1127B Benfield Blvd
Millersville, MD 21108
Signal Systems Corporation is a small business with a strong capability in signal processing and active noise control. We specialize in distributed acoustic sensors for surveillance and reconnaissance.
We specialize in distributed acoustic sensors for surveillance and reconnaissance. At SSC we combine a deep understanding of advanced technology with exceptional skill in bringing our customer's perspective to new projects. We bring these strengths together with our proven practices of hardware and software development to provide solutions that are changing the state of the art.
Enhanced contact screening for MAC missions will be accomplished by adapting deep learning techniques developed by researchers for image processing to perform pattern recognition on the Bayesian target state estimator for MAC. The state estimate, a probability mass function encapsulating the existence of a target and its potential position and velocity, contains 225,000 data points for every ping. This information will serve as the input for a deep convolutional neural network which will label regions of the field as target, bottom clutter, ephemeral clutter, or empty. This labeled map will be used to reduce clutter by improving snippet scores, and increasing the speed with which persistent clutter is identified by MAC. Other improvements include an enhanced operator display and better ping control algorithms.
SSC is developing technologies which will accurately estimate areas of uncertainty for selected target echoes. The area of uncertainty will be significantly reduced by incorporating advanced buoy localization methods and by retrospective multiple hypothesis tracking on selected receivers with lower detection thresholds. The buoy localization techniques will reduce buoy location errors, sound speed uncertainty, and compass bias errors. The multiple hypothesis tracker will reduce target azimuth errors by repeated measurements of the target's angle of arrival. We seek to reduce the circular error probability radius by a factor of two (2), resulting in a four times reduction in AOU. Accurate and reliable AOUs will be computed from the position probability density function of the target, using in-situ estimates of the relevant target localization parameters. The buoy localization algorithms and retrospective tracker will be used to assess the effects different buoy patterns have on the resulting target AOU. Reduced Target Area of Uncertainty will improve target tracking and prosecution. Increasing the number of target detections using a wide area search system will improve system classification performance.
SSC is demonstrating the technology of using DIFAR receivers to receive data from an MH-60R ALFS system and that data then being linked back to the CV-TSC for processing and operator review. In order to do this SSC will show via simulation that using the DIFAR buoys provides measurable improvement over baseline ALFS detection performance. SSC is modifying existing MAC multi-static signal processing for the mission to run in real time and develop CONOPS and planning tools to enable this technology to be effectively used in the fleet. Later, SSC will field a working SOAR system into the CV-TSC by integrating the real-time signal processing software into the CV-TSC as well as providing a planning tool that would support successful deployment and operation of the system.
SSC & GDIT will develop a self-updating tactical decision aid for the Air ASW community that will generate sensor performance predictions and recommend optimized operational parameters, built on a new service-oriented architecture (SOA) that can autonomously reach out across the internet to retrieve the most current environmental predictions and in-situ measurements. SSC will leverage our Multi-Static Sonar Performance Model (MSPM), which is currently being used for P-8A Increment 3 system studies, to model the current acoustic environment and recommend optimum configurations for sonobuoy spacing, operating depth, ping plan strategies, and pulse settings for a multiplicity of op-areas and threats.
This project will focus on software and firmware development that further improves the search and detection phase of Air ASW submarine prosecution using pulsed spread spectrum waveforms. These enhancements will allow for at least four simultaneous sources to broadcast simultaneously. Estimated probability of detection will increase in difficult submarine detection conditions and search times will be reduced in dense field spacing where single-echo detection rates are higher. The goal for this effort is to develop the real-time software for in-flight testing using an at-sea target. At the end of this effort, we will have demonstrated our technology in the aircraft during a real mission, and demonstrated its usefulness on at-sea data. To achieve this goal, we will complete the real-time software development of the software. We will procure 32 modified SSQ-125 sonobuoys and update their interfaces. We will conduct test flights and update simulations. These tasks will be utilized to prepare the software for integration into the MAC signal processing software and identify risks to integration under the Increment 3 program.
This effort adds an automated multi-static contact follower that significantly enhances active/passive fusion and improves multiple submarine search capability. This approach will reduce the cost of executing the Increment 2 LRT integration by providing a head start on the LRT integration effort prior to the start of the Increment 2 Rapid COTS Insertion (RCI) effort. This jump start will provide the schedule relief needed to fully develop the operator interfaces that will make the LRT an even more powerful tool. During effort, we will focus on the rapid integration of the LRT software and the development of the operator-machine interface (OMI) in preparation for the Fleet evaluation. The option effort will focus on improving LRT performance relative to the baseline software based on the findings of the base effort and the operator evaluation. Option efforts will also include such improvements to the LRT such as additional operator interaction and active/passive fusion.
SSC is developing a Maritime Acoustic Relative VELocity (MARVEL) sensor to measure the Doppler shift of an ultrasonic signal induced by the relative motion between an unmanned aerial vehicle (UAV) and the deck. SSC will demonstrate the feasibility of using an innovative, small, lightweight, low-cost array of directional ultrasound sensors to produce real-time tracking velocity measurements (TVM) at low taxiing/creeping speeds. Ultrasound sensors operating in continuous active sonar (CAS) mode are a natural fit for measuring relative velocity. The sensor is always on, allowing for the uninterrupted tracking of the Doppler shift over time. SSC's approach uses Acoustic Doppler to sense motion more directly than imaging or range finding approaches. This sensing modality does not depend on lighting conditions and a significant range of the ultrasonic wavelengths are relatively immune to backscatter from mist and fog, making it a natural choice for day and night maritime conditions.
SSC is immediately focused on integrating MARVEL sensor technology on the NAVY UAV platforms developed under the MQ-25 Stingray project. MARVEL sensor technology is also highly relevant to advanced driver assistance systems and the sensor suites of autonomous vehicles. SSC plans to pursue both military and commercial applications in these areas.
Demonstrate software that increases the spatial coverage of the AN/SSQ-125 sonar system, reducing the search time and eliminating the need to deploy additional localization sonobuoys during operations.
This effort develops and evaluates features exploiting the swim bladder resonance observed in broadband echoes from fish for automatic screening, reducing mid-frequency active sonar clutter. Real world data from shallow water is used to develop and evaluate features for discriminating between the broad peaks characteristic of an aggregate echo from a school of fish and the comparatively flat echo from target and target-like scatterers. Exploitation of this feature is important because biologics can produce high level echoes, move, and are not amenable to other sensing modalities. Because the frequency and sharpness of the resonances depend strongly on the relative density of fish species and their depth, physically motivated features of the spectral shape and auto-regressive coefficients from speech recognition are leading candidates for investigation. Another product of the work is an understanding of the system bandwidth required to achieve reliable automatic screening of fish echoes without significantly reducing target detections. Beyond the benefits of reliable screening, the developed features themselves offer the potential to improve associations in automatic tracking. This project will demonstrate the feasibility of exploiting fish swim bladder resonances to improve automatic screening and tracking performance of U.S. Navy mid-frequency active sonar systems.
SSC showed, using a simulation-based approach, the extent to which it is feasible to use airborne ASW platforms as an underwater sound source useful in submarine echo detection. SSC developed ocean acoustics models which include the refracted paths and the evanescent path, and are capable of modeling the air/water interface. Airborne multi-tonal and broadband low frequency sources will be used as excitation sources. These model components were be incorporated into existing SSC multistatic coherent sonar performance simulations and used in conjunction with the Likelihood Ratio Tracker (LRT) model to determine the feasibility of the approach, optimal configurations, and requirements for specifically designed airborne sources. In addition SSC conducted a tradeoff study concerning available source noise generation alternatives for the infrasonic frequency source generation mechanism which will be experimentally verified to fully explore the feasibility of the evanescent (lateral wave) excitation path.
Future Air ASW will be conducted at higher altitudes, making visual, Mark-On-Top and RF techniques less accurate for receiver localization. Alternatives such as installing GPS receivers in the sonobuoys suffer from high cost or are easily jammed. Recent news reports concerning North Korea's jamming of joint US-South Korea military exercises highlights the vulnerability of our defense systems to GPS denial, and makes it critical to find alternate solutions that do not rely on GPS. What is needed are techniques that can provide buoy and target localization using acoustic information. Traditional acoustic stabilization techniques typically update only the relative geometry of the sensor field. Absolute positions depend on initial drop accuracy which at high altitudes is going to be challenging. Field ocean currents will also introduce errors that traditional acoustic buoy stabilization techniques cannot overcome. Signal Systems Corporation is developing a new and innovative acoustic approach of buoy and target localization to provide absolute target geo-location without visual, RF or GPS inputs.
The RAP/VLA and other emerging sonobuoy based sensing systems require a robust over-the-horizon (OTH) communications mechanism that offers low probability of detection (LPD) and low probability of intercept (LPI) as well as secure transmission. Signal Systems Corporation (SSC) will demonstrate a system in water with a RF Gateway Buoy. The RF Gateway Buoy will also house COTS SATCOM, VHF, and acoustic communications modules with encryption. 500 mile OTH transmission tests will be conducted using a custom designed land based Master Station.
Signal Systems Corporation, with its partners USSI and Marine Acoustics Inc, will show, using a simulation based design approach, that it is feasible to develop a highly automated Marine Mammal Mitigation Sonar (M3S), embedded in an AN/SSQ-125 source sonobuoy, which is effective in reducing operator workload while providing marine mammal mitigation to meet NAVAIR, OPNAV N45 requirements and the US government regulator (National Marine Fisheries Service) current standards. During the Phase I Option we will construct a breadboard of M3S and demonstrate its use in water. The SSC team has proposed a sound approach that comprehensively examines the entire set of risks associated with the M3S problem: sonar performance and development risk, regulatory approval risk, sonar automation in the presence of clutter, and achieving operator workload reduction. At the conclusion of Phase I, the SSC team will have a recommend M3S architecture, Key Performance Parameters that are needed for the final system, a simulation-based design assessment of the M3S performance with respect to these KPPs, conducted bench-top tests of the leading AN/SSQ-125 design changes, specifications for a prototype M3S in Phase II, briefing materials for regulatory review and a breadboard that will be tested.
The versatile and affordable design of SSC's compact acoustic sensor may be adapted to meet multiple customer specifications. This page highlights tracking of ground and air vehicles with internal combustions engines. Algorithms for impulsive sources (gunshots, mortars, explosives, etc) have been developed. Applications have been explored for tracking small drones, detecting and localizing voices, and interpreting ship's horn and bell signals.
Signal Systems Corporation (SSC) is developing the Maritime Acoustic Sensing Unit (MASU) to provide situational awareness to manned and unmanned naval assets. The MASU leverages our innovative acoustic chambered design developed for robotic vehicles to provide a compact rugged, self-contained sensor capable of detecting, locating and classifying sounds. We plan to demonstrate the capability of our compact sensor design to provide 360° detection, localization and classification of standard COLREGS signals out to one mile. We will improve our signal processing algorithms to detect and discriminate these sounds from non-navigational signals and develop a robust decision tree based classifier that will identify the signals to the operator. We will evaluate physical sensor design improvements to address the flow, wind, and platform noise effects, enabling us to meet the one mile detection range with good bearing accuracy.
Benefits include: Situational awareness for any robotic vehicle. Specifically the Navy's Common Unmanned Surface Vehicle (CUSV), Adaro ASV, Medium Displacement USV, The Army's Unmanned Ground Vehicle (UGV), and as a Sound Reception Device on commercial ships.
SSC is building a low power tri-axial acoustic sensor that leverages our existing acoustic chambered design to provide a directional sensor that has high sensitivity, rugged construction with low power consumption. Our approach extends prototypes developed under DoD sponsorship, including DARPA efforts. Our innovative chambered design provides a large physical aperture that includes novel wind noise reduction features without exposing sensitive microphone elements to the environment directly. The unit exhibits increasing acoustic gain at higher frequencies that help in classification of targets that have weak high frequency signature information.Download the ASU Brochure (PDF 148kB)
The two plots illustrate the elevation sensing performance against an ultralight target. In the top graph, the black dotted line is the ground truth, the actual, GPS measured elevation angle of the ultralight relative to the ASU. The colored lines show the ASU's elevation estimate at the time. During the highlighted blue region shows, the pilot turned off the engine
The lower plot shows the altitude and distance along the ground the ultralight was from the ASU. The black highlighted areas indicated where the ASU was tracking the ultralight
The image shows the usefulness of employing active notice cancellation algorithms in the detection and tracking process. The top plot shows how the tones from the vehicle can be removed from the microphone data. The images below that show how active noise cancellation prevents the ASU from tracking the vehicle it is mounted on.
Active Noise Control quiets offensive noise by using cancellation techniques, or anti-sound. Signal Systems Corporation's mission is to help quiet irritating noises so you can have a more peaceful life as well as tactical noise reduction and hearing loss prevention.
Abstract: The modern vehicle has evolved into a multimedia hub, becoming a vital integration and delivery point for a panoply of media and devices. However, the resulting in-vehicle noise pollution created by this multitude of services has significant potential to become annoying to all vehicle occupants. This problem motivated the authors to build a system that enables the configuration of in-vehicle personalized audio zones (PAZs) that don't require earphones. The PAZ system comprises a novel user interface, custom-designed headrests, and an infotainment noise-control subsystem. The performance evaluations of PAZ in a BMW 5 series sedan delivered approximately 20 decibels of isolation, which resulted in an overwhelmingly positive subjective experience for the occupants. PAZ not only ameliorates noise pollution, but also provides a unique solution to sound personalization via configurable audio zones and individual media selection that doesn't require headphones.
Many people have heard of active noise control, but with the exception of headphones, few people have experienced its benefits. Why has this happened?
The short answer is cost. Unlike over-hyped technologies, active noise control works. The obstacle has been to make active noise control a cost-effective solution to noise problems. This obstacle has been far more difficult than many people expected. When a technology is more expensive than its benefits are generally worth, only a small market exists for the technology.
Now, new technologies are usually expensive to start out. Early users of a technology pay a higher price for being first, with a competitive advantage as the benefit. Technology developers gain valuable experience working with early customers. This experience and know-how yields product improvements that provide more economical solutions for future customers. In this way, the technology spirals into wider and wider use, as the cost for implementation falls.
So, what happened to active noise control? Why don't we see active noise control technology in our daily lives? The answer lies in the fact that most consumers are reluctant to pay more than 100 to 2000 dollars for noise reduction solutions. This cost range has been difficult to achieve with effective active solutions. The notable exceptions are noise canceling headphones and some dishwashers.
The result is that other applications of active noise control have been in industrial situations, where the benefit for active noise control is driven by hearing safety concerns. In some cases, improving speech communication has been important enough to use active noise control. Even in industrial markets, active noise control technology spirals have been rare. The result is that the pervasive use of active noise control still waits for the "killer-app" that can propel it out of the one-of-a-kind, custom project cycle that best describes how much of active noise control technology is applied today.
So, where has active noise control been successfully applied? A partial list:
These products are successful because they have taken active noise control technology and reduced it to practice. Another common element is that with the exception of cabin noise reduction, the solution is 'simple'. By simple, I mean that the solution does not require an extensive number of microphones, sensors, cables, etc. In many cases the controller that produces anti-sound commands can be built with analog circuits, leading to lower costs and portability.
The exception to this rule is aircraft cabin noise reduction. In this case, numerous speakers (or headsets) and microphones are used. In the noise reduction system built into new Boeing aircraft, it appears that the noise reducing apparatus has been integrated into the entertainment system. This has the benefit of reducing the cost of the noise reducing system, since it is being added to an existing acoustic system. The existing entertainment system uses headphones, signal processors, and cabling that can be leveraged by the active noise control (ANC) design.
So where should we go in ANC technology development? I think that continued development of simple solutions is best done through education. Present commercial efforts are mired in patent issues and return on investment questions. Through education, engineers can be trained in the use of active noise control. When these engineers are confronted with design problems, they will be equipped to find niche solutions using active noise control.
Researchers in this field should focus on two approaches. The first is the development of integrated active control solutions for complex noise problems. Automobile audio systems, with integrated personal communications systems and active noise control technology could improve driving enjoyment and safety. A second approach is the search for the 'killer application'. As an example, are there new ways of communicating that rely in a fundamental way on ANC technology? We will have to wait and see.
SSC developed a MEDEVAC Active Noise Cancellation Acoustic Pillow (MANCAP) featuring active noise cancellation (ANC) and passive noise reduction measures to create a quiet zone around injured personnel's ears during evacuations in and around noisy military vehicles. The MANCAP concept allows access to the patient's face for respirators and medical treatment while installed on any standard NATO litter. The MANCAP will reduce the local noise level of the patient to less than 80 dBA in a military helicopter by leveraging our ANC algorithms, real time software, hardware and headrest technology previously developed under commercial and DoD sponsorship, including Army, Navy and Special Forces efforts.
Noise levels in crew compartments below the flight decks on Navy ships during flight operations have traditionally been extremely noisy due to jet engine noise as well as launch machinery transients. Levels exceed Navy desired levels by over 10 dB. Current state of the art materials do not work well at low frequencies. SSC proposes to develop an active noise solution that consists of a modular, fully integrated smart material that can be applied to the interior compartments of ships. The smart acoustic panel will reduce radiating noise by employing advanced smart materials such as polyvinylidene fluoride (PVDF) and lead zirconate titanate (PZT) actuation materials, embedded MEMs based acoustic and vibration sensors, and polyurethane foam for passive vibration absorption. A method to use smart acoustic materials to provide local noise control of manned spaces will also be investigated if global control proves to be unfeasible.
Benefits of this project include: development of acoustic smart panels and quiet zone generation will enhance habitability on aircraft, and in high noise manufacturing areas. It will also enhance vehicle stealth applications.
We are developing noise cancellation software for use in Army battlefield robotics. This software will eliminate unwanted signals from microphones mounted on an unmanned vehicle. We have recently tested our system on the Demo III Experimental Unmanned Vehicle (XUV) built by General Dynamics Robotic Systems Technology. Our noise cancellation software achieved over 40 dB narrowband cancellation while eliminating over 30 tones from the robots' background noise level.
Some of these results are presented in the Air Coupled Sensor Workshop Presentation Slides (Adobe Acrobat PDF Format 437 kB)
We have been developing active noise cancellation systems for acoustic composite tiles for several years. We have developed a real-time 48 channel controller using programmable DSPs. This system was integrated into a smart skin that was demonstrated underwater. Our control system designs are based on hierarchical approaches.
We are currently investigating on-line evolutionary techniques for fully adaptive control systems that change sensor and actuator configurations as well as filter coefficients. These systems promise to define the state of the art in affordable and effective controllers for intelligent materials.
We are currently developing an 80 channel active noise control system using programmable DSPs networked together. The active noise control system contains processing resources with over 16 Billion Operations Per Second capability.
A related publication is: L. Riddle and J. Murray, 'Smart Structure Active Sonar Echo Cancellation Using Frequency Scheduled Control,presented at the 1998 SPIE Conference on Smart Materials
A technical review of our progress appears in the Smart Skin Demonstration Presentation Slides (Adobe Acrobat PFD Format 159 kB)
A full length paper describing the trade-offs involved in making a cost effective ANC system for complex problems is described in:
L.Riddle, J. Murray and S. Lease, 'Active Noise Control Architecture for the Smart Skin Demonstration,' ACTIVE-99, International Symposium on Active Noise Control, Dec 2-4, 1999.
We have developed a new MATLAB™ based Active Noise Control Simulation Toolbox. The simulation offers finite element modeling interfaces, sensor, filter and hardware models, and state-of-the-art multi-channel adaptive LMS algorithms.
Christopher E. Ruckman,wrote an useful ANC FAQ in 1994-1999. It provides a solid introduction to the technology.
An edited list of active noise control web sites is maintained at the Open Directory Project.
Dr. Riddle formed Signal Systems Corporation in the summer of 1995, after more than 15 years working in corporate research and development and defense contracting. As President of SSC, Dr. Riddle brings a unique combination of research and management skills, plus technical expertise, to high technology systems engineering.
In addition to conducting or leading dozens of independent research and development projects, Dr. Riddle has extensive experience managing full scale engineering development (FSED) projects. His work has earned him professional recognition, through both awards and published papers, as well as a patent.
Dr. Riddle received his Ph.D., in Electrical and Computer Engineering, from the Johns Hopkins University. He completed his undergraduate studies at the Georgia Institute of Technology in Applied Physics with highest honors.
Ninety percent (90%) of our engineering staff hold advanced engineering degrees and more than 50% have been developing signal processing systems for at least 10 years. Signal Systems Corporation has 20 other staff members, 18 with Masters degrees and 7 with Ph.D's.
Sensor technology maker Signal Systems Corp. has received a potential five-year, $13.5M contract to provide undersea and anti-submarine warfare technologies to support the U.S. Navy’s sonar signal processing research and development efforts.
SSC was named one of twenty four World Class Team Award winners in 2014 by Northrup Grumman. Consideration for awards include: "product, service, quality and record" and "demonstrated delivery performance, outstanding program support, superior technical achievement and reported cost performance/competitiveness and/or continuous process improvement."
The Northrup Grumman press release can be found here.
Signal Systems Corporation in Severna Park, MD has been awarded a contract by the Naval Air Warfare Center Aircraft Division to use current sonobuoy systems to investigate the environment of coastal waters. Coastal waters experience rapid and sudden changes in environmental characteristics so it is important to the Navy to be able to make these measurements quickly and whenever needed. The contract was awarded as a Phase III Small Business Innovative Research contract, for $25 million over five years.
SSC is tasked to use the currently available air deployable active receiver (ADAR) sonobuoy in order to take these environmental measurements and to help give information which will determine the most effective way to search for hostile submarines.
Signal Systems' technology in multistatic signal and information processing is used for environmental assessment, improved target detection capability and advanced distributed networked sensor systems.
1127B Benfield Blvd
Millersville, MD 21108