53 research outputs found

    New Approaches to Pulse Compression Techniques of Phase-Coded Waveforms in Radar

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    The present thesis aims to make an in-depth study of Radar pulse compression, Neural Networks and Phase coded pulse compression codes. Pulse compression is a method which combines the high energy of a longer pulse width with the high resolution of a narrow pulse width. The major aspects that are considered for a pulse compression technique are signal to sidelobe ratio (SSR) performance, noise performance and Doppler shift performance. Matched filtering of biphase coded radar signals create unwanted sidelobes which may mask important information. The adaptive filtering techniques like Least Mean Square (LMS), Recursive Least Squares (RLS), and modified RLS algorithms are used for pulse radar detection and the results are compared. In this thesis, a novel approach for pulse compression using Recurrent Neural Network (RNN) is proposed. The 13-bit and 35-bit barker codes are used as signal codes to RNN and results are compared with Multilayer Perceptron (MLP) network. RNN yields better signal-to-sidelobe ratio (SSR), error convergence speed, noise performance, range resolution ability and Doppler shift performance than neural network (NN) and some traditional algorithms like auto correlation function(ACF) algorithm. But the SSR obtained from RNN is less for most of the applications. Hence a Radial Basis Function (RBF) neural network is implemented which yields better convergence speed, higher SSRs in adverse situations of noise and better robustness in Doppler shift tolerance than MLP and ACF algorithm. There is a scope of further improvement in performance in terms of SSR, error convergence speed, and Doppler shift. A novel approach using Recurrent RBF is proposed for pulse radar detection, and the results are compared with RBF, MLP and ACF. Biphase codes, namely barker codes are used as inputs to all these neural networks. The disadvantages of biphase codes include high sidelobes and poor Doppler tolerance. The Golay complementary codes have zero sidelobes but they are poor Doppler tolerant as that of biphase codes. The polyphase codes have low sidelobes and are more Doppler tolerant than biphase codes. The polyphase codes namely Frank, P1, P2, P3, P4 codes are described in detail and autocorrelation outputs, phase values and their Doppler properties are discussed and compared. The sidelobe reduction techniques such as single Two Sample Sliding Window Adder (TSSWA) and double TSSWA after the autocorrelator output are discussed and their performances for P4 code are presented and compared. Weighting techniques can also be applied to substantially reduce the range time sidelobes. The weighting functions such as Kaiser-Bessel amplitude weighting function and classical amplitude weighting functions (i.e. Hamming window) are described and are applied to the receiver waveform of 100 element P4 code and the autocorrelation outputs, Peak Sidelobe Level (PSL), Integrated Sidelobe Level (ISL) values are compared with that of rectangular window. The effects of weighting on the Doppler performance of the P4 code are presented and compared

    Development of Radar Pulse Compression Techniques Using Computational Intelligence Tools

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    Pulse compression techniques are used in radar systems to avail the benefits of large range detection capability of long duration pulse and high range resolution capability of short duration pulse. In these techniques a long duration pulse is used which is either phase or frequency modulated before transmission and the received signal is passed through a filter to accumulate the energy into a short pulse. Usually, a matched filter is used for pulse compression to achieve high signal-to-noise ratio (SNR). However, the matched filter output i.e. autocorrelation function (ACF) of a modulated signal is associated with range sidelobes along with the mainlobe. These sidelobes are unwanted outputs from the pulse compression filter and may mask a weaker target which is present nearer to a stronger target. Hence, these sidelobes affect the performance of the radar detection system. In this thesis, few investigations have been made to reduce the range sidelobes using computational intelligence techniques so as to improve the performance of radar detection system. In phase coded signals a long pulse is divided into a number of sub pulses each of which is assigned with a phase value. The phase assignment should be such that the ACF of the phase coded signal attain lower sidelobes. A multiobjective evolutionary approach is proposed to assign the phase values in the biphase code so as to achieve low sidelobes. Basically, for a particular length of code mismatch filter is preferred over matched filter to get better peak to sidelobe ratio (PSR). Recurrent neural network (RNN) and recurrent radial basis function (RRBF) structures are proposed as mismatch filters to achieve better PSR values under various noise conditions, Doppler shift and multiple target environment

    Design and Optimization of Physical Waveform-Diverse and Spatially-Diverse Radar Emissions

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    With the advancement of arbitrary waveform generation techniques, new radar transmission modes can be designed via precise control of the waveform's time-domain signal structure. The finer degree of emission control for a waveform (or multiple waveforms via a digital array) presents an opportunity to reduce ambiguities in the estimation of parameters within the radar backscatter. While this freedom opens the door to new emission capabilities, one must still consider the practical attributes for radar waveform design. Constraints such as constant amplitude (to maintain sufficient power efficiency) and continuous phase (for spectral containment) are still considered prerequisites for high-powered radar waveforms. These criteria are also applicable to the design of multiple waveforms emitted from an antenna array in a multiple-input multiple-output (MIMO) mode. In this work, three spatially-diverse radar emission design methods are introduced that provide constant amplitude, spectrally-contained waveforms implemented via a digital array radar (DAR). The first design method, denoted as spatial modulation, designs the radar waveforms via a polyphase-coded frequency-modulated (PCFM) framework to steer the coherent mainbeam of the emission within a pulse. The second design method is an iterative scheme to generate waveforms that achieve a desired wideband and/or widebeam radar emission. However, a wideband and widebeam emission can place a portion of the emitted energy into what is known as the `invisible' space of the array, which is related to the storage of reactive power that can damage a radar transmitter. The proposed design method purposefully avoids this space and a quantity denoted as the Fractional Reactive Power (FRP) is defined to assess the quality of the result. The third design method produces simultaneous radar and communications beams in separate spatial directions while maintaining constant modulus by leveraging the orthogonal complement of the emitted directions. This orthogonal energy defines a trade-space between power efficiency gained from constraining waveforms to be constant amplitude and power efficiency lost by emitting energy in undesired directions. The design of FM waveforms via traditional gradient-based optimization methods is also considered. A waveform model is proposed that is a generalization of the PCFM implementation, denoted as coded-FM (CFM), which defines the phase of the waveform via a summation of weighted, predefined basis functions. Therefore, gradient-based methods can be used to minimize a given cost function with respect to a finite set of optimizable parameters. A generalized integrated sidelobe level (GISL) metric is used as the optimization cost function to minimize the correlation range sidelobes of the radar waveform. System specific waveform optimization is explored by incorporating the linear models of three different loopback configurations into the GISL metric to match the optimized waveforms to the particular systems

    Addressing Spectrum Congestion by Spectrally-Cooperative Radar design

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    This dissertation attempts to address a significant challenge that is encountered by the users of the Radio Frequency (RF) Spectrum in recent years. The challenge arises due to the need for greater RF spectrum by wireless communication industries such as mobile telephony, cable/satellite and wireless internet as a result of growing con-sumer base and demands. As such, it has led to the issue of spectrum congestion as radar systems have traditionally maintain the largest share of the RF spectrum. To resolve the spectrum congestion problem, it has become even necessary for users from both radar and communication systems to coexist within a finite spectrum allocation. However, this then leads to other problems such as the increased likelihood of mutual interference experienced by all systems that are coexisting within the finite spectrum.. In order to address this challenge, the dissertation will seek to resolve it via a two-step approach that are described as follows. For the first step of this approach, it will present a structured and meticulous approach to design a sparse spectrum allocation optimization scheme that will lead to the release of valuable spectrum previously allocated to radar applications for reallocation to other players such as the wireless video-on-demand and telecommunication industries while maintaining the range resolution performance of these radar applications. This sparse bandwidth allocation scheme is implemented using an optimization process utilizing the Marginal Fisher information (MFI) measure as the main metric for optimization. Although the MFI approach belongs to the class of greedy optimization methods that cannot guarantee global convergence, the results obtained indicated that this approach is able to produce a locally optimal solution. For the second step of this approach, it will present on the design of a spectral efficient waveform that can be used to ensure that the allocated spectrum limits will not be violated due to poor spectral emission containment. The design concept of this waveform is based on the joint implementation of the first and higher orders of the Poly-phase coded Frequency Modulated (PCFM) waveform that expands previous research on first order PCFM waveform. As any waveform generated using the PCFM framework possesses good spectral containment and is amenable to high power transmit operations such as radar due to its constant modulus property, thus the combined-orders of PCFM waveform is a very suitable candidate that can be used in conjunction with the sparse bandwidth allocation scheme in the first step for any radar application such that the waveform will further mitigate the issue of interference experienced by other users coexisting within the same band

    Optimisation des formes d'ondes d'un radar d'aide à la conduite automobile, robustes vis-à-vis d'environnements électromagnétiques dégradés

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    Several driver assistance radars are developed for security and comfort requirements. Their goal is among others to detect the presence of obstacles for collision avoidance. The current demand in terms of automotive radar sensors experience a significant growth and the technologies being employed must ensure good performances especially in an environment degraded by interfering signals of other users. In this thesis, we are interested in developing a radar system which is effective in all situations especially in a multi-user context. For this purpose, we propose novel radar waveforms based on the combination of frequency hopping Costas codes and other pulse compression techniques, using modified Costas signals. The design approach allows to synthesize a significant number of waveforms, thanks to the high diversity introduced. Afterwards, we have exploited two estimation of target parameters approaches. The first one, quite classic, is based on Doppler processing in a coherent pulse train. The second one, recent in the automotive field , is based on the Compressed sensing techniques. An adaptation of these algorithms to proposed signals is discussed in noisy and multi-target environments. All these works contribute in one hand to explore novel radar waveforms, complement to those currently used in automotive radars and in another hand to propose an innovative processing at the receiver level, suited to radar applications in general and automotive ones in particular.Divers radars sont développés pour des besoins d’aide à la conduite automobile de sécurité mais aussi de confort. Ils ont pour but de détecter la présence d’obstacles routiers afin d’éviter d’éventuelles collisions. La demande actuelle en termes de capteurs radars pour l’automobile connaît une croissance importante et les technologies employées doivent garantir de bonnes performances dans un environnement dégradé par les signaux interférents des autres utilisateurs. Dans cette thèse, nous nous intéressons au développement d’un système radar performant en tout lieu et en particulier dans un contexte multi-utilisateurs. A ce propos, nous proposons de nouvelles formes d’ondes qui se basent sur la combinaison des codes fréquentiels de Costas et d’autres techniques de compression d’impulsion en exploitant les signaux de Costas modifiés. La conception adoptée permet, grâce à la diversité introduite, de synthétiser un nombre important de formes d’ondes. Nous avons, ensuite, exploité deux approches d’estimation des paramètres des cibles. La première, plutôt classique, se base sur le traitement Doppler dans un train d’impulsions cohérent. La deuxième, récente dans le domaine automobile, se base sur la technique dite de « Compressed Sensing ». Une adaptation de ces algorithmes pour les signaux proposés a été discutée dans des environnements bruités et multi-cibles. L’ensemble de ces travaux contribue à explorer de nouvelles formes d’ondes, autres que celles utilisées dans les radars actuels et à proposer un traitement innovant en réception, adapté aux radars en général et à l’automobile en particulier

    Adaptive equalisation for fading digital communication channels

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    This thesis considers the design of new adaptive equalisers for fading digital communication channels. The role of equalisation is discussed in the context of the functions of a digital radio communication system and both conventional and more recent novel equaliser designs are described. The application of recurrent neural networks to the problem of equalisation is developed from a theoretical study of a single node structure to the design of multinode structures. These neural networks are shown to cancel intersymbol interference in a manner mimicking conventional techniques and simulations demonstrate their sensitivity to symbol estimation errors. In addition the error mechanisms of conventional maximum likelihood equalisers operating on rapidly time-varying channels are investigated and highlight the problems of channel estimation using delayed and often incorrect symbol estimates. The relative sensitivity of Bayesian equalisation techniques to errors in the channel estimate is studied and demonstrates that the structure's equalisation capability is also susceptible to such errors. Applications of multiple channel estimator methods are developed, leading to reduced complexity structures which trade performance for a smaller computational load. These novel structures are shown to provide an improvement over the conventional techniques, especially for rapidly time-varying channels, by reducing the time delay in the channel estimation process. Finally, the use of confidence measures of the equaliser's symbol estimates in order to improve channel estimation is studied and isolates the critical areas in the development of the technique — the production of reliable confidence measures by the equalisers and the statistics of symbol estimation error bursts

    Aeronautical engineering: A continuing bibliography with indexes (supplement 202)

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    This bibliography lists 447 reports, articles and other documents introduced into the NASA scientific and technical information system in June 1986

    Abstracts on Radio Direction Finding (1899 - 1995)

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    The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion
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