Discrete Frequency and Phase Coding Waveform for MIMO Radar

In multi-input multi-output (MIMO) radar system, good orthogonality between transmitting waveforms will fairly simplify the signal processing, along with improve the targets detection as well as the parameters estimation performance of the system. In this paper, a discrete frequency and phase coding waveform (DFPCW), which attains good orthogonality by varying the carrier frequency and initial phase of each pulse in the pulse train, is designed. The theoretical derivations of ambiguity function (AF) and cross ambiguity function (CAF) of the DFPCW are also given. After then, a generic algorithm (GA) is applied by optimizing the carrier frequency code sequence and initial phase code sequence to minimize both the auto-correlation sidelobe peaks (ASP) and cross-correlation peaks (CP) of the waveforms. The simulation results demonstrate that DFPCW has better orthogonality and sidelobe property compared with the traditional discrete frequency coding waveform and widely employed frequency modulated continuous wave (FMCW), henceforth this new waveform may become to an alternative option for MIMO radar

Multibeam radar system based on waveform diversity for RF seeker applications

Existing radiofrequency (RF) seekers use mechanically steerable antennas. In order to improve the robustness and performance of the missile seeker, current research is investigating the replacement of mechanical 2D antennas with active electronically controlled 3D antenna arrays capable of steering much faster and more accurately than existing solutions. 3D antenna arrays provide increased radar coverage, as a result of the conformal shape and flexible beam steering in all directions. Therefore, additional degrees of freedom can be exploited to develop a multifunctional seeker, a very sophisticated sensor that can perform multiple simultaneous tasks and meet spectral allocation requirements. This thesis presents a novel radar configuration, named multibeam radar (MBR), to generate multiple beams in transmission by means of waveform diversity. MBR systems based on waveform diversity require a set of orthogonal waveforms in order to generate multiple channels in transmission and extract them efficiently at the receiver with digital signal processing. The advantage is that MBR transmit differently designed waveforms in arbitrary directions so that waveforms can be selected to provide multiple radar functions and better manage the available resources. An analytical model of an MBR is derived to analyse the relationship between individual channels and their performance in terms of isolation and phase steering effects. Combinations of linear frequency modulated (LFM) waveforms are investigated and the analytical expressions of the isolation between adjacent channels are presented for rectangular and Gaussian amplitude modulated LFM signals with different bandwidths, slopes and frequency offsets. The theoretical results have been tested experimentally to corroborate the isolation properties of the proposed waveforms. In addition, the practical feasibility of the MBR concept has been proved with a radar test bed with two orthogonal channels simultaneously detecting a moving target

Digital Predistortion of Pseudo-Orthogonal Wideband Waveforms for Dual-Polarimetric Phased Array Radars

Many new and interesting radar operational modes and techniques are being explored to maximize the efficiency and utility of next-generation radar systems while complying with increasingly stringent operational and budgeting requirements. This dissertation's aim is to analyze and present possible techniques to help maximize the scientific value of measurements while complying with operational requirements through methods of physical transmission and exciting the target area, methods of processing the received waveforms, and methods of designing waveforms for a given system. In regard to methods of physical transmission and exciting the target area, this dissertation addresses unique problems that will be faced by next-generation radar systems utilizing simultaneous transmit and simultaneous receive operational modes in polarimetric active phased array architectures. This is accomplished through establishing mathematical representations of the received complex baseband waveforms for dual-polarimetric radar operation and analyzing the predicted behavior versus traditional polarimetric radar alternating transmit and simultaneous receive operation. In regard to methods of processing the received waveforms, pulse compression will undoubtedly be widely utilized in future radar systems due to the increase in range resolution that it provides for a given pulse length. Additionally, matched filtering allows the realization of simultaneously transmitted pseudo-orthogonal waveforms occupying the same spectral region that would be otherwise impossible. As a result, the mathematical basis of pulse compression is provided, and pulse compression effects are taken into account in all relevant system analyses in this manuscript. This dissertation arguably provides the most attention in regard to methods for designing and modifying waveforms for application in a given system. An analysis of common pulse compression waveforms for suitability in pseudo-orthogonal waveform sets is provided in addition to a novel method for designing polyphase coded waveform and non-linear frequency modulated waveform based pseudo-orthogonal waveform sets utilizing particle swarm optimization. Additionally, for the first time, research is presented on the full design and application methods for digital predistortion of wideband solid state radar amplifiers. Digital predistortion methods and results are presented for both the impedance matched high power amplifier case and for the varying load impedance case that can be expected to be encountered in radar systems utilizing electronic beamsteering in active phased array architectures. Overall, this dissertation's aim is to provide relevant results from conducted research in the form of analysis and novel design methods that can be applied in both the design and operation of next-generation radar systems to maximize utility and scientific data quality while operating within given system and environmental specifications

Adaptive OFDM Radar for Target Detection and Tracking

We develop algorithms to detect and track targets by employing a wideband orthogonal frequency division multiplexing: OFDM) radar signal. The frequency diversity of the OFDM signal improves the sensing performance since the scattering centers of a target resonate variably at different frequencies. In addition, being a wideband signal, OFDM improves the range resolution and provides spectral efficiency. We first design the spectrum of the OFDM signal to improve the radar\u27s wideband ambiguity function. Our designed waveform enhances the range resolution and motivates us to use adaptive OFDM waveform in specific problems, such as the detection and tracking of targets. We develop methods for detecting a moving target in the presence of multipath, which exist, for example, in urban environments. We exploit the multipath reflections by utilizing different Doppler shifts. We analytically evaluate the asymptotic performance of the detector and adaptively design the OFDM waveform, by maximizing the noncentrality-parameter expression, to further improve the detection performance. Next, we transform the detection problem into the task of a sparse-signal estimation by making use of the sparsity of multiple paths. We propose an efficient sparse-recovery algorithm by employing a collection of multiple small Dantzig selectors, and analytically compute the reconstruction performance in terms of the $ell_1$-constrained minimal singular value. We solve a constrained multi-objective optimization algorithm to design the OFDM waveform and infer that the resultant signal-energy distribution is in proportion to the distribution of the target energy across different subcarriers. Then, we develop tracking methods for both a single and multiple targets. We propose an tracking method for a low-grazing angle target by realistically modeling different physical and statistical effects, such as the meteorological conditions in the troposphere, curved surface of the earth, and roughness of the sea-surface. To further enhance the tracking performance, we integrate a maximum mutual information based waveform design technique into the tracker. To track multiple targets, we exploit the inherent sparsity on the delay-Doppler plane to develop an computationally efficient procedure. For computational efficiency, we use more prior information to dynamically partition a small portion of the delay-Doppler plane. We utilize the block-sparsity property to propose a block version of the CoSaMP algorithm in the tracking filter

Beyond the spatio-temporal limits of atmospheric radars: inverse problem techniques and MIMO systems

The Earth’s upper atmosphere (UA) is a highly dynamic region dominated by atmospheric waves and stratified turbulence covering a wide range of spatio-temporal scales. A comprehensive study of the UA requires measurements over a broad range of frequencies and spatial wavelengths, which are prohibitively costly. To improve the understanding of the UA, an investment in efficient and large observational infrastructures is required. This work investigates remote sensing techniques based on MIMO and inverse problems techniques to improve the capabilities of current atmospheric radars

Multistatic radar optimization for radar sensor network applications

The design of radar sensor networks (RSN) has undergone great advancements in recent years. In fact, this kind of system is characterized by a high degree of design flexibility due to the multiplicity of radar nodes and data fusion approaches. This thesis focuses on the development and analysis of RSN architectures to optimize target detection and positioning performances. A special focus is placed upon distributed (statistical) multiple-input multipleoutput (MIMO) RSN systems, where spatial diversity could be leveraged to enhance radar target detection capabilities. In the first part of this thesis, the spatial diversity is leveraged in conjunction with cognitive waveform selection and design techniques to quickly adapt to target scene variations in real time. In the second part, we investigate the impact of RSN geometry, particularly the placement of multistatic radar receivers, on target positioning accuracy. We develop a framework based on cognitive waveform selection in conjunction with adaptive receiver placement strategy to cope with time-varying target scattering characteristics and clutter distribution parameters in the dynamic radar scene. The proposed approach yields better target detection performance and positioning accuracy as compared with conventional methods based on static transmission or stationary multistatic radar topology. The third part of this thesis examines joint radar and communication systems coexistence and operation via two possible architectures. In the first one, several communication nodes in a network operate separately in frequency. Each node leverages the multi-look diversity of the distributed system by activating radar processing on multiple received bistatic streams at each node level in addition to the pre-existing monostatic processing. This architecture is based on the fact that the communication signal, such as the Orthogonal Frequency Division Multiplexing (OFDM) waveform, could be well-suited for radar tasks if the proper waveform parameters are chosen so as to simultaneously perform communication and radar tasks. The advantage of using a joint waveform for both applications is a permanent availability of radar and communication functions via a better use of the occupied spectrum inside the same joint hardware platform. We then examine the second main architecture, which is more complex and deals with separate radar and communication entities with a partial or total spectrum sharing constraint. We investigate the optimum placement of radar receivers for better target positioning accuracy while reducing the radar measurement errors by minimizing the interference caused by simultaneous operation of the communication system. Better performance in terms of communication interference handling and suppression at the radar level, were obtained with the proposed placement approach of radar receivers compared to the geometric dilution of precision (GDOP)-only minimization metric