This paper deals with the problem of Paretooptimal waveform design in the presence of colored Gaussian noise, under a similarity and an energy constraint.At the design stage, we determine the optimal radar code according to the following criterion: joint constrained maximization of the detection probability and constrained minimization of the Cramer Rao Lower Bound (CRLB) on the Doppler estimation accuracy.This is tantamount to jointly maximizing two quadratic forms under two quadratic constraints, so that the problem can be formulated in terms of a non-convex multi-objective optimization problem.In order to solve it, we resort to the scalarization technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions.At the analysis stage, we assess the performance of the proposed waveform design scheme in terms of detection performance and region of achievable Doppler estimation accuracy.In particular, we analyze the role of the Pareto weight in the optimization process.

Magnetron-based marine radar technology is mature, affordable, reliable, and very effective for maritime safety applications. Commercial systems may be procured at a modest cost as compared to fully coherent solid-state systems. Magnetron oscillators inherently generate random phase signals. Phase instability on a pulse-to-pulse basis impedes this class of marine radars from success in applications requiring coherency such as moving target indication (MTI) or in generating target imagery. This limitation may be overcome by incorporating radio frequency sampling and cross-correlation of the transmit and receive signal technology to augment the current capability of available systems. In this research, the pulse train on transmit and receive is correlated in order to reject interference and detect image targets. Sampling the transmit signal and target echo on receive permits fully coherent processing. Marine radars traditionally operate non-coherently, and as such, offer limited surveillance in clutter rich environments. In this study, the authors report on a non-coherent marine radar that has been modified to produce a pseudo-coherent or coherent-on-receive sensor system. This is crucial to MTI and target image formation. In laboratory experiments, they employed a magnetron oscillator-based system to generate an inverse synthetic aperture radar image. The image was formed using four different algorithms: filtered back-projection (FBP), time domain back-projection (TDBP), an algebraic reconstruction technique, and frequency domain back-projection. In their research, TDBP produces exquisite imagery of steel rods, and it is the standard developed in this study. FBP performed poorly as compared to all other algorithms.

In this paper, we derive Cramer-Rao Lower Bound (CRLB) expressions for two-channel radar target delay-Doppler estimation with unknown transmit waveforms. We have access to these unknown waveforms only via the noisy reference measurements. Further, we assume that the waveform source transmits periodic pulses as is common for most pulsed radar illuminators. Recent CRLB literature for radar has focussed on specific types of illuminators and derived the CRLB assuming these specific transmitted waveforms are known and incorporating them directly into the measurement model. Further, some papers while assuming the waveform itself to be unknown, make simplifying statistical assumptions on the waveforms or the waveform structure. Contrary to this, we compute a more general result that is not restricted to any specific waveform and we also include the noisy reference channel measurements in our derivation of the CRLB to obtain a more accurate performance analysis. The only assumption we make is on the periodicity of the transmit signal, which is true in practice. We demonstrate the CRLB using extensive numerical simulations both in the presence and absence of phase synchronization between the transmitter and receiver.

The effect of foreign portfolio investments on the performance of financial sector in Nigeria was investigated by means of the ex-post facto design. Data of foreign portfolio investments and contribution of financial sector to gross domestic product was obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin and World Bank Development Indicators spanning 1981–2016. Data obtained was analysed using stationarity and unit root, co-integration, ordinary least square estimation, error correction model, and variance decomposition tests. Findings of the study showed that foreign portfolio investments significantly affect the performance of financial sector in Nigeria. On the basis of this, it was recommended the government should strengthen the financial sector, specifically the money and capital markets in order to enhance the flow of foreign portfolio investments into this sector in Nigeria. This is because foreign investors can invest on financial or liquid assets with the hope of a sound future return.

In this study, a forward model for radio frequency tomography (RFT) is improved to remove the effect of strong sidelobes from dominant scatterers in the region of interest. This approach uses a 'suppression algorithm (SA)' to remove the effect of strong sidelobes on weak targets. SA is used to remove the effect of these strong sidelobes using the information from the dyadic contrast function (DCF). DCF is analysed in order to remove the effects of strong sidelobes generated by dominant cells in the measurement domain. The eigenvalues and eigenvectors for dominant cells are obtained to remodel the strong cells as a secondary source in the measurement scene. Furthermore, to simplify the inversion problem in the new forward model, iterative reconstruction algorithms is considered. Subsurface multiplicative algebraic reconstruction technique as additive technique is proposed to solve the new forward model RFT with less computing power and memory. The presented algorithm has been verified using simulated RFT data, generated by the computational electromagnetic software FEKO, for regular and irregular targets scenarios. The proposed research shows that using information from the DCF it is possible to obtain high quality imagery of buried weak targets in RFT.

This paper analyzes the heat spreading capabilities of conventional Mass Via Arrays (MVA). Modelling and simulation are performed for MVAs and are compared to equivalent measurements for Thermal Via Arrays (TVA). Based on this analysis we determine that an MVA with many interspersed heat spreaders provides superior heat spreading when compared to regular TVAs.

In this paper, we introduce a new method to improve the capability of RF tomography to reconstruct an image of weak scatterers when strong scatterers are present in the same measurement domain based on information from Dyadic Contrast Function (DCF) analysis. DCF is developed in order to reconstruct the weak targets close to dominant targets. This approach uses a Suppression Algorithm (SA) to remove the effect of strong sidelobes from dominant scatterers in the measurement domain that lead to failure to reconstruct the image of weaker nearby returns. We represent each dominant cell in the initial reconstructed image as a DCF of three dimensions, and using its eigenvalues and eigenvectors to model the strong cells as a secondary source. Furthermore, Subsurface Multiplicative Algebraic Reconstruction Technique (SMART), and the Iterative Reconstruction Algorithm (IRA), iteratively solve the inversion problem in a set of linear equations modeling the imaging system in RF tomography with rectangular matrices and ill-conditioned operators with less computing power and memory. Simulation results using the computational electromagnetic software FEKO to validate the proposed method are presented.

This paper builds on the ideas presented in [1] and [2] to create a more robust Space-Time Adaptive Processing (STAP) system. Through the use of extensive knowledge bases, circular SAR registration, and expert reasoning, the system has been shown to increase the detection performance in non-homogeneous environments.

Improving target detection and imagery in the presence of metal plates for any scanning device is a very important for two reasons: First, side plates are part of the scanning devices cannot be eliminated. Second, designing side plates using materials that absorb unwanted energy is very complicated and expensive. In this paper, we investigate the effect of metal side plates on a scanning radar operating at high frequency. Our goal is to improve the target image in the presence of these metal side plates. Mathematically, we can reduce the reflected waves from these surfaces and improve the resulting target image if we know the scattering caused by these plates (or at least a part of them).

Detection, localization and reconstruction of images (3D / 2D) of below ground targets based upon RF tomography is a process using multistatic antenna (Transmitters and Receivers) configuration of randomly distributed over the measurement domain. In this paper, an effective method for RF tomography image enhancement is presented. The interference between strong scatterer sidelobes and weak scatterers in the measurement domain, leading to a decrease in the image quality and also can mask the returns from nearby weak targets in Rf Tomography. We propose a faster, more flexible and accurate method to deal with ill-conditioned operators in RF tomography, we decrease the effects of strong sidelobes on targets which increases the potential to reconstruct quality images of buried weak targets using an Iterative Reconstruction Algorithms (IRT), such as Multiplicative Algebraic Reconstruction Techniques (MART). The MART algorithm is an iterative algebraic approach that inverts the linear operator with less computational expense when the operator is ill-conditioned. Suppression, or the clean algorithm is an effective approach to remove the effect of strong sidelobes from dominant scatterers on nearby weak targets in the measurement domain. This algorithm functions by modeling the strong scatterers as extra transmitters in the measurement domain. The sidelobes of these dipoles are subtracted from the collected field to sharpen the quality of the weak targets image. Simulation data using the computational electromagnetic software FEKO are used to validate a inversion scheme, based on an Iterative Reconstruction Algorithms (IRT), such as Multiplicative Algebraic Reconstruction Techniques (MART), and the proposed suppression algorithm.

The use of multicarrier waveforms, such as orthogonal frequency division multiplexing (OFDM) as used in radio communication, is gaining interest within the radar community. This paper considers the optimization of radar performance within the structure imposed by a coded OFDM format required to achieve an acceptable communication link. The dual goal of achieving both satisfactory radar and communication performance raises challenges that can be substantively addressed by combining phase coding and modulation techniques to provide the temporal and spectral structure necessary to implement simultaneous radar and communication operations.

In this paper, we present a Ground Penetrating Radar (GPR) technique currently under development to image a moving object. This GPR system localizes and tracks a moving spherical object that could be in a plastic pipe under the ground for a given bistatic and multi-static radar geometry. Two different approaches (two dyadic Green's functions) are applied to image a moving object using Maxwell's equations, and analyzing the comparison between two dyadic functions is considered. The object is assumed to be inside a region of interest (ROI). Due to the excellent geometric results in [6], the applied GPR system can localize and track a moving object underground by scanning the region of interest in t intervals. During each scan, the GPR system detects and calculates the exact location of the object using a Threshold Technique Method (TTM) based target detection system by analyzing the electromagnetic fields. The 3D FEKO Electromagnetic (EM) simulation software tool is used to model and simulate the GPR system. Simulation results achieve an excellent and accurate performance in the absence of external and unknown disturbances.

Sunday, May 10, 2015 1 pm to 5 pm Title T-Ol-Phased Arrays -Salon FIG T-02 Radar Trans. Design for the Crowded Radio Spectrum -Salon H T-03 Distributed Aperture Radar & RF Tomography­ Salon J T-04 Advanced Detection and CFAR Techniques -Salon 1 T-05 Noise Radar -Salon 2 Monday, May 11, 2015 8 am to 12 pm Title T-06 Ultra Wide Band Surveillance Radar -Salon FIG T-07 Passive Radar -Salon H T-08 Small Target Detection -Salon J T-09 -Electronically Scanned Arrays -Salon 1 T-l0 -Bistatic and Multistatic Radar Imaging -Salon 2 Monday May 11, 2015 1 pm to 5 pm Title T-l1-Radar Waveforms -Salon FIG T-12 -Advanced Radar Detection and Applications­ Salon 1 T-13 -High Res. Sea & Land Clutter Modeling and Analysis -Salon H Instructor(s)

In this paper, we derive Cramer-Rao Lower Bound (CRLB) expressions for two-channel radar target delay-Doppler estimation with unknown transmit waveforms. We have access to these unknown waveforms only via the noisy reference measurements. Further, we assume that the waveform source transmits periodic pulses as is common for most pulsed radar illuminators Recent CRLB literature for radar has focussed on specific types of illuminators and derived the CRLB assuming these specific transmitted waveforms are known and incorporating them directly into the measurement model. Further, some papers while assuming the waveform itself to be unknown, make simplifying statistical assumptions on the waveforms or the waveform structure. Contrary to this, we compute a more general result that is not restricted to any specific waveform and we also include the noisy reference channel measurements in our derivation of the CRLB to obtain a more accurate performance analysis. The only assumption we make is on the periodicity of the transmit signal, which is true in practice.

A novel radio frequency (RF) steganography scheme is proposed to hide digital communication in linear frequency modulation (LFM) radar signals. This joint radar/communication waveform serves two purposes simultaneously: it performs as the original radar waveform, and it provides a covert communication to legitimate receivers. The proposed RF steganography scheme hides digitally modulated communication information inside an LFM radar signal to prevent enemy from detecting the existence of such hidden information via a new modulation and variable symbol duration design.

This paper presents a generalized mathematical model for calculating the temperature of MVAs at specific interface points. This model is formulated using thermal circuit analysis of an n-many layers MVA. We performed numerical calculations and simulations using our model. The results are compared to corresponding COMSOL simulations and the comparison results indicate model accuracy of ±xxx%.

The Frequency Diverse Array (FDA) antenna provides range - angle - time dependent beampattern, potentially generating highly directional beams with high gain that may be steered directly and continuously to the desired position. Therefore, a ground receiving antenna system based on the Frequency Diverse Array antenna is presented for tracking and communicating with Low Earth Orbit (LEO) satellite. This is required to minimize complexity and cost of the ground station. Furthermore,, to meet the system figure of merit (G/T) requirements; the radiation characteristics, the gain requirements, the array size, the minimum number of elements and their distribution for several FDA array antenna architectures are calculated and analyzed.

The goal of this research is to develop a method that allows for processing of bistatic marine radar signals, in order to demonstrate an improvement in target detection (Pd) and false alarm control (Pfa) in systems limited by cross-correlated interference. In this work, a method is presented for coherent processing of signals from a bistatic magnetron oscillator based marine radar. The feasibility of this approach was previously demonstrated for a monostatic radar through a hardware modification that allowed for capture of data via a Xilinx ADC and processing in FPGAs. It is demonstrated here that operating two of radars in this manner and combining their resulting signals allows for an improvement in overall detection and track. Our approach works by sampling the transmitted and received signals at each radar. Cross-correlations between all four combinations of transmitted and received signals are used to demonstrate the limits due to mutual interference in a bistatic/multistatic system of radars. This processing is successfully demonstrated in software, showing the potential for coherency between two marine radars. In general, bistatic coherent radars are very expensive, and this work provides a method for achieving the equivalent coherent performance using a two modified non-coherent radar systems.

Non-coherent marine radar technology has matured over the past several decades. Researchers have developed coherent magnetron oscillator based marine radars by sampling the signals on transmit and receive [1]. We leverage this research to contribute to the science and technology of RF Tomography based upon exploitation of marine radar technology, and digital sampling / signal processing techniques. This requires many steps. First, selecting and modifying an affordable yet suitable marine radar. In this case, we employed a Furuno DRS25A. Second, by embedding an RF sampling circuit, we captured the various radar waveforms. Third, we digitized transmit and receive signals using a Signatec model PX1500 analog-to-digital converter (ADC). Next, we designed an experimental geometry to support image formation via RF Tomography. We applied Filtered Back Projection based upon the Projection-Slice Theorem, the Algebraic Reconstruction Technique, and classical Inverse Synthetic Aperture Radar imaging algorithms in order to match filter data and image targets. We provide both simulation analysis and experimental results in this paper.

In this study the authors introduce a novel method for passive source localisation that exploits phase variance. This method performs phase detection and estimation without relying on precise antenna geometry. The method uses a network of coherent receivers to estimate a continuous wave transmitter source in a two-dimensional plane with a network of statically and arbitrarily placed receivers with known positions. First the authors develop the mathematical formulation of the method. Next they establish the relationship between knowledge of the transmitter phase at arbitrarily placed receiver locations and a countable number of ambiguous transmitter locations. The authors then develop a more realistic scenario involving multi-path, noise and other signals in the receiver bandwidth and present numerical results for three different geometries. Finally, the authors compare the numerical results with those achieved with traditional phase difference of arrival.