Nikita Visnevski

Syntactic Modeling and Signal Processing of Multifunction Radars: A Stochastic Context-Free Grammar Approach

Multifunction radars (MFRs) are sophisticated sensors with complex dynamical modes that are widely used in surveillance and tracking. This paper demonstrates that stochastic context-free grammars (SCFGs) are adequate models for capturing the essential features of the MFR dynamics. Specifically, MFRs are modeled as systems that ldquospeakrdquo a language that is characterized by an SCFG. The paper shows that such a grammar is modulated by a Markov chain representing radars policy of operation. The paper also demonstrates how some well-known statistical signal processing techniques can be applied to MFR signal processing using these stochstic syntactic models. We derive two statistical estimation approaches for MFR signal processing-a maximum likelihood sequence estimator to estimate radars policies of operation, and a maximum likelihood parameter estimator to infer the radar parameter values. Two layers of signal processing are introduced in this paper. The first layer is concerned with the estimation of MFRs policies of operation. It involves signal processing in the CFG domain. The second layer is concerned with identification of tasks the radar is engaged in. It involves signal processing in the finite-state domain. Both of these signal processing techniques are important elements of a bigger radar signal processing problem that is often encountered in electronic warfare applications-the problem of the estimation of the level of threat that a radar poses to each individual target at any point in time.

Threat Estimation by Electronic Surveillance of Multifunction Radars: A Stochastic Context Free Grammar Approach

Multi-function radars (MFRs) are sophisticated sensors that are widely used in military systems. It is shown that the stochastic context free grammar (SCFG) efficiently captures the essential features of the MFR dynamics compared to more traditional finite Markov models (regular grammars). The dynamics of the MFR are formulated as a mixture of two SCFGs - the mixture parameter determining the threat level. We then present a maximum likelihood threat estimation algorithm by capturing the noisy radar signals represented as strings from the MFR language. The relative simplicity of the SCFG model facilitates development of a systematic design procedure for electronic warfare (EW) surveillance algorithms

Modeling and simulation for unmanned and autonomous system test and evaluation

Test and evaluation may be viewed as a technology enabler for the successful deployment of unmanned vehicles and robots in all their envisioned applications. It is however a challenging endeavor, considering that roboticists and developers are not used to thinking of test and evaluation as an integral component of robot development. Moreover, the community who has conducted test and evaluation up to this date does not possess the tools to cope with the growing complexity of unmanned and autonomous systems. This paper proposes a solution to one of the hardest problems in testing and evaluation of robots: test planning. The approach put forward relies on constructive simulation tools and on new techniques for searching in high dimensional spaces. The goal of the test planner is to generate a set of tests that make highly efficient use of resources to unveil weaknesses of the system under test. A secondary objective of the paper is to create reciprocal awareness between test and evaluation and robotics communities, who could benefit significantly from each other.

Analysis of autonomous deconfliction in Unmanned Aircraft Systems for Testing and Evaluation

Autonomous deconfliction capability is crucial to the successful deployment of Unmanned Aircraft Systems (UAS) in most of their envisioned application scenarios. Civil and military applications of UAS demand ever-decreasing levels of human involvement and oversight, hence, UAS need to grow in autonomy. Autonomous deconfliction is a capability that is not only essential for the UASs self-preservation, but also for avoiding damage to static infrastructure and/or to friendly and civilian aircraft flying contiguously. It is also key to the successful completion of the missions assigned to the UAS. Numerous solutions to partial aspects of autonomous deconfliction have been proposed. However, there is an enormous gap in systematic approaches that may be used for Testing and Evaluation (T&E) of autonomous capabilities such as deconfliction. This paper focuses on application of Systems Engineering-oriented tools to the analysis of autonomous deconfliction capability in UAS. The Systems Capability Technical Reference Model (SC-TRM) presented in this work helps in identifying the different aspects of a deconfliction solution. Besides presenting the Systems Engineering-oriented tools and the analysis of the deconfliction problem based on those tools, this paper also proposes venues that may enable concrete implementation and development of T&E methods that are applicable to civil as well as military applications.

Embedded instrumentation systems architecture

The objective of the Embedded Instrumentation Systems Architecture (EISA) initiative is to develop a comprehensive methodology for large-scale, non-intrusive, flexible data collection for test and evaluation (T&E) needs. These needs include system-level developmental, operational, and continuous T&E. The architecture can also be useful in monitoring, diagnostics and health management, as well as protection in control applications. This paper briefly explains how EISA architecture offers a metadata driven methodology for heterogeneous data collection and aggregation in a synchronized and time-correlated fashion. It also supports real-time instrumentation and sensor management as well as virtual (synthetic) instrumentation.

Evolutionary framework for test of autonomous systems

A DoD mission and challenge is to enable a high percentage of autonomous vehicles in the warfighter fleet by 2015. These systems will need to display a high degree of autonomous capabilities. The capabilities of these autonomous systems must be acceptable to the warfighter and his/her logistical support structure. Autonomous systems of the future will need to be tested so their mission capabilities and robustness are predictable to the warfighter. The principal challenge therefore is the set of test strategies for these future autonomous systems. The goal of the test community is that these autonomous systems be broadly accepted to seamlessly operate either independently or as part of a human-in-the-loop system. Our goal is to develop an efficient intelligent test process that will enable the rapid introduction of autonomous systems on the battlefield. We propose a novel war game simulation-based multi-objective evolutionary test framework that combines the elements of testing an autonomous systems mission execution capabilities as a function of its innate capabilities and evolutionary computation.

A UAS capability description framework: Reactive, adaptive, and cognitive capabilities in robotics

This paper offers a framework that helps in characterizing, analyzing, and developing Unmanned Autonomous Systems (UAS) capabilities including autonomy, adaptability, and machine cognition. We propose a technical reference model that brings these levels of capabilities together into a three-dimensional graphical model. Based on this technical reference model, we offer a system-theoretic analysis framework that includes three views into systems capabilities - reactive, adaptive and cognitive. For illustration purposes, this framework is applied to the analysis of capabilities of autonomous systems derived from four fundamental schools of thought in robotics - deliberative, reactive, hybrid and probabilistic. This exercise helps in understanding where the state of the art currently is in terms of UAS capabilities, what capabilities modern UAS lack, and what capabilities could be expected in the near future. The approach presented in this work provides a useful foundation for capability development and capability testing in UAS.

Testing and evaluation aspects of integration of unmanned air systems into the national air space

Current developments show that the integration of Unmanned Aerial Systems (UAS) into the National Airspace System (NAS) is a process that will inevitably happen. Arguably, it may be viewed as one of the key milestones in the history of aviation. Whereas the majority of research and development efforts are being invested on developing the core technologies and regulations to enable such a leap, there are currently a number of gaps that need to be addressed to transition those new technologies to daily operations with no detriment to performance of the NAS and chiefly, to safety of the NAS. One of those gaps relates to the efficient Testing and Evaluation (T&E) methodologies and procedures that need to be applied to guarantee smooth integration of UAS with varying levels of autonomy. Another main gap relates to the performance metrics that need to be considered to support these new T&E processes. This paper elaborates on those two aspects and it shows examples of how to streamline T&E to accelerate UAS integration.

Evolutionary computing for mission-based test and evaluation of unmanned autonomous systems

Test and evaluation may be viewed as a technology enabler for the successful deployment of unmanned vehicles and robots in all their envisioned applications. It is however a challenging endeavor, considering that roboticists and developers are not used to thinking of comprehensive test and evaluation as an integral part of robot development. Moreover, the community who has conducted test and evaluation up to this date does not possess the tools to cope with the growing complexity of unmanned and autonomous systems. This paper proposes an approach to one of the hardest problems in testing and evaluation of robots: mission-based test planning. This approach relies on constructive simulation tools and on evolutionary computing techniques for searching in high dimensional spaces of possible test scenarios. The goal of the test planner is to generate a set of tests that make highly efficient use of resources to unveil weaknesses of the system under test in a context of a specific mission.