Capraro Technologies (United States)

Because radio spectrum is a finite resource, its usage and sharing is regulated by government agencies. These agencies define policies to manage spectrum allocation and assignment across multiple organizations, systems, and devices. With more portions of the radio spectrum being licensed for commercial use, the importance of providing an increased level of automation when evaluating such policies becomes crucial for the efficiency and efficacy of spectrum management. We introduce our Dynamic Spectrum Access Policy Framework for supporting the United States government's mission to enable both federal and non-federal entities to compatibly utilize available spectrum. The DSA Policy Framework acts as a machine-readable policy repository providing policy management features and spectrum access request evaluation. The framework utilizes a novel policy representation using OWL and PROV-O along with a domain-specific reasoning implementation that mixes GeoSPARQL, OWL reasoning, and knowledge graph traversal to evaluate incoming spectrum access requests and explain how applicable policies were used. The framework is currently being used to support live, over-the-air field exercises involving a diverse set of federal and commercial radios, as a component of a prototype spectrum management system.

An airborne ground looking radar sensor's performance may be enhanced by selecting algorithms adaptively as the environment changes. A short description of an airborne intelligent radar system (AIRS) is presented with an in-depth description of the knowledge based filter and detection portions. A second level of artificial intelligence (AI) processing is presented that monitors, tests, and learns how to improve and control the first level. This approach is based upon metacognition.

Abstract An airborne ground looking radar sensor’s performance may be enhanced by selecting algorithms adaptively as the environment changes. A short description of an airborne intelligent radar system (AIRS) is presented with a description of the knowledge based filter and detection portions. A second level of artificial intelligence (AI) processing is presented that monitors, tests, and learns how to improve and control the first level. This approach is based upon metacognition, a way forward for developing knowledge based systems.KeywordsMetacognitionradarsignal processingCFARknowledge-basedsensors

The desire to anticipate actions before they occur is a goal within the military. Cognitive sensor and communications systems along with distributed radar systems are key enablers to meet this need. Close in sensing examples are provided showing the value of waveform diversity in distributed radar. The use of waveform diversity presents a challenge to the electromagnetic compatibility (EMC) community.

This chapter contains sections titled: Introduction Problem Formulation and Design Issues KA Data Selector 2S-DSP Data Selection Procedure RP-ANMF Detector Performance Analysis Conclusions References Appendix 6A: Registration Geometry

The multistatic ambiguity function can be used as a tool for analyzing multistatic radar systems. It has been demonstrated that the multistatic ambiguity function can serve as a guideline for developing multistatic radar signal processing rules and waveform selection strategies in system configurations with a single transmitter and multiple receivers. In this work we extend the development of multistatic ambiguity function to radar systems with multiple transmitters and multiple receivers.

Many practical problems arise when implementing digital terrain data in airborne knowledge-aided (KA) space-time adaptive processing (STAP). This paper addresses these issues and presents solutions with numerical implementations. In particular, using digital land classification data and digital elevation data, techniques are developed for registering these data with radar return signals, correcting for Doppler and spatial misalignments, adjusting for antenna gain, characterizing clutter patches for secondary data selection, and ensuring independent secondary data samples. These techniques are applied to select secondary data for a single-bin post-Doppler STAP algorithm using multi-channel airborne radar measurement (MCARM) program data. Results with the KA approach are compared with those obtained using the standard sliding window method for choosing secondary data. These results illustrate the benefits of using terrain information, a priori data about the radar, and the importance of statistical independence when selecting secondary data for improving STAP performance

As CPUs increase in performance, the number of passive components on the surface of circuit boards also increases dramatically. To reduce the number of components, as well as improve the electrical performance (i.e. reduce inductance), designers are increasingly embedding capacitive layers in the PCB. The majority of the products in use utilize reinforced epoxy laminates. These products are relatively easy to handle, but the thickness and Dk limit the effectiveness of the layer to perform as a capacitor. Other materials are being developed that are thinner (and thus increase capacitance), but either have problems with dielectric breakdown strength, handling or offer only a marginal improvement over existing materials. This paper describes new non‐reinforced substrates for use as embedded capacitance layers that address these issues. The material selection process, substrate processing and electrical performance are reviewed.

Future US Air Force sensor systems must be able to adapt to changing environments in real time. A capabilities-based modeling approach offers a new method for building the next generation weapon system. To accommodate this model based approach, the Department of Defense (DoD) is promoting the use of waveform diversity for active radar systems. Building a weapon system including one or more systems with waveform diversity will require the use of artificial intelligence (AI) tools and techniques. We provide a model of how an aircraft sensor system can be retrofitted to accommodate radars employing waveform diversity without causing fratricide.