SuperDARN parameter estimation optimization and implementation of new techniques

Thesis (M.S.) University of Alaska Fairbanks, 2013The Super Dual Auroral Radar Network (SuperDARN) is an international radar network to study the ionosphere and upper atmosphere. The primary target of SuperDARN is field-aligned plasma irregularities in the E- and F-region of the ionosphere. To quantify the characteristics of these irregularities, the radar measures power, Doppler velocity, and spectral width from auto-correlation functions of the received samples. Since the target of interest is overspread, the derived parameters suffer from errors related to cross-range interference. In this thesis, we propose two scenarios to address this problem. First, we implement new approaches to avoid the cross-range interference, and second, we develop new optimization techniques that are more robust and less sensitive in dealing with this interference. New methods include filtering techniques, spectral analysis, and use of inverse techniques. The filtering methods (mismatched and adaptive) offer improvement in both suppressing the side lobes associated with pulse compression techniques and optimal estimation of the main lobe signal-to-noise ratio. Spectral analysis, extracts multiple Doppler velocities in the range while the current time-domain analysis is only capable of measuring one. Instead of dealing with ambiguities, inverse theory applied to SuperDARN received samples can potentially remove the associated cross-range interference, which results in more detailed and accurate information in obtaining the structure and dynamics of the irregularities. More accurate and detailed empirical models resulting from new optimization methods give more information that can be mapped over the current in-progress theoretical models, which finally results in better understanding the physics of the ionosphere

WAVEFORM AND TRANSCEIVER OPTIMIZATION FOR MULTI-FUNCTIONAL AIRBORNE RADAR THROUGH ADAPTIVE PROCESSING

Pulse compression techniques have been widely used for target detection and remote sensing. The primary concern for pulse compression is the sidelobe interference. Waveform design is an important method to improve the sidelobe performance. As a multi-functional aircraft platform in aviation safety domain, ADS-B system performs functions involving detection, localization and alerting of external traffic. In this work, a binary phase modulation is introduced to convert the original 1090 MHz ADS-B signal waveform into a radar signal. Both the statistical and deterministic models of new waveform are developed and analyzed. The waveform characterization, optimization and its application are studied in details. An alternative way to achieve low sidelobe levels without trading o range resolution and SNR is the adaptive pulse compression - RMMSE (Reiterative Minimum Mean-Square error). Theoretically, RMMSE is able to suppress the sidelobe level down to the receiver noise floor. However, the application of RMMSE to actual radars and the related implementation issues have not been investigated before. In this work, implementation aspects of RMMSE such as waveform sensitivity, noise immunity and computational complexity are addressed. Results generated by applying RMMSE to both simulated and measured radar data are presented and analyzed. Furthermore, a two-dimensional RMMSE algorithm is derived to mitigate the sidelobe effects from both pulse compression processing and antenna radiation pattern. In addition, to achieve even better control of the sidelobe level, a joint transmit and receive optimization scheme (JTRO) is proposed, which reduces the impacts of HPA nonlinearity and receiver distortion. Experiment results obtained with a Ku-band spaceborne radar transceiver testbed are presented

Development and application of spread-spectrum ultrasonic evaluation technique

A new approach to ultrasonic NDE called spread-spectrum ultrasonic evaluation (SSUE) is investigated. It regards the ultrasonic nondestructive evaluation as an acoustic-impulse-response estimation and characterization problem. This problem has been compared with the analogous problems of radio-detection-and-ranging from communications field and the seismic exploration problem of geophysics. Out of the various options for the impulse response estimation, the continuous pseudorandom signal correlation method has been shown to be the optimum for peak-power limited systems such as the ultrasonic NDE systems. The problem of self-noise and its consequences in pseudorandom correlation systems is investigated, followed by the development of various optimum and sub-optimum approaches to self-noise elimination. After verifying the theoretical results through computer simulations, a lab-grade SSUE instrument was developed and analyzed. Also, a new, efficient method for the implementation of DSP-based correlator is developed. The application of SSUE technique to various practical NDE situations like, flaw detection, velocity/thickness measurements, attenuation measurement, global integrity assessment, etc., was investigated through various laboratory experiments. It is concluded that the SSUE technique holds great promise for all ultrasonic NDE applications where high signal attenuation results into the loss of signal-to-noise ratios beyond workable limits;SSUE employs a non-traditional approach to ultrasonic NDE that makes it more robust and powerful. One significant feature of the SSUE technique is that it overcomes the maximum average power limitation of the existing techniques. Conventional pulsed ultrasonic NDE systems are peak power limited by the transducer breakdown voltage and the average power is limited by the narrow pulse duration which is important to maintain good resolution. In certain NDE applications there are factors other than the transducer peak power limitation, which limit the amplitude of the transmitted signal. In case of medical ultrasound devices, for example, the peak power limit arises from the risk of causing tissue damage. For such kind of applications, SSUE has a direct solution to increasing the average power while maintaining the resolution. Ultrasonic NDE instrument in a field or industrial environment is subject to all kinds of acoustic and electromagnetic interferences. This results into a degradation of instrument sensitivity and reliability. SSUE technique, by virtue of its robust operating principal, is capable of interference rejection to a much larger extent

Space-time adaptive processing techniques for multichannel mobile passive radar

Passive radar technology has reached a level of maturity for stationary sensor operations, widely proving the ability to detect, localize and track targets, by exploiting different kinds of illuminators of opportunity. In recent years, a renewed interest from both the scientific community and the industry has opened new perspectives and research areas. One of the most interesting and challenging ones is the use of passive radar sensors onboard moving platforms. This may offer a number of strategic advantages and extend the functionalities of passive radar to applications like synthetic aperture radar (SAR) imaging and ground moving target indication (GMTI). However, these benefits are paid in terms of motion-induced Doppler distortions of the received signals, which can adversely affect the system performance. In the case of surveillance applications, the detection of slowly moving targets is hindered by the Doppler-spread clutter returns, due to platform motion, and requires the use of space-time processing techniques, applied on signals collected by multiple receiving channels. Although in recent technical literature the feasibility of this concept has been preliminarily demonstrated, mobile passive radar is still far from being a mature technology and several issues still need to be addressed, mostly connected to the peculiar characteristics of the passive bistatic scenario. Specifically, significant limitations may come from the continuous and time-varying nature of the typical waveforms of opportunity, not suitable for conventional space-time processing techniques. Moreover, the low directivity of the practical receiving antennas, paired with a bistatic omni-directional illumination, further increases the clutter Doppler bandwidth and results in the simultaneous reception of non-negligible clutter contributions from a very wide angular sector. Such contributions are likely to undergo an angle-dependent imbalance across the receiving channels, exacerbated by the use of low-cost hardware. This thesis takes research on mobile passive radar for surveillance applications one step further, finding solutions to tackle the main limitations deriving from the passive bistatic framework, while preserving the paradigm of a simple system architecture. Attention is devoted to the development of signal processing algorithms and operational strategies for multichannel mobile passive radar, focusing on space-time processing techniques aimed at clutter cancellation and slowly moving target detection and localization. First, a processing scheme based on the displaced phase centre antenna (DPCA) approach is considered, for dual-channel systems. The scheme offers a simple and effective solution for passive radar GMTI, but its cancellation performance can be severely compromised by the presence of angle-dependent imbalances affecting the receiving channels. Therefore, it is paired with adaptive clutter-based calibration techniques, specifically devised for mobile passive radar. By exploiting the fine Doppler resolution offered by the typical long integration times and the one-to-one relationship between angle of arrival and Doppler frequency of the stationary scatterers, the devised techniques compensate for the angle-dependent imbalances and prove largely necessary to guarantee an effective clutter cancellation. Then, the attention is focused on space-time adaptive processing (STAP) techniques for multichannel mobile passive radar. In this case, the clutter cancellation capability relies on the adaptivity of the space-time filter, by resorting to an adjacent-bin post-Doppler (ABPD) approach. This allows to significantly reduce the size of the adaptive problem and intrinsically compensate for potential angle-dependent channel errors, by operating on a clutter subspace accounting for a limited angular sector. Therefore, ad hoc strategies are devised to counteract the effects of channel imbalance on the moving target detection and localization performance. By exploiting the clutter echoes to correct the spatial steering vector mismatch, the proposed STAP scheme is shown to enable an accurate estimation of target direction of arrival (DOA), which represents a critical task in system featuring few wide beam antennas. Finally, a dual cancelled channel STAP scheme is proposed, aimed at further reducing the system computational complexity and the number of required training data, compared to a conventional full-array solution. The proposed scheme simplifies the DOA estimation process and proves to be robust against the adaptivity losses commonly arising in a real bistatic clutter scenario, allowing effective operation even in the case of a limited sample support. The effectiveness of the techniques proposed in this work is validated by means of extensive simulated analyses and applications to real data, collected by an experimental multichannel passive radar installed on a moving platform and based on DVB-T transmission

Mismatched Processing for Radar Interference Cancellation

Matched processing is a fundamental filtering operation within radar signal processing to estimate scattering in the radar scene based on the transmit signal. Although matched processing maximizes the signal-to-noise ratio (SNR), the filtering operation is ineffective when interference is captured in the receive measurement. Adaptive interference mitigation combined with matched processing has proven to mitigate interference and estimate the radar scene. A known caveat of matched processing is the resulting sidelobes that may mask other scatterers. The sidelobes can be efficiently addressed by windowing but this approach also comes with limited suppression capabilities, loss in resolution, and loss in SNR. The recent emergence of mismatch processing has shown to optimally reduce sidelobes while maintaining nominal resolution and signal estimation performance. Throughout this work, re-iterative minimum-mean square error (RMMSE) adaptive and least-squares (LS) optimal mismatch processing are proposed for enhanced signal estimation in unison with adaptive interference mitigation for various radar applications including random pulse repetition interval (PRI) staggering pulse-Doppler radar, airborne ground moving target indication, and radar & communication spectrum sharing. Mismatch processing and adaptive interference cancellation each can be computationally complex for practical implementation. Sub-optimal RMMSE and LS approaches are also introduced to address computational limitations. The efficacy of these algorithms is presented using various high-fidelity Monte Carlo simulations and open-air experimental datasets

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

Breaking the Practical Performance Barriers of Polarimetric Phased Array Weather Radars

Phased array radars (PAR) are being proposed as an alternative to replacing the Next Generation Weather Radar (NEXRAD) network, which has been in service for more than 30 years, reaching the end of its life cycle. The PAR can improve the temporal resolution of weather coverage compared to reflector antennas (currently implemented on NEXRAD). Temporal resolution is crucial for severe weather detection and surveillance, especially rapid-evolving phenomena such as tornadoes and hail storms. An all-digital PAR design is presently being explored based on their performance and flexibility improvement. Nevertheless, even all-digital PARs are not free from limitations. This work proposes two signal processing solutions to mitigate two significant limitations observed in those radar systems, i.e., blind range resulted from pulse compression technique and cross-polar contamination inherent in the patch antenna implementation, which is currently the only viable solution to an all-digital PAR system. The mitigation techniques to these two limitations are called Progressive Pulse Compression and Cross-Polar Canceler, respectively. The Progressive Pulse Compression (PPC) technique is proposed to mitigate the blind range problem observed in radars using a frequency modulated waveform and pulse compression. The blind range is caused by the strong leak-through coupled into the receive chain during the transmission cycle. The PPC technique is based on partial decoding. It uses a portion of the uncontaminated received signal in conjunction with pulse compression to estimate the target characteristics from the incomplete signal. The technique does not require using a fill pulse or any hardware modifications. The PPC technique can be divided into three steps. First is to apply a smooth taper to discard all the contaminated samples in the received signal that corresponds to the transmission cycle. The second step is to perform pulse compression using the so called matched filter. Finally, the third step is to calculate and apply a calibration factor to compensate for the progressively changing return signal (affected by the tapering) to recover the proper reflectivity values. This technique is implemented on the PX-1000 radar. In the near future, PPC will be implemented on the Horus phased array radar system. The PX-1000 and Horus radar systems have been designed by the Advanced Radar Research Center (ARRC) at the University of Oklahoma (OU). Nevertheless, PPC has some limitations caused by the different frequency content between the modified (tapered) return signal and the matched filter used for compression. This difference causes a shift in the mainlobe peak and an asymmetrical increase in the sidelobe levels producing a “shoulder” effect. This work proposes improving PPC by compressing the modified return signal with amplitude-modulated versions (range dependent) of the original matched filter. The improved PPC is termed PPC+ and is planned as a software update from PPC. The PPC+ has been tested using data from the PX-1000 and will be presented in this dissertation. The Cross-Polar Canceler (XPC) technique is proposed to mitigate the cross-polar contamination observed on phased array radars. The cross-polar contamination is especially problematic when steering the beam away from the broadside. It is defined as a leakage from the intended polarization observed in the perpendicular one. In the XPC technique, the elements on the array are divided into two groups: main elements and canceler elements. The main elements transmit without any modification. However, the canceler elements transmit a modulated version of the inverse (i.e., the mathematical negative) of the original waveform in the perpendicular polarization. After integration, the field radiated by the canceler elements cancels the cross-polar contamination produced by the main ones. The XPC technique involves calculating the correct number of canceler elements, their location in the array, and the complex scaling factor that better mitigates the cross-polar contamination. This technique has been designed for polarimetric radars transmitting in simultaneous transmission and simultaneous reception of H/V polarization (STSR). The XPC technique will be implemented on the Horus radar system, currently under development. For polarimetric radars, the difference in the element patterns on each polarization produces an angular mismatch between the peaks on the H and V array patterns. This angular mismatch affects the maximum performance achievable with the XPC. Calibration is included as part of XPC to mitigate this effect. Iterative calibration is necessary in the XPC technique. Additionally, calibration is performed before and after XPC is implemented on an operational PAR system. This enhanced version of XPC (including calibration) is termed improved XPC. Like the XPC, the improved XPC is intended to be implemented on the Horus radar system

Frequency Diverse Array Radar: Signal Characterization and Measurement Accuracy

Radar systems provide an important remote sensing capability, and are crucial to the layered sensing vision; a concept of operation that aims to apply the right number of the right types of sensors, in the right places, at the right times for superior battle space situational awareness. The layered sensing vision poses a range of technical challenges, including radar, that are yet to be addressed. To address the radar-specific design challenges, the research community responded with waveform diversity; a relatively new field of study which aims reduce the cost of remote sensing while improving performance. Early work suggests that the frequency diverse array radar may be able to perform several remote sensing missions simultaneously without sacrificing performance. With few techniques available for modeling and characterizing the frequency diverse array, this research aims to specify, validate and characterize a waveform diverse signal model that can be used to model a variety of traditional and contemporary radar configurations, including frequency diverse array radars. To meet the aim of the research, a generalized radar array signal model is specified. A representative hardware system is built to generate the arbitrary radar signals, then the measured and simulated signals are compared to validate the model. Using the generalized model, expressions for the average transmit signal power, angular resolution, and the ambiguity function are also derived. The range, velocity and direction-of-arrival measurement accuracies for a set of signal configurations are evaluated to determine whether the configuration improves fundamental measurement accuracy