Development of Radar Pulse Compression Techniques Using Computational Intelligence Tools

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

Multiobjective Optimization — New Formulation and Application to Radar Signal Processing

The present thesis aims to make an in-depth study of Multiobjective optimization (MOO), Multiobjective algorithms and Radar Pulse Compression. Following the approach of bacteria foraging technique, a new MOO algorithm Multiobjective Bacteria Foraging Optimization (MOBFO) has been proposed in this thesis. We compared the performance of our proposed algorithm with existing algorithms Nondominated Sorting Genetic Algorithm (NSGA-II) and Multiobjective Particle Swarm Optimization (MOPSO) for different test functions. In radar signal processing Pulse Compression is used for high range resolution and long range detection. The classical methods for Pulse Compression of the received signal use matched filter and mismatched filter. For improving the performance of pulse compression, a new problem formulation has been constructed that uses constrained function optimization with the help of Particle Swarm Optimization (PSO). Artificial Neural Network (ANN) is being used for Pulse Compression that achieves a significant supression of the sidelobes. Functional Link Artificial Neural Network (FLANN)has been proposed for better sidelobes reduction than Multi Layer Perceptron (MLP)network with both lower computational and lower structural complexity. MOO approach has been proposed to use with Radial Basis Function (RBF) for Pulse Compression that improves the accuracy and complexity of RBF network

Comparison of DC and SRF Photoemission Guns For High Brightness High Average Current Beam Production

A comparison of the two most prominent electron sources of high average current high brightness electron beams, DC and superconducting RF photoemission guns, is carried out using a large-scale multivariate genetic optimizer interfaced with space charge simulation codes. The gun geometry for each case is varied concurrently with laser pulse shape and parameters of the downstream beamline elements of the photoinjector to obtain minimum emittance as a function of bunch charge. Realistic constraints are imposed on maximum field values for the two gun types. The SRF and DC gun emittances and beam envelopes are compared for various values of photocathode thermal emittance. The performance of the two systems is found to be largely comparable provided low intrinsic emittance photocathodes can be employed

Waveform design and processing techniques in OFDM radar

Includes bibliographical referencesWith the advent of powerful digital hardware, software defined radio and radar have become an active area of research and development. This in turn has given rise to many new research directions in the radar community, which were previously not comprehensible. One such direction is the recently investigated OFDM radar, which uses OFDM waveforms instead of the classic linear frequency mod- ulated waveforms. Being a wideband signal, the OFDM symbol offers spectral efficiency along with improved range resolution, two enticing characteristics for radar. Historically a communication signal, OFDM is a special form of multi- carrier modulation, where a single data stream is transmitted over a number of lower rate carriers. The information is conveyed via sets of complex phase codes modulating the phase of the carriers. At the receiver, a demodulation stage estimates the transmitted phase codes and the information in the form of binary words is finally retrieved. In radar, the primary goal is to detect the presence of targets and possibly estimate some of their features through measurable quantities, e.g. range, Doppler, etc. Yet, being a young waveform in radar, more understanding is required to turn it into a standard radar waveform. Our goal, with this thesis, is to mature our comprehension of OFDM for radar and contribute to the realm of OFDM radar. First, we develop two processing alternatives for the case of a train of wideband OFDM pulses. In this, our first so-called time domain solution consists in applying a matched filter to compress the received echoes in the fast time before applying a fast Fourier transform in the slow time to form the range Doppler image. We motivate this approach after demonstrating that short OFDM pulses are Doppler tolerant. The merit of this approach is to conserve existing radar architectures while operating OFDM waveforms. The second so-called frequency domain solution that we propose is inspired from communication engineering research since the received echoes are tumbled in the frequency domain. After several manipulations, the range Doppler image is formed. We explain how this approach allows to retrieve an estimate of the unambiguous radial velocity, and propose two methods for that. The first method requires the use of identical sequence (IS) for the phase codes and is, as such, binding, while the other method works irrespective of the phase codes. Like the previous technique, this processing solution accommodates high Doppler frequencies and the degradation in the range Doppler image is negligible provided that the spacing between consecutive subcarriers is sufficient. Unfortunately, it suffers from the issue of intersymbol interference (ISI). After observing that both solutions provide the same processing gain, we clarify the constraints that shall apply to the OFDM signals in either of these solutions. In the first solution, special care has been employed to design OFDM pulses with low peak-to-mean power ratio (PMEPR) and low sidelobe level in the autocorrelation function. In the second solution, on the other hand, only the constraint of low PMEPR applies since the sidelobes of the scatterer characteristic function in the range Doppler image are Fourier based. Then, we develop a waveform-processing concept for OFDM based stepped frequency waveforms. This approach is intended for high resolution radar with improved low probability of detection (LPD) characteristics, as we propose to employ a frequency hopping scheme from pulse to pulse other than the conventional linear one. In the same way we treated our second alternative earlier, we derive our high range resolution processing in matrix terms and assess the degradation caused by high Doppler on the range profile. We propose using a bank of range migration filters to retrieve the radial velocity of the scatterer and realise that the issue of classical ambiguity in Doppler can be alleviated provided that the relative bandwidth, i.e. the total bandwidth covered by the train of pulses divided by the carrier frequency, is chosen carefully. After discussing a deterministic artefact caused by frequency hopping and the means to reduce it at the waveform design or processing level, we discuss the benefit offered by our concept in comparison to other standard wideband methods and emphasize on its LPD characteristics at the waveform and pulse level. In our subsequent analysis, we investigate genetic algorithm (GA) based techniques to finetune OFDM pulses in terms of radar requirements viz., low PMEPR only or low PMEPR and low sidelobe level together, as evoked earlier. To motivate the use of genetic algorithms, we establish that existing techniques are not exible in terms of the OFDM structure (the assumption that all carriers are present is always made). Besides, the use of advanced objective functions suited to particular configurations (e.g. low sidelobe level in proximity of the main autocorrelation peak) as well as the combination of multiple objective functions can be done elegantly with GA based techniques. To justify that solely phase codes are used for our optimisation(s), we stress that the weights applied to the carriers composing the OFDM signal can be spared to cope with other radar related challenges and we give an example with a case of enhanced detection. Next, we develop a technique where we exploit the instantaneous wideband trans- mission to characterise the type of the canonical scatterers that compose a target. Our idea is based on the well-established results from the geometrical theory of diffraction (GTD), where the scattered energy varies with frequency. We present the problem related to ISI, stress the need to design the transmitted pulse so as to reduce this risk and suggest having prior knowledge over the scatterers relative positions. Subsequently, we develop a performance analysis to assess the behaviour of our technique in the presence of additive white Gaussian noise (AWGN). Then, we demonstrate the merit of integrating over several pulses to improve the characterisation rate of the scatterers. Because the scattering centres of a target resonate variably at different frequencies, frequency diversity is another enticing property which can be used to enhance the sensing performance. Here, we exploit this element of diversity to improve the classification function. We develop a technique where the classification takes place at the waveform design when few targets are present. In our case study, we have three simple targets. Each is composed of perfectly electrically conducting spheres for which we have exact models of the scattered field. We develop a GA based search to find optimal OFDM symbols that best discriminate one target against any other. Thereafter, the OFDM pulse used for probing the target in the scene is constructed by stacking the resulting symbols in time. After discussing the problem of finding the best frequency window to sense the target, we develop a performance analysis where our figure of merit is the overall probability of correct classification. Again, we prove the merit of integrating over several pulses to reach classification rates above 95%. In turn, this study opens onto new challenges in the realm of OFDM radar. We leave for future research the demonstration of the practical applicability of our novel concepts and mention manifold research axes, viz., a signal processing axis that would include methods to cope with inter symbol interference, range migration issues, methods to raise the ambiguity in Doppler when several echoes from distinct scatterers overlap in the case of our frequency domain processing solutions; an algorithmic axis that would concern the heuristic techniques employed in the design of our OFDM pulses. We foresee that further tuning might help speeding up our GA based algorithms and we expect that constrained multi- objective optimisation GA (MOO-GA) based techniques shall benefit the OFDM pulse design problem in radar. A system design axis that would account for the hardware components' behaviours, when possible, directly at the waveform design stage and would include implementation of the OFDM radar system

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

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

Research Article Enhanced Optimized Link State Routing for Multimedia Traffic using Genetic Algorithm

Abstract: The aim of this research is to modify OLSR using GA to reduce the end to end delay and to improve the network throughput. Simulation was carried out for multimedia traffic and video streamed network traffic using OPNET Simulator. Routing is a primary MANET function where each node forms routes between nodes not directly in each others range for communication. Major challenges in MANET are routing protocol design while maintaining quality of service in the network. Optimized Link State Routing (OLSR) protocol is

Development of Efficient Radar Pulse Compression Technique for Frequency Modulated Pulses

Radar systems use Pulse Compression techniques to enhance the long range detection capability of long duration pulse and the range resolution capability of short pulse. Frequency and phase modulation techniques are used to increase the BW of long duration pulse to achieve better range resolution with limited peak power. Towards this purpose Linear FM chrip is the very common form of waveform. This waveform has a matched filtered Response (or ACF) with side lobe level is about -13dB. It may be improve by using methods such as windowing, adaptive filtering and optimization techniques. Windowing is used in LFM pulse Compression to reduce the side lobes. But the output SNR can be reduced by 1 to 2 dB due to windowing, this leads to reduce the false alarm rates in object detection applications. Using a train of stepped frequency pulses is an efficient method that achieves large overall Bandwidth and at the same time, maintains narrow instantaneous bandwidth. In this method a frequency step frequency step is added between successive pulses. One of the benefits of this method is that it allows us to use the duration between pulses to control the mid frequency of the other narrow band components of the radar system. Introducing frequency step between consecutive pulses is an efficient method to enhance the bandwidth of pulse train. The large value of frequency step gives large total bandwidth and better range resolution. However, if the product of frequency step and pulse width becomes more than one, the stepped frequency pulse-train ACF experiences unwanted peaks, referred to as “grating lobes”. A way to reduce these grating lobes is to use LFM pulses of some bandwidth B in place of the fixed frequency pulses. We can derive a relationship between frequency step, bandwidth and pulse duration such that nulls are placed at points where the grating lobes have been located by analyzing ambiguity function and ACF expression

SoC-based FPGA architecture for image analysis and other highly demanding applications

Al giorno d'oggi, lo sviluppo di algoritmi si concentra su calcoli efficienti in termini di prestazioni ed efficienza energetica. Tecnologie come il field programmable gate array (FPGA) e il system on chip (SoC) basato su FPGA (FPGA/SoC) hanno dimostrato la loro capacità di accelerare applicazioni di calcolo intensive risparmiando al contempo il consumo energetico, grazie alla loro capacità di elevato parallelismo e riconfigurazione dell'architettura. Attualmente, i cicli di progettazione esistenti per FPGA/SoC sono lunghi, a causa della complessità dell'architettura. Pertanto, per colmare il divario tra le applicazioni e le architetture FPGA/SoC e ottenere un design hardware efficiente per l'analisi delle immagini e altri applicazioni altamente demandanti utilizzando lo strumento di sintesi di alto livello, vengono prese in considerazione due strategie complementari: tecniche ad hoc e stima delle prestazioni. Per quanto riguarda le tecniche ad-hoc, tre applicazioni molto impegnative sono state accelerate attraverso gli strumenti HLS: discriminatore di forme di impulso per i raggi cosmici, classificazione automatica degli insetti e re-ranking per il recupero delle informazioni, sottolineando i vantaggi quando questo tipo di applicazioni viene attraversato da tecniche di compressione durante il targeting dispositivi FPGA/SoC. Inoltre, in questa tesi viene proposto uno stimatore delle prestazioni per l'accelerazione hardware per prevedere efficacemente l'utilizzo delle risorse e la latenza per FPGA/SoC, costruendo un ponte tra l'applicazione e i domini architetturali. Lo strumento integra modelli analitici per la previsione delle prestazioni e un motore design space explorer (DSE) per fornire approfondimenti di alto livello agli sviluppatori di hardware, composto da due motori indipendenti: DSE basato sull'ottimizzazione a singolo obiettivo e DSE basato sull'ottimizzazione evolutiva multiobiettivo.Nowadays, the development of algorithms focuses on performance-efficient and energy-efficient computations. Technologies such as field programmable gate array (FPGA) and system on chip (SoC) based on FPGA (FPGA/SoC) have shown their ability to accelerate intensive computing applications while saving power consumption, owing to their capability of high parallelism and reconfiguration of the architecture. Currently, the existing design cycles for FPGA/SoC are time-consuming, owing to the complexity of the architecture. Therefore, to address the gap between applications and FPGA/SoC architectures and to obtain an efficient hardware design for image analysis and highly demanding applications using the high-level synthesis tool, two complementary strategies are considered: ad-hoc techniques and performance estimator. Regarding ad-hoc techniques, three highly demanding applications were accelerated through HLS tools: pulse shape discriminator for cosmic rays, automatic pest classification, and re-ranking for information retrieval, emphasizing the benefits when this type of applications are traversed by compression techniques when targeting FPGA/SoC devices. Furthermore, a comprehensive performance estimator for hardware acceleration is proposed in this thesis to effectively predict the resource utilization and latency for FPGA/SoC, building a bridge between the application and architectural domains. The tool integrates analytical models for performance prediction, and a design space explorer (DSE) engine for providing high-level insights to hardware developers, composed of two independent sub-engines: DSE based on single-objective optimization and DSE based on evolutionary multi-objective optimization