and debris (or clutter) that affect the performance of discrimination and tracking algorithms. Problems include missed detections, false alarms, corrupted signatures and masking of pixels that contain lethal objects. The objective of the proposed effort is to develop a focal plane clutter identification and mitigation algorithm suite that can execute on-board the ABIR, PTSS and SM-3 platforms. The suite uses multiple band focal plane data to identify regions of interest that contain clutter via characterization of the surface material properties found on the focal plane. Once identified, regions are processed by generating image maps that are manipulated to reject “hot” clutter thereby enhancing signatures of relatively “cool” targets of interest. The suite then leverages the CCIR3.1 closely spaced object (CSO) algorithm to provide target detections. This phase II effort will focus on maturation, testing and integration of the algorithm suite into the SM-3 Block IIA testbed, laying the groundwork for a successful phase III transition.

2011 SBIR Phase II
Missile Defense Agency

The ExoMHT association algorithm is an innovative Multiple Hypotheses Tracker which operates in real-time for large numbers of boosting, maneuvering, and deploying targets. During Phase I, ExoAnalytic Solutions developed the ExoMHT association algorithm into a Technology Readiness Level (TRL) 3 algorithm, incorporated this algorithm into a system-level simulation called SysTRAAK, and demonstrated performance. The ExoMHT association algorithm successfully ran in real-time on a large MDA raid scenario containing 78 missiles. During Phase II, ExoAnalytic Solutions will mature the ExoMHT association algorithm into a TRL 6 algorithm, which will be ready for insertion into various MDA program elements during Phase III. Improvements to the ExoMHT association algorithm during Phase II will include adding a sensor bias correction capability, structuring the code to take advantage of multiple processors, upgrading the algorithm to utilize feature-aided track correlation inputs, and other upgrades based on extensive testing and MDA element feedback. The ExoMHT association algorithm performance will be characterized against raid scenarios of interest for a variety of IR sensor platforms. Promoting, adapting, and documenting the ExoMHT association algorithm in preparation for Phase III will also be a focus of this proposed effort.

2010 SBIR Phase I
Missile Defense Agency

Objects tracked by optical sensors in ascent phase and midcourse are frequently obscured on the focal plane by countermeasures and debris (or clutter) that affect the performance of discrimination and tracking algorithms. Ascent phase can be especially challenging due to the presence of fuel fragments and constraints due to a short timeline and closely spaced objects (CSO) on the focal plane. Problems include missed detections, false alarms, corrupted signatures and masking of pixels that contain lethal objects. ExoAnalytic Solutions possesses a body of tools that have been used to demonstrate that, when unmitigated, clutter could negatively impact the performance of the BMDS system. The proposed effort will be to develop a focal plane clutter identification and mitigation algorithm suite. The suite uses multiple band focal plane data to identify regions of interest that contain clutter via characterization of the surface material properties found on the focal plane. Once identified, regions are processed by generating image maps that are manipulated to reject “hot” clutter thereby enhancing signatures of relatively “cool” targets of interest. This work will extend efforts previously completed by the authors in the areas of CSO and clutter mitigation in support of ascent phase intercept.

2010 SBIR Phase I
Missile Defense Agency

The objective of this proposal is to develop a Multiple Hypothesis Tracking (MHT) algorithm that will operate in real-time while receiving detection reports in ascent phase from a variety of disparate sensors. ExoAnalytic Solutions has developed mature tools, including the CCIR3 CSO algorithm and the SysTRAAK MHT tracking and discrimination simulation that will form the starting point for this proposal. CCIR3 is a TRL 6 CSO mitigation algorithm that is currently undergoing insertion into the SM-3 Block IIA testbed at Raytheon. The SysTRAAK end-to-end tracking and discrimination simulation utilizes the CCIR3 CSO algorithm to study multiple platform BMDS tracking, handover and discrimination performance. Using a focal plane detection algorithm like CCIR3 is critical for tracking and correlation studies in ascent phase where the CSO condition is a major issue to be resolved. The SysTRAAK simulation operates on detection reports containing metric data from disparate sensors (DSP, STSS, PTSS, airborne IR, interceptors, radar, others). It carries multiple hypotheses to account for potential target deployment, maneuvers, and for the “ghosting” that arises when targets and sensors nearly lie in a plane. This proposal will investigate utilizing radiometric information to enhance the probability of correct handover with demonstrations focused on ascent phase intercept.