MERC has a staff of Electronic Warfare (EW) professionals providing critical software support to both Air Force and Navy weapon systems. MERC's software experience spans the entire spectrum of EW to include Radio Frequency (RF), Electro Optical (EO) and Infrared (IR). Through our broad EW systems experience, MERC is postured to provide "one stop shopping" for all EW related requirements to include operational flight program design, mission data threat analysis and reprogramming, hardware technology insertion, diagnostic system hardware and software test program sets, training system software, modeling and simulation, and software tool sets. MERC is a recognized industry expert in advanced RF pulse train de-interleaving and real-time geolocation with patents currently on file. MERC's EW laboratory includes a host of stimulation resources for urban environment signal analysis for the demonstration of new EW technologies to assess technology readiness, optimize design solutions, reduce program risk, and lower EW system life-cycle cost. MERC is now pursuing both cognitive and cyber EW applications to continue our growth as a recognized industry leader in full spectrum EW solutions.
The ALQ-161 electronic warfare (EW) system is employed by the B-1B bomber aircraft and consists of over 100 line replaceable units (LRUs) making it one of the most complex EW systems in the Air Force inventory. MERC is under contract from the Warner Robins Air Logistics Complex to address system software deficiencies, provide engineering support to the software integration laboratory, and provide configuration management support.
MERC's expert engineering expertise is leading the way in advanced system multi-beam processing, agile emitter processing, receiver scan analysis, and catchall processing to improve aircraft survivability in high threat environments. MERC's systems engineering experience provides solutions to improve overall ALQ-161 effectiveness , increase availability and reduce total ownership cost.
The ALR-69(A) was the follow-on replacement system for the current ALR-69 Radar Warning Receiver (RWR) currently employed on US aircraft such as the F-16 fighter, A-10, and the C-130 transport aircraft. Under subcontract to Raytheon Electronic Systems, MERC provided extensive threat analysis and subsequent Electronic Identification Database design, development and testing for the ALR-69(A). Analysis included the identification of unique emitter parameters that will be useful for such advanced functionality as complex environment deinterleaving, specific emitter identification, and emitter geolocation. Early identification of these emitter characteristics helps direct system design decisions to provide enhanced functionality at lower cost.
MERC performed an analysis of the existing ALR-69 laboratory toolset to determine requirements for modification or replacement of existing tools for operation with the ALR-69(A). We identified modifications to the current system design and are now producing a new toolset to support the ALR-69(A) over the course of the expected system lifetime. This toolset is comprised of a combination of new and existing tools and technologies.
MERC is also providing Raytheon Electronic Systems with on-site engineering and programming support for key elements of the ALR-69(A) system design and development effort. We are working together to develop advanced pulse deinterleaving and pulse buffer management architecture that will allow the ALR-69(A) system to operate efficiently in a complex, high density RF environment. Future support areas include specific emitter identification and geolocation algorithms and technologies.
We are proud of our ongoing partnership with the Electronic Warfare Directorate at the Warner Robins Air Logistics Complex. Together, we provide software and support system engineering services to maintain and enhance the Tactical Electronic Warfare Suite (TEWS) deployed on the F-15 air superiority fighter aircraft. Our system engineering, code generation, and functional testing capabilities are key for the development and release of two block cycle updates to the ALR-56A Pacer Turbo Radar Warning Receiver (RWR) Operational Flight Program (OFP) software. MERC has also provided threat data analysis and threat identification database programming for this system in conjunction with the updates.
We manufactured a mobile test cart to provide power and cabling for the RWR and the ALE-45 Electronic Countermeasures Dispenser to be operated as stand-alone units or in conjunction with other components of the TEWS system. We also designed a set of test computers that simulate chaff and flare loads and provide system operational feedback to monitor stores inventory and dispense functions. MERC supplied a COTS test instrumentation package and performed integration testing to ensure operation with the ALR-56C and ALR-56A Pacer Turbo RWR systems.
Currently, MERC is designing and developing a user-reprogrammable F-15 Central Computer simulator. This simulator will be integrated with the ALR-56C RWR and the ALQ-135 Internal Countermeasures Set. MERC has also performed feasibility studies evaluating the impacts of re-hosting the TEWS development tools and threat data file verification tools from the VAX to a PC environment. Re-hosting these tools will be completed during the next phase of the program.
A Missile Warning Receiver System (MWR) must have a very high probability of detecting missiles, while at the same time, minimizing the number of false alarms. The MWR must also function autonomously and be able to signal for electronic countermeasures very quickly. Background clutter acts synergistically with missile signatures changing during flight to provide a demanding task for the programmers of these systems.
Relatively recent software developments in the field of artificial intelligence (AI) can now attack the problem of isolating threat signals in high-density IR/UV environments. MERC has received two USAF contracts for MWRs, both IR and UV, calling for the study and analysis of AI techniques and algorithms to distinguish missiles from background signals. MERC’s analysis has utilized AI techniques to globally train detection algorithms with signatures taken from large quantities of recorded data containing both missiles and background sources. After training, a classification network then has the informed detection intelligence to reliably detect, discriminate, and declare incoming missiles. MERC has demonstrated reduction of false alarm rates by two-thirds on one combat system.
The AI approach is comparable to tediously juggling millions of data items using traditional programming techniques (i.e., decision trees and loops). For example, changes in one parameter to accommodate one particular scenario frequently deteriorate the detection quality of previously programmed scenarios. Standard programming becomes a difficult process, balancing one signal against another. In comparison, a classification network, after training, is programmed to select the mathematically best case to all inputs.
While this may sound straightforward, there are the additional constraints to also operate within limitations of available memory and processing power in currently fielded systems. MERC has many years of experience in network selection for such systems and in other signal processing and artificial intelligence algorithms.
Mercer Engineering Research Center has explored novel signal processing approaches to solve EW problems with artificial intelligence based algorithms within a digital receiver. Low power RF pulse detection is typically achieved by the improvement of hardware, which is an expensive alternative. Sensitivity improvements are achieved using wavelet algorithms and high-order statistical detectors, improving signal detection by more than 3 dB over the conventional PolyPhase Filter technique. The goals of this research were to detect and identify very low power pulsed signals and determine their pulse characteristics for identification.
Wavelet algorithms decompose a signal into its simpler components ,like a Fast Fourier Transform (FFT), with a localization property that allows them to efficiently portray signals with discontinuities (unlike an FFT). Their multi-resolution analysis separates a signal into fine and coarse resolution components.
After wavelets are utilized to quantify the energy, a determination must be made about the existence of a pulse. MERC used an unconventional method involving High Order Statistics to determine the Gaussian part of a scale to separate the pulsed energy from background noise.
The HPI System Analysis Model (HSAM) program leveraged the design of a previous system analysis model produced by MERC for testing an advanced pulse-deinterleaving algorithm. The HSAM system hosts the AN/WLR-8A/HPI signal processing code in a software shell that emulates the system's native operating system while hosted on a Linux based desktop workstation. The HSAM environment generator models the dynamic motion and electromagnetic environment and provides those inputs to the HPI system to stimulate it to react as if would in the operational environment. The model includes receiver anomalies such as spurious signals, images at band crossovers, transfer function inaccuracies, density driven pulse corruption levels as a function of bandwidth and recovery time of video amplifiers and detectors, system threshold impacts on timing accuracy and measurement, preprocessing and system shadow time effects on pulse buffer data.
The signal processing code is then connected to the actual control display processor for the system and provides actual expected system response to the input threat data. This tool is used for threat data file validation and for operator training. Automated testing of the database is also provided with a tool for automated scoring of the test and reporting to the database developer.
The Automatic Direction Finding (ADF) System Analysis Model (ASAM) is a follow-on to the HSAM program that provides for integration of the ADF module upgrade to the WLR-8. In addition to the existing HSAM functionality, ASAM adds capability to the HSAM environment generation by providing a COTS signal generator module that produces a video signal consistent with the threat signal that is sent to the ADF module. It also provides platform-positioning information via the scenario generator to provide fully functional ADF operation for testing and validation.
MERC has provided multiple modernization updates to the Integrated Support Stations used by the Air Force system engineers responsible for the ALR-56A, ALR-56C, and ALR-69 Radar Warning Receivers, and the AN/ALE-45 Countermeasures Dispenser on the F-15 aircraft. These efforts were designed to replace obsolete hardware and software components to ensure system supportability for the foreseeable future.
MERC integrated legacy hardware components critical to station operation into a more modern configuration including updated computer hardware and operating systems. MERC provided new, sustainable system architectures at minimal cost and with no reduction in system operational capability. System modifications ranged from replacing proprietary custom hardware boards with COTS field-programmable gate array (FPGA) systems, to writing new drivers for legacy proprietary hardware. MERC has also conributed both major and minor software changes. Updates included improvements to the user interface modules to provide interpreted, man-readable test result data instead of raw data files.
MERC was able to replace an unsupported legacy computer by duplicating the functionality provided by that system through the use of open-source software running on modern computer systems and modified as necessary to support the legacy system requirements.
MERC provided support for the Multi-System Electronic Warfare Reprogramming Integrated Toolset (MERITS) for the Air Force AN/ALR-46 and AN/ALR-69 Radar Warning Receiver systems. MERC had previously supported two versions of the MERITS application, the original Macintosh-based system and a more recent, PC-based system.
For the original Macintosh-based system, MERC utilized complex reverse-engineering techniques to provide a full set of UML-based documentation for the application. MERC then went on to resolve numerous software issues within the system that caused excessive user review and editing of the output reprogramming file.
MERC completed initial development and fielding of the PC-based version of the MERITS application using Microsoft C#.NET, Windows Forms, and Microsoft SQL Server. Using the updated Macintosh system as a requirements baseline, MERC initiated a complete architecture redesign of the application to produce a more efficient and maintainable design. The original requirements were fully implemented and released. MERC then moved forward to incorporate new user requirements and enhancements into the system to provide a more complete and robust toolset.
Additionally, based on the enthusiastic response of the user community, MERC is now developing a front-end database and editor tool that can serve as a generic Electronic Warfare threat database and can support connections to mission data generation tools for a wide variety of Electronic Warfare systems.