Adaptive Beamsteering Cognitive Radar with Integrated Search-and-Track of Swarm Targets

The article of record as published may be found at http://dx.doi.org/10.1109/ACCESS.2021.3069350, IEEE AccessAdaptive beamsteering cognitive radar (AB-CRr) systems seek to improve detection and tracking performance by formulating a beam placement strategy adapted to their environment. AB-CRr builds a probabilistic model of the target environment that enables it to more efficiently employ its limited resources to locate and track targets. In this work, we investigate methods for adapting the AB- CRr framework to detect and track large target swarms. This is achieved by integrating the properties of correlated-motion swarms into both the radar tracking model and AB-CRr’s underlying dynamic probability model. As a result, a list of newly CRr-integrated contributions are enumerated: a) improved uncertainty function design, b) incorporates Mahalanobis nearest neighbors multi-target association methodology into AB-CRr, c) introduces a novel Kalman-based consolidated swarm tracking methodology with a common velocity state vector that frames targets as a correlated collection of swarm members, d) introduces an improved uncertainty growth model for updating environment probability map, e) introduces a method for incorporating estimated swarm structure and behavior into the uncertainty update model referred to as "track hinting", and f) introduces new metrics for swarm search/detection and tracking called swarm centroid track error and swarm tracking dwell ratio. The results demonstrate that AB-CRr is capable of adapting its beamsteering strategy to efficiently perform resource balancing between target search and swarm tracking applications, while taking advantage of group structure and intra-swarm target correlation to resist large swarms overloading available resources.Approved for public release; distribution is unlimited

Modeling SIGINT

NPS NRP Executive SummaryOPNAV and NAVAIR seek to more accurately assess both the engineering-level capability of a set of airborne SIGINT sensors against a representative set of threat emissions, and the impact of those airborne SIGINT sensors on effects chains. Intent is to assess current and future performance, better informing investment and design trade space decisions. The research objectives are threefold: survey existing SIGINT Modeling capabilities within the DOD, design and implement engineering level SIGINT modeling capabilities as required, and finally, match/aggregate those engineering level results to mission level models such as the Naval Simulation System (NSS) and the Advanced Framework for Simulation, Integration, and Modeling (AFSIM). The research approach will be straight forward. All researchers will collaborate on surveying the existing SIGINT modeling domain. Then the research team will create two sub teams. The first will investigate possible SIGINT Engineering modeling solutions. The second team will investigate the requirements for feeding SIGINT engineering details into the mission models. Deliverables are intended to be a completed survey of SIGINT Modeling, with an analysis of possible capability gaps, design and or production of engineering level SIGINT Models, and instructions for how to aggregate SIGINT engineering models into mission level models.N9 - Warfare SystemsThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Modeling SIGINT

NPS NRP Project PosterOPNAV and NAVAIR seek to more accurately assess both the engineering-level capability of a set of airborne SIGINT sensors against a representative set of threat emissions, and the impact of those airborne SIGINT sensors on effects chains. Intent is to assess current and future performance, better informing investment and design trade space decisions. The research objectives are threefold: survey existing SIGINT Modeling capabilities within the DOD, design and implement engineering level SIGINT modeling capabilities as required, and finally, match/aggregate those engineering level results to mission level models such as the Naval Simulation System (NSS) and the Advanced Framework for Simulation, Integration, and Modeling (AFSIM). The research approach will be straight forward. All researchers will collaborate on surveying the existing SIGINT modeling domain. Then the research team will create two sub teams. The first will investigate possible SIGINT Engineering modeling solutions. The second team will investigate the requirements for feeding SIGINT engineering details into the mission models. Deliverables are intended to be a completed survey of SIGINT Modeling, with an analysis of possible capability gaps, design and or production of engineering level SIGINT Models, and instructions for how to aggregate SIGINT engineering models into mission level models.N9 - Warfare SystemsThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

High Data Rate HF Communications for BFTN Using Advanced Waveform Techniques

NPS NRP Project PosterIn this feasibility study, we propose the application of advanced waveforms techniques (e.g. Orthogonal Frequency Division Multiplexing, OFDM) for high data rate HF communications within the Battle Force Tactical Network (BFTN). OFDM and other multicarrier-type modulations can potentially mitigate the multipath problem that HF is subjected to and potentially increase the limited data throughput of HF systems. While SATCOM provides reliable RF communications and data links, the Navy needs a viable alternative to SATCOM. Beyond line of sight (BLOS) HF communications (2-30 MHz band) can be improved using advanced digital waveform techniques that are used in wireless and cellular communications. It can be a complementary system or be the solution to SATCOM-degraded scenarios.Naval Information Warfighting Development Center (NIWDC)U.S. Fleet Forces Command (USFF)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

High Data Rate HF Communications for BFTN Using Advanced Waveform Techniques

NPS NRP Executive SummaryIn this feasibility study, we propose the application of advanced waveforms techniques (e.g. Orthogonal Frequency Division Multiplexing, OFDM) for high data rate HF communications within the Battle Force Tactical Network (BFTN). OFDM and other multicarrier-type modulations can potentially mitigate the multipath problem that HF is subjected to and potentially increase the limited data throughput of HF systems. While SATCOM provides reliable RF communications and data links, the Navy needs a viable alternative to SATCOM. Beyond line of sight (BLOS) HF communications (2-30 MHz band) can be improved using advanced digital waveform techniques that are used in wireless and cellular communications. It can be a complementary system or be the solution to SATCOM-degraded scenarios.Naval Information Warfighting Development Center (NIWDC)U.S. Fleet Forces Command (USFF)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Detection Performance of Matched Transmit Waveform for Moving Extended Targets

Depending on the radar-target dynamics, the time extent and amplitude of a moving extended target from a radar’s perspective may actually change as a function of relative motion. It follows that waveform design should accommodate for the increase or decrease of a target’s time extent and changes in amplitude as the target moves towards or away from a radar or vice versa. This paper shows the performance gain and/or degradation of both matched transmit waveform (called eigenwaveform) and the classical wideband pulsed transmit waveform when the effect of motion on target’s time extent and amplitude changes are considered

MATCHED WAVEFORM DESIGN AND ADAPTIVE BEAMSTEERING IN COGNITIVE RADAR APPLICATIONS

Cognitive Radar (CR) is a paradigm shift from a traditional radar system in that previous knowledge and current measurements obtained from the radar channel are used to form a probabilistic understanding of its environment. Moreover, CR incorporates this probabilistic knowledge into its task priorities to form illumination and probing strategies thereby rendering it a closed-loop system. Depending on the hardware's capabilities and limitations, there are various degrees of freedom that a CR may utilize. Here we will concentrate on two: temporal, where it is manifested in adaptive waveform design; and spatial, where adaptive beamsteering is used for search-and-track functions. This work is divided into three parts. First, comprehensive theory of SNR and mutual information (MI) matched waveform design in signal-dependent interference is presented. Second, these waveforms are used in a closed-loop radar platform performing target discrimination and target class identification, where the extended targets are either deterministic or stochastic. The CR's probabilistic understanding is updated via the Bayesian framework. Lastly, we propose a multiplatform CR network for integrated search-and-track application. The two radar platforms cooperate in developing a four-dimensional probabilistic understanding of the channel. The two radars also cooperate in forming dynamic spatial illumination strategy, where beamsteering is matched to the channel uncertainty to perform the search function. Once a target is detected and a track is initiated, track information is integrated into the beamsteering strategy as part of CR's task prioritization

Transmit Energy Efficiency of Two Cognitive Radar Platforms for Target Identification

The article of record as published may be found at http://dx.doi.org/10.3390/aerospace2030376Cognitive radar (CRr) is a recent radar paradigm that can potentially help drive aerospace innovation forward. Two specific platforms of cognitive radar used for target identification are discussed. One uses sequential hypothesis testing (SHT) in the receiver processing and is referred to as SHT-CRr and the other one uses maximum a posteriori (MAP) and is referred to as MAP-CRr. Our main goal in this article is to make a practical comparison between SHT-CRr and MAP-CRr platforms in terms of transmission energy efficiency. Since the performance metric for the SHT-CRr is the average number of illuminations (ANI) and the performance metric for MAP-CRr is the percentage of correct decisions (Pcd), a direct comparison between the platforms is difficult to perform. In this work, we introduce a useful procedure that involves a metric called total transmit energy (TTE) given a fixed Pcd as a metric to measure the transmit energy efficiency of both platforms. Lower TTE means that the platform is more efficient in achieving a desired Pcd. To facilitate a robust comparison, a transmit-adaptive waveform that consistently outperforms the pulsed waveform in terms of both Pcd and ANI is needed. We show that a certain adaptive waveform called the probability weighted energy signal-to-noise ratio-based (PWE-SNR) waveform outperforms the pulsed wideband waveform (i.e., flat frequency response) in terms of ANI and Pcd for all ranges of transmit waveform energy. We also note that the Pcd performance of SHT-CRr can be drastically different from the probability threshold (i.e., the probability value that is used to stop radar illumination for the purposes of classification), which is critically important for CRr system designers to realize. Indeed, this fact turns out to be key in accomplishing our goal to compare SHT-CRr and MAP-CRr in terms of transmit energy efficiency

Digital Image Synthesis of Structured False Targets Against High Range Resolution Profiling Radars

CRUSER TechCon 2018 Research at NPS. Wednesday 1: Sensin