About Toyon Research Corporation
Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Advanced antennas for air vehicle flight test evaluation.. The abstract given for this project is as follows: The utility of precision strike weapon flight testing is critically dependent on the use of fleet-representative test articles. The Navy has a need for a suite of flight test antennas that allow communication with the weapon under test without impacting the weapon's aerodynamic or observability characteristics. Toyon proposes to design a suite of antennas for operation of flight termination, Link 16, S-band telemetry, and C-band transponder/beacon systems on strike weapons. The proposed antenna suite will mount conformally to the airframe, and will be designed for use on highly survivable platforms. Toyon will build and test an electrically representative prototype antenna during the Phase I effort, and will construct flight-ready antennas during Phase II.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Geo And Ortho Rectified Video With Fused 3d Mapping, Light Detection And Ranging (LIDAR), And Live Video Overlays. The abstract given for this project is as follows: While full motion video (FMV) data contains a wealth of information, its potential for providing actionable intelligence cannot be realized unless the data is provided within its geographic context and is correlated with available intelligence from human assets. To provide the necessary contextual, registration to/fusion with GIS data is a natural choice. This requires both geo- and ortho-rectification of the video frames based on measurements of the sensor position and orientation, knowledge of the natural and man- made terrain from 3D map and LIDAR data, and video data-driven processing. Toyon Research Corporation proposes to develop an automated sensor calibration and pixel geo-registration system using a suite of innovative algorithms which are applicable for various video sensors. The algorithms do not require a priori estimates of the intrinsic or extrinsic sensor parameters or of the terrain. Nevertheless, any available information (for example, initial calibration estimates, GPS and/or inertial measurements, DTED, LIDAR range maps, or geo-registered orthoimages) can be used by the algorithms with the benefit of improved estimation accuracy and/or improved computational efficiency. The processing is performed using an innovative, computationally-efficient particle filtering algorithm that Toyon has developed for this purpose. When completed, the software will provide, among other benefits, FMV windows with optional intelligence overlays displayed in a viewpoint congruent manner. BENEFITS: The successful completion of this research and development will result in a net centric, open architecture, operating system independent software solution providing near real-time geo- and ortho-rectification of live full motion video, with fusion and viewpoint-congruent display of LIDAR and 3D mapping data with intelligence overlays. This will allow surveillance and tactical asset operators and commanders, as well as geographically distributed analysts, to maximize the efficiency and effectiveness of sensor data exploitation. For example, this technology would be useful for surveillance over challenging terrain along portions of the US Southern and Northern borders, as well as in law enforcement, disaster monitoring and response management, transportation studies, surveying, and environmental monitoring. The technology could even be used to provide improved realism in personnel training and computer gaming.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Control Algorithms for Network Centric Fusion. The abstract given for this project is as follows: The coordination and management of sensor data collection has a strong influence on the accuracy and completeness of the fused situational awareness picture. To provide the best possible picture, Toyon Research Corporation proposes to develop algorithms which generate controls for a collection of UAVs in order to maximize the probability of identifying and maintaining track on suspected enemy vehicles or dismounts. Algorithm inputs will include environmental data (terrain, roads, buildings), sensor, platform, and target motion models, and the current network centric fused estimate of the world (e.g., target kinematic state, uncertainty, and Bayesian classification estimate). The algorithms developed will generate UAV routes which are synchronized and optimized with high demand platforms. In Phase I we will simulate the performance of our approach in a realistic Ramadi-Falluja scenario in which enemy vehicles move between rural and urban safe-houses. Our sensor systems will include one standoff platform with radar and several UAVs with video sensors. Information processing will include multi-sensor fusion (MTI and video) and target signature extraction and fingerprinting. We will use track life as our primary performance metric. Phase II will advance the algorithms and demonstrate the overall approach in closed-loop exercise.BENEFIT:Automatic route and task generation for sensor assets has immediate application to network centric warfare. In addition, the algorithm technology can seamlessly transition into our Geospatial Analysis and Planning Support (GAPS) Toolbox application, which is sponsored by JFCOM Joint Urban Operation Office, and to the Decision Aid currently being developed for the U.S. Army under a Phase II SBIR contract. In addition to military systems, the technology developed during this project will serve as a foundation for planning tools for manned and unmanned systems, providing, for example, emergency response plans for natural disasters or biological, chemical, or nuclear attacks.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Indoor Cooperative MAV Navigation using Signals of Opportunity. The abstract given for this project is as follows: Toyon Research Corporation proposes to determine the feasibility of developing a cooperative indoor navigation framework using signals of opportunity (SoOP). SoOP- aided navigation (SAN) will rely on signals such as those being emitted by WiFi and WiMAX access points and routers. A SoOP sensor design with direction-finding (DF) capability will be developed and its angle of arrival accuracy evaluated. The cooperative navigation system will be compatible with Toyons plug-and-play Software-Defined Navigation(TM) architecture that enables on-the-fly changes to the sensor mixture. The SoOP/DF sensor will be incrementally augmented with alternative sensors such an inertial measurement unit (IMU) and a camera. The performance of each sensor configuration will be evaluated. Communication bandwidth and network topology requirements will be determined. A roadmap for developing the system hardware and software will be identified in preparation for a Phase II demonstration.BENEFIT:The cooperative SoOP- aided navigation (SAN) system will permit accurate navigation under GPS-denied conditions and is applicable to both indoor and outdoor missions. All civilian and military navigation platforms with severe size, weight and power (SWAP) constraints are potential hosts for the proposed cooperative navigation system. These include ground- based and aerial unmanned vehicles, robots, and farming systems.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Georegistration of Imagery with Target Tracking. The abstract given for this project is as follows: Precise detection, tracking and geo-location of multiple moving and stationary targets from airborne sensors in real time poses a great challenge due to the separate registration tasks involved, with the most difficult being geo-registration which requires matching images taken under different conditions. Registration of one image to the next in a video sequence allows detection and tracking of moving targets by aligning common background features in the images, but to obtain the geo-location of these targets the image must also be registered to a geodetically calibrated reference image and overcome the potentially drastic differences in viewing angle, elevation and season to align common world feature points. Toyon proposes to design algorithms to unify frame- and geo- registration by combining the feature point analysis necessary for image registration. Toyons approach to computationally efficient geo-registration is based on a detailed understanding of automated video analysis, and will minimize complexity by only updating a frame to the geo-reference image when the scene content has significantly changed, mapping the known pixel geo-coordinates between intermediate frames. When fully developed in commercially available hardware, this technology is expected to provide significant improvements in exploitation of aerial video surveillance data, in real time. BENEFIT:Successful completion of the proposed research and development effort will result in a real-time video-based target detection and tracking system with track outputs in world coordinates and geo-referenced output frames. The main benefits are expected in military applications where coordination among multiple airborne and ground assets is necessary and real-time performance is critical. However, smaller scale operations would be able to use these capabilities along borders, near ports, or along the coastline to monitor for illegal or terrorist activities. The proposed techniques can be extended to land vehicle-born implementations for enhanced situational awareness along highways or country roads. Potential commercial applications include many police or homeland security applications.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Persistent Electro-Optical/Infra-Red (EO/IR) Wide-Area Sensor Exploitation. The abstract given for this project is as follows: Toyon proposes to develop high-performance algorithms and real-time software for exploitation of persistent wide-area high-resolution video-rate imaging information in accordance with AFRL's pixelpedia concept. The focus in Phase I is on demonstrating feasibility of key algorithm components of the architecture, including georegistered dense 3D reconstruction based on multiple view geometry, construction of statistical model components of the pixelpedia in the georegistered 3D framework, and extension of advanced real-time parallax mitigation algorithms to leverage the 3D and statistical data. While development of some algorithm components of the proposed architecture is reserved for a potential Phase II effort, other components can be integrated as they become available from other sources, via collaboration with AFRL researchers and other contractors. As part of the Phase I feasibility demonstration, Toyon proposes to demonstrate automated detection and tracking using a data source of interest to the government. This demonstration will incorporate the new algorithm developments on this project, and leverage existing detection and feature-aided multiple target tracking algorithms and real-time software developed by Toyon for AFRL and other customers. The final report will include algorithm details, evaluation results, and recommendations. BENEFIT: The successful completion of this research and development will result in significant improvements in real-time exploitation of persistent wide-area high-resolution video-rate EO/IR imaging sensors, including automated target detection, tracking, and identification in dense and cluttered urban environments. Secondary technical benefits will include the ability to automatically calibrate imaging sensors using flight data, rapidly create high-fidelity georegistered 3D models of large scenes, perform on-line learning of georegistered statistical background models, and mitigate the effects of parallax in change detection. This technology would have direct applications in deployed and current developmental wide-area persistent surveillance EO/IR sensor systems, as well as in a broad range of Air Force and other DoD surveillance systems, including air-, ground-, sea-, and space-based platforms. One possible opportunity for transition of the developed technology is into the Distributed Common Ground System (DCGS) being developed by Raytheon, and Toyon has discussed this proposal with Raytheon and obtained a Letter of Support. In surveillance applications, geo-registered 3D data provides context for the sensor operator, as well as exploitation system operators. Highly precise 3D geo-registration is required for multi-look change detection to locate emplacement of possible structures of interest or of threats such as IEDs, and on shorter time scales to perform moving-target detection. The technology could also be used to provide improved realism in personnel training, and even in computer gaming.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Automatic Detection and Tracking of Suspicious Dismounts. The abstract given for this project is as follows: The capability to automatically monitor areas of strategic interest at increased ranges will undoubtedly yield a key advantage on the battlefield by reducing manpower and improving knowledge of enemy target locations. The ability to effectively exploit data from multiple sensor types to find, track, and recognize targets of interest such as dismounts is key to realizing the promise AFSOC advanced sensors. Yet due to a number of well-known challenges, including the large number of target classes and aspects, long and varying viewing range, obscured targets, cluttered backgrounds, various geographic and weather conditions, sensor noise, and variations caused by translation, rotation, and scaling of the targets, effective algorithms for discriminating enemy and neutral targets are still far and few between. An integrated solution which addresses the aforementioned problems in a rigorous, methodical way is necessary to achieve the goals of AFSOC advanced sensors. Our signal processing solution works with many sensors, in many environments, and has matured to the point of natural extension to dismount classification and intent recognition. We propose to augment our tracking solution with advanced machine learning and signal processing algorithms for both appearance-based and motion-based dismount recognition. Furthermore, we propose to recognize enemy combatants through the use of algorithms that can find line-shaped objects consistent with the shape and length of weapons.BENEFIT: Toyon's approach has successfully tracked multiple, closely spaced targets using multiple sensor types (including EO, I2, MWIR, and LWIR), mounted on multiple platforms (hand-held, building pan-tilt-zoom, and UAV). Successful completion of this work will result in a prototype that can discriminate dismounts, identify weapon-like shapes, and run in real time. Such a system will improve battlefield awareness by emitting prioritized cues only on targets of interest.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Embedded Miniature Motion Imagery Transmitter. The abstract given for this project is as follows: High quality video sensors are an invaluable tool for the defense community, enabling unprecedented capabilities for command and control applications. These video systems traditionally use advanced image compression algorithms and Gigabit Ethernet for low latency transmission of large volumes of data. However, these are processing intensive tasks, resulting in large, rack mount solutions. There currently is no compact, low power transmitter capable of delivering high quality, low latency imagery. To address this need, Toyon proposes to develop a highly integrated solution comprised of a third party, ASIC for H.264 motion video compression and transmission, and an FPGA to support multiple camera interfaces. The design will be modular allowing the Embedded Miniature Motion Imagery Transmitter (EMMIT) to support a variety of camera interface modules for the greatest flexibility in the smallest possible package. This combination of compact form- factor, low power consumption, high processing capability, plus flexible interfacing will provide maximum utility for the Army.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Feature-Aided Tracking (FAT). The abstract given for this project is as follows: Cooperative engagement and cooperative sensing tasks require the development of accurate and persistent tracks. Though much work to date has focused on tracking using kinematic information only, a wide variety of feature information on the targets may be available to the tracker. Combining this feature information with kinematic information can improve track accuracy and persistence, especially in challenging environments. Toyon Research Corporation proposes a dual-layer solution for feature-aided tracking to deal with both short-term individual measurement associations and longer-term track-to-target associations. A Multiple Hypothesis Tracker (MHT) will be used in conjunction with a Bayesian network to model feature information and possible inferences garnered from this information in a way that promotes improved measurement-to-track association. Toyon's Tracked Object Manager (TOM) will handle feature database management and use its track stitching algorithms to maintain long-term continuous track, even in situations where features do not singly provide much discrimination between targets. These layers may be implemented in a distributed and decentralized environment. Toyon will also design a test scenario in order to test these algorithms.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: GPS-based 3-D Attitude Determining SAASM Receiver System for Gun-Launched Projectiles. The abstract given for this project is as follows: Toyon Research Corporation and Rockwell Collins propose to develop an anti-jam (AJ) GPS receiver for gun-launched projectiles that incorporates a Selective Availability/Anti- Spoofing Module (SAASM) and provides direct GPS-based 3-D attitude measurements for spin-stabilized and non-spin-stabilized platforms. The roll angle accuracy of the system, while tracking seven satellites and spinning at rates of as much as 300 Hz, is predicted to be better than 3.0 degrees (one-sigma) and the pitch/yaw accuracy is predicted to be better than 2.2 degrees (one-sigma), respectively. The GPS-based attitude (GPS/A) sensor capability is due to Toyon's patent-pending MIDAAS(TM) receiver architecture while Rockwell Collins provides proven gun-hardened SAASM GPS receiver technology and manufacturing capabilities.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Sensor Guided Flight for Unmanned Air Vehicles. The abstract given for this project is as follows: Sensor guided flight is an essential capability for utilizing UAVs more effectively in reconnaissance, surveillance and target acquisition (RSTA) missions. Sensor guided flight is envisioned as the ability for a UAV's sensing system, primarily an imaging system, to automatically request a platform position and attitude that maximizes its performance. It is the ability to monitor viewing conditions for a given RSTA task, assess whether the sensor system parameters and platform position and attitude most optimal for those viewing conditions, and, if not, compute and recommend preferred parameters and platform state for best quality imagery for those viewing conditions. This effort will develop the software and architecture that can deliver robust, reliable RSTA from UAVs. We will identify sensor system parameters that can be adjusted automatically during flight, develop techniques to initialize these parameters to an optimum default configuration, automatically monitor platform state to check if viewing obstacles interfere with the line of sight (LOS) to ground, automatically alter sensor system configuration parameters to regain LOS, and enable system transition from operator-managed flight planning to fully autonomous flight.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Persistent Multi-Intelligence Perimeter Sensing. The abstract given for this project is as follows: Imagery is a powerful tool for enhancing situational awareness. If operating personnel can see potential enemies well in advance of them being an active threat, there is time to mount a coordinated response. Imagery is particularly useful as it is an excellent sensor for classifying not only types of targets, but even their intent. While imagery is very useful for perimeter security, particularly infrared, it carries with it costs in terms of not only equipment but also operator hours for managing the resulting data. This solicitation, and our proposed solution, attempts to overcome these challenges by pairing a low-cost radio frequency (RF) direction finding (DF) system based on time difference of arrival (TDOA) with automated image processing. The DF system will provide an initial cue for the secondary imaging sensor with automated image processing. Such a concept reduces the number of cameras required for a particular installation as well as the operator load and data communications bandwidth of the cameras themselves. Toyon's proposed solution leverages many years of experience in wireless communications, namely multiple-input multiple-output (MIMO) and software defined radio (SDR) systems. Our solution also features high confidence detection and track confirmation video analytics.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Universal Air-to-Ground Broadband Networking Communications Waveform. The abstract given for this project is as follows: Modern military in-theater tactical and emergency communications would benefit greatly from an ability to communicate among all service platforms, but no common waveform standard currently exists to support this. Ideally, such as waveform would fully leverage the higher bandwidth connectivity capabilities inherent in aircraft-to-ground communications, while preserving the capabilities of current terrestrial waveform standards. These operational settings are very challenging for wireless communications because the waveform must simultaneously be robust to multipath and the associated signal fading and inter-symbol interference, and to Doppler shifts typically encountered with air platforms. In this effort Toyon proposes to develop a waveform standard capable of adequately meeting these divergent requirements, as well as developing the associated software and hardware to demonstrate these capabilities. For this purpose we pursue a technical path focusing on orthogonal frequency-division multiplexing (OFDM), which combined with the spatial diversity benefits inherent in multiple-input and multiple-output (MIMO). At the successful completion of this Phase I effort, Toyon will provide real-world demonstrations of the technology and work with the Navy to select a final system to which to target development in a potential Phase II.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Dynamic Modeling of Safe Routes. The abstract given for this project is as follows: The timely determination of the safest routes and schedules for supply convoys is a critical need for post-conflict operations; however, the computational challenge increases exponentially with the number of destinations and the number of supply convoys. We will combine a form of A* algorithm with a combinatorial optimization algorithm to solve for the best convoy schedules. We will utilize a discrete directed graph with dynamic edge costs that represent a degree of 'safe-ness' by incorporating factors which include neighborhood hostility, traffic, and time of day. We propose to develop and compare two combinatorial optimization methods, Simulated Annealing and Genetic Algorithm, to provide timely near-optimal, multiple-convoy to multiple-destination delivery schedules. This work will build upon one of our existing operationally deployed GIS applications featuring an optimization module and routing algorithms. Deliverables will include two performance demonstrations: (a) planning for supply convoy scheduling and, (b) rapid re-planning for the convoy commander. We will also deliver a standalone software application which can be used in live exercises to evaluate the efficacy of the developed technology. Phase II will advance the optimization method and develop the capability as a web service application.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Modeling Human Decision Making and Agent-Based Modeling of C3 Architectures in Warfare Assessment Models. The abstract given for this project is as follows: Toyon Research Corporation proposes to develop the capability within a constructive simulation to model military command and control decisions given information from many sources. In particular, Toyon will address the problem of intelligently redeploying forces given changing conditions reflected in the information provided by military sensors, including complex reactions such as learning from past experience. Toyon will use a layered approach; one layer will be a threat propagation layer, where single elements are modeled by a dynamic Bayesian network and relations between elements are modeled by a cellular-automaton based approach. The second layer will scalably simulate human command and control decisions by modeling each asset as an agent bound by simple local rules. In Phase I, we will develop these algorithms to specifically address the problem of re-deployment of ISR assets. We will show the utility of our work in a proof-of-concept scenario where the complex behavior of the cellular automaton and agent-based algorithms will allow a richer decision-making process than a simplistic rule-based decision tree. In Phase II, we shall design and implement a prototype model integrated within a mission-level simulation to model sophisticated C3 behaviors in a campaign-level scenario of utility to the Navy.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Low-Cost, Multi-Channel Arbitrary Waveform Generator. The abstract given for this project is as follows: The US Army has a need for a vehicle mounted arbitrary waveform generator to be used for research, development, and testing of various Electronic Surveillance (ES) and Electronic Warfare (EW) systems. The generator must be low-cost, multi-channel, high power, fast tuning, and capable of operation over a wide bandwidth. It must also be designed to operate from vehicle power or a battery pack, and it must be ruggedized for harsh environments, particularly for the shock and vibration associated with operation from a HMMWV. Toyon proposes to meet these requirements with a highly modular design consisting of up to 10 channel-modules and a backplane providing power and Ethernet connectivity. Each channel-module will support a fully independent, high power channel output over the entire operating band. Individual modules will have their own Flash Memory, field programmable gate array (FPGA), waveform synthesizer, up-conversion chain and set of power amplifiers (PAs). They will also be interchangeable, field replaceable, and individually configurable. Toyon is particularly well suited for the development and design of such a waveform generator due to our extensive signal processing, RF design, and prototyping experience.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Optimal Intervisibility Site Selection. The abstract given for this project is as follows: Optimal placement of multiple sensors is an important part of the contemporary battlefield, however the computational challenge increases exponentially with the number of sensors considered in the problem. Global search techniques such as Simulated Annealing and Genetic Algorithms have been employed with success against such problems. Toyon proposes to develop and compare two optimization methods, Simulated Annealing and Genetic Algorithm to provide a timely near-optimal multiple sensor placement solution. By leveraging the Geospatial Analysis and Planning Support (GAPS) Toolbox, Toyon begins from an operationally deployed GIS application with an optimization module already developed. This proposal presents case study results for the existing Simulated Annealing approach and three techniques that show promise in minimizing the time to achieve a solution. Our Genetic Algorithm approach utilizes efficient storage and processing techniques that show promise with initial testing. Phase I deliverables will include a demonstration of the visibility optimizers against 1200 x 1200 cell urban and rural terrains, comparison results, and a standalone executable. Phase II will advance the optimization method and develop the capability as a web service application capable of interfacing with the Commercial Joint Mapping Toolkit environment.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: System for Robust Navigation of Micro Air Vehicles. The abstract given for this project is as follows: It is clear that autonomous navigation, guidance, and control of micro air vehicles (MAV) in cluttered environments while detecting and avoiding objects is highly challenging. MAVs and small unmanned aerial vehicles place severe size, weight, and power constraints on avionics and sensor payloads. Although current systems have collocated navigation, guidance and control electronics, they are not fully integrated for optimal navigation and control. Toyon proposes to develop a Software-Defined Navigation(TM) (SDN(TM)) system with Integrated Guidance and Control (IGC) specifically for small platforms. The integrated design will eliminate redundancy while improving robustness and performance. The plug-and-play SDN/IGC system will accept inputs from a variety of sensors including gyros, accelerometers, magnetometers, and several novel sensors currently under development at Toyon. These include a very small GPS-based attitude sensor, an ultrasonic ranging device, and an optical-flow sensor with reduced computational requirements. The system will provide robust guidance and control under disturbances such as wind gusts while enhancing the operational envelope under GPS-denied or jammed conditions. While ambitious, the proposed SDN/IGC system is realizable and will significantly improve the performance of small, autonomous platforms. Toyon will design the system during Phase I and build, test and demonstrate a prototype during the Phase II effort.Toyon Research Corp. is a company that received a Department of Defense SBIR/STTR grant for a project entitled: Highly Directive 100 to 300 MHz Super Gain Antenna. The abstract given for this project is as follows: The Air Force currently has a strong need to conduct antenna gain tests over the 100-300 MHz frequency band. It is desirable to conduct these tests indoors utilizing an anechoic chamber, to control the environment and reduce EMI from external sources. Unfortunately, the walls of anechoic chambers at these low frequencies have relatively high reflectivity that can cause unacceptable levels of multi-path. This issue is compounded by the fact that commonly available source antennas at these low frequencies (i.e. log-periodic antennas) have wide beamwidths and high sidelobes that heavily illuminate the chamber walls.