Adaptive MIMO Radar for Target Detection, Estimation, and Tracking

We develop and analyze signal processing algorithms to detect, estimate, and track targets using multiple-input multiple-output: MIMO) radar systems. MIMO radar systems have attracted much attention in the recent past due to the additional degrees of freedom they offer. They are commonly used in two different antenna configurations: widely-separated: distributed) and colocated. Distributed MIMO radar exploits spatial diversity by utilizing multiple uncorrelated looks at the target. Colocated MIMO radar systems offer performance improvement by exploiting waveform diversity. Each antenna has the freedom to transmit a waveform that is different from the waveforms of the other transmitters. First, we propose a radar system that combines the advantages of distributed MIMO radar and fully polarimetric radar. We develop the signal model for this system and analyze the performance of the optimal Neyman-Pearson detector by obtaining approximate expressions for the probabilities of detection and false alarm. Using these expressions, we adaptively design the transmit waveform polarizations that optimize the target detection performance. Conventional radar design approaches do not consider the goal of the target itself, which always tries to reduce its detectability. We propose to incorporate this knowledge about the goal of the target while solving the polarimetric MIMO radar design problem by formulating it as a game between the target and the radar design engineer. Unlike conventional methods, this game-theoretic design does not require target parameter estimation from large amounts of training data. Our approach is generic and can be applied to other radar design problems also. Next, we propose a distributed MIMO radar system that employs monopulse processing, and develop an algorithm for tracking a moving target using this system. We electronically generate two beams at each receiver and use them for computing the local estimates. Later, we efficiently combine the information present in these local estimates, using the instantaneous signal energies at each receiver to keep track of the target. Finally, we develop multiple-target estimation algorithms for both distributed and colocated MIMO radar by exploiting the inherent sparsity on the delay-Doppler plane. We propose a new performance metric that naturally fits into this multiple target scenario and develop an adaptive optimal energy allocation mechanism. We employ compressive sensing to perform accurate estimation from far fewer samples than the Nyquist rate. For colocated MIMO radar, we transmit frequency-hopping codes to exploit the frequency diversity. We derive an analytical expression for the block coherence measure of the dictionary matrix and design an optimal code matrix using this expression. Additionally, we also transmit ultra wideband noise waveforms that improve the system resolution and provide a low probability of intercept: LPI)

Toward Data-Driven Radar STAP

Catalyzed by the recent emergence of site-specific, high-fidelity radio frequency (RF) modeling and simulation tools purposed for radar, data-driven formulations of classical methods in radar have rapidly grown in popularity over the past decade. Despite this surge, limited focus has been directed toward the theoretical foundations of these classical methods. In this regard, as part of our ongoing data-driven approach to radar space-time adaptive processing (STAP), we analyze the asymptotic performance guarantees of select subspace separation methods in the context of radar target localization, and augment this analysis through a proposed deep learning framework for target location estimation. In our approach, we generate comprehensive datasets by randomly placing targets of variable strengths in predetermined constrained areas using RFView, a site-specific RF modeling and simulation tool developed by ISL Inc. For each radar return signal from these constrained areas, we generate heatmap tensors in range, azimuth, and elevation of the normalized adaptive matched filter (NAMF) test statistic, and of the output power of a generalized sidelobe canceller (GSC). Using our deep learning framework, we estimate target locations from these heatmap tensors to demonstrate the feasibility of and significant improvements provided by our data-driven approach in matched and mismatched settings.Comment: 39 pages, 24 figures. Submitted to IEEE Transactions on Aerospace and Electronic Systems. This article supersedes arXiv:2201.1071

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Analysis of Software-Defined Networks as a Mechanism for Enforcing Corporate Security Policies in OT Networks

Cyber Security has been given a high priority for operational technology systems in recent years after specific cyber-incidents targeting them. Previously, these systems were primarily concerned with reliability; however, cyber security is now viewed as a critical aspect in avoiding production damage and financial losses. According to certain studies, replacing traditional networks in OT systems with software-defined networks (SDN) minimizes cyber-attacks due to the features provided by these networks. SDN networks have various advantages over traditional networks, due to the separation of the data plane and control plane. The concern is whether SDN networks are more dependable than existing traditional networks, and whether we can take advantage of all of SDN's characteristics when connecting with OT systems. Furthermore, deploying cyber security on a network infrastructure necessitates the creation and implementation of security policies that define the authorized communication between network devices. There is, however, a distinction to be made between security policies and the technologies that implement them. There is also often a distinction between intended policy and deployed or configured policy. Therefore there is a need to confirm compliance between policy and reality in a network. This is especially true in operational technology systems where there is a lot of network infrastructure and special purpose devices which can not be scanned or analyzed using traditional cyber security tools. To address the cyber security issues in operational technology systems, this dissertation reviews cyber-incidents reported on them and summarizes possible attacks on each of their sub-systems to gain broader insight into vulnerabilities present in them and uses the common vulnerability exposure database to enumerate trends. Then, a process is formally developed and evaluated through a proof of concept tool to detect the security policy implemented in the control rules of an SDN switch deployed in an industrial control system network. These rules were analyzed to determine if this security policy is compliant with the organization's high-level policies.doctoral, Ph.D., Computer Science -- University of Idaho - College of Graduate Studies, 2022-0

Adaptive polarization design for target detection and tracking

Transmitting waveforms with different polarizations in radar systems provide morecomplete information about the target and its environment, ensuring a significantenhancement of the radar’s performance. Conventional polarimetric radars transmitwaveforms with a fixed polarization pattern, independent of the target and cluttercharacteristics. In this chapter, we explore the adaptive design of radar polarizationwaveforms. We focus on a closed-loop system that sequentially estimates thetarget and clutter scattering parameters and then uses these estimates to select thepolarization of the subsequent waveforms.We demonstrate that the radar system performanceis significantly improved when the polarization of the transmitted signalis optimally and adaptively selected to match the polarimetric aspects of the targetand the environment. In particular, we include an overview of our recent results inpolarimetric design for radar detection and tracking.Fil: Hurtado, Martin. Universidad Nacional de La Plata. Facultad de Ingeniería. Departamento de Electrotecnia. Laboratorio de Electrónica Industrial, Control e Instrumentación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Gogineni, Sandeep. Washington University in St. Louis; Estados UnidosFil: Nehorai, Arye. Washington University in St. Louis; Estados Unido

A highly conserved human gene encoding a novel member of WD-repeat family of proteins (WDR13)

We have identified and characterized a novel member of the WD-repeat motif gene family, WDR13, which contains 9 exons and 8 introns. The gene has been mapped to the genomic locus Xp11.23 by fluorescent in situ hybridization and in silico mapping. Sequence analysis has revealed a continuous open reading frame (ORF) encoding for 485 amino acids with six WD motifs. The expression of this gene has been detected in all the tissues analyzed with significantly varied expression levels among the tissues studied. Analysis of EST clones from various tissues, showing significant homology to WDR13, has identified two spliced variants. The transcription start point has been mapped. Promoter analysis has identified high activity in the 5' UTR, which interestingly showed a testis-specific activity in the transgenic animals studied. The subcellular localization of the WDR13 protein in the nucleus suggests that it may also have a regulatory role in nuclear function along with protein-protein interaction like other members of the WD family of proteins