Radar Signal Processing

This paper develops a new radar system based on the concept of quantum entanglement property termed by Albert Einstein as a spooky action at a distance. The predicted Entangled Photonic Radar (EPR) System employs the non-classic strong correlation of the quantum states of two entangled photonic beams over radar range. Here, a block diagram of the EPR system is presented, which includes high power signal and idler entangled photonic beams generator. The signal beam is transmitted via the antenna towards the target and the idler beam is detected directly into the idler detector array that carries the quantum states changes of the radar signal beam simultaneously before the echo arrival. The returned signal from the target is detected by the signal detector array. The output information of idler and signal detectors are applied to the coincidence estimator to be processed to characterize the target parameters and its clear image. The EPR system diagrams and analytical method are presented. The developed efficient detection devices for different quantum states may lead to a significant radar resolution in displaying the target image and location as soon as the beam impinges the target. This system will overcome many of drawbacks of the classic radars.

Subsurface radar techniques are increasingly being used for the detection and location of buried artefacts and structures within the upper regions of the earth's surface. The paper reviews the work done to date in this field, laying emphasis on the range of applications and the need for system design to match the intended application. An overall design strategy is outlined, together with a more detailed treatment of a range of topics which are relevant to effective subsurface radar operation. These include the dielectric properties of earth materials, signal modulation schemes, design and construction of suitable antennas, and methods of signal processing. Finally, an assessment is made of future prospects, both technical and commercial, for this developing area of radar technology.

Linear frequency modulated pulse compression (LFM-PC) radar is one of the widely used modern radar systems. It has high immunity against conventional noise jamming due to its high processing gain. To sufficiently affect such radar, smart jamming techniques should be applied. In the last decade, different smart jamming techniques have been proposed. However, literature lacks to the analysis and evaluation of the effect of such techniques on modern radar systems. In this paper, the effect of one of the recently proposed jamming techniques, called chopping jamming, is analyzed and evaluated against LFM-PC radar depending on a typical LFM-PC verified radar model. The worthy of the application of chopping jamming on LFM-PC radar regarding to the probability of false alarm as well as radar detection is discussed and presented.

We will illustrate two problems of Machine Learning on Lie groups for Radar applications. Target recognition on Radar micro-Doppler data could be modeled by a problem of classification of dataset considered as elements of SU(1,1) Lie Group. Second example consider flying object recognition on their kinematics coded in SE(3) Lie Groups. We will use Souriau method to define covariant Gibbs density on Lie groups to be able to make statistics on Lie groups.

In multichannel pulse Doppler surveillance radars, parallel signal processing is used in several timespatial channels, i.e. range-azimuth-elevation. Time-spatially differenced data give radar output picture about targets existence, position and moving parameters. A data fusion center synthesizes differenced channels data to provide continuous reliable tracking and displaying. Targets move over flying area across time-spatially channels, including "null" space occurring between antenna beams. The concept of non-coherent inter-channel statistical CFAR detection based on antenna beam forming is introduced in this paper to obtain continuous inter-channel even-detection output.

Applications of digital signal processing in telecommunications are considered, taking into account the characteristics of telecommunications systems, aspects of digital transmission, digital switching, digital signal processing in pulse-code modulated transmission terminals, ...

This tutorial provides a broad-based discussion of radar system, covering the following topics:
-Introduction to Radars in Military and Commercial Applications
-Radar System Block Diagram
-Radar Antennas (slotted waveguide array, planar array), Transmitter (magnetron, solid-state), Receiver, Pedestal and Radome
-Plot Extraction, Tracking Algorithms and Display
-Radar Range Equation, Detection Performance
-Wave Propagation and Radar Cross Section
-Emerging and Advanced Radar Systems (phased-array, multi-beam, multi-mode, FMCW, solid-state)

In the discussion, practical systems, technical specifications and data will be used to enhance learning.In addition, simulation results will also be used to present findings.

The objective of the tutorial session is to equip participants with solid understanding of radar systems for system level applications and prepare them for advanced and professional radar courses, projects and research.

This tutorial is designed and developed based on the following references:
[1] G. W. Stimson, Introduction to Airborne Radar Second Edition, Scitech Publishing, 1998.
[2] L. V. Blake, A Guide to Basic Pulse-Radar Maximum-Range Calculation, NRL Report 6930, 1969.
[3] K. H. Lee, Radar Systems for Nanyang Technological University, TBSS, 2014.

In this paper, we present a new complex electronic system for facilitating communication with severely disabled patients and telemonitoring their physiological parameters. The proposed assistive system includes three subsystems (Patient, Server, and Caretaker) connected to each other via the Internet. The two-way communication function is based on keywords technology using a WEB application implemented at the server level, and the application is accessed remotely from the patient’s laptop/tablet PC. The patient’s needs can be detected by using different switch-type sensors that are adapted to the patient’s physical condition or by using eye-tracking interfaces. The telemonitoring function is based on a wearable wireless sensor network, organized around the Internet of Things concept, and the sensors acquire different physiological parameters of the patients according to their needs. The mobile Caretaker device is represented by a Smartphone, which uses an Android application for communicating with patients and performing real-time monitoring of their physiological parameters.

This is MATLAB's 10 most easy & most basic programs that I's supposed to submit in my practicals. In this document I've complied 10 MATLAB programs from basic to advanced through intermediate levels, But overall they are for beginners only. It's only a 26 pages doc. for academic purposes. well, What else a student can offer you, huh? LOLz

Automotive radar is an emerging field of research and development. Technological advancements in this field will improve safety for vehicles, pedestrians, and bicyclists, and enable the development of autonomous vehicles. Usage the Automotive radar is expanding in car and road areas to reduce collisions and accident. Automotive radar developers face a problem to test their radar sensor in the street since there are a lot of interferences signals, noise and unpredicted situations. This thesis provides a part of the solution for this problem by designing a device can demonstrate a different speeds value. This device will help the developer to test their radar sensor inside an anechoic chamber room that provides accurate control of the environmental conditions. This report shows how to build the measuring setup device, step by step to demonstrate the people and vehicle’s speed in the street by a Doppler emulator using the wheel for millimetre FWMC radar. Linear speed system needs a large space for testing, but using the rotational wheel allow the developer to test the radar sensor in a small area. It begins with the wheel design specifications and the relation between the rotational speed (RPM) of the wheel and the Doppler frequency. The Doppler frequency is changed by varying the speed of the wheel. Control and power circuit was carefully designed to control the wheel speed accurately. All the measuring setup device parts were assembled in one box. Also, signal processing was done by MATLAB to measure the Doppler frequency using millimetre FMCW radar sensor. The measuring setup device was tested in the anechoic chamber room for different speeds. the manual and automatic tests show good results to measure the different wheel speeds with high accuracy.

Inverse Synthetic Aperture Radar (ISAR) provides a very effective technique for reconstructing high resolution Imagery from raw data collected by relatively small antenna. ISAR imaging is induced by target motion and is obtained by means of a signal processing that can be enabled both on and off-line. ISAR produces high-resolution on two- and three-dimensional images by taking into account the information in both down-range direction (received echoes from target scatterers in time domain) and cross-range direction (Doppler). ISAR radars are commonly used on vessels or aircraft and can provide a radar image of sufficient quality for target recognition. The ISAR image is often adequate to discriminate between various missiles, military aircraft, and civilian aircraft. This project deals with MATLAB based signal processing system to perform Range-Doppler processing in real-time for Linear FMCW (frequency Modulated Continuous Wave) radar systems. The Range-Doppler Image can be obtained after coherent integration of several frequency sweepings. Range-Doppler images can be used later for identification and classification algorithms.

As we are diving deeper into the world of Autonomous Driving, we need a more reliable and robust system which can sense the surrounding of a vehicle in all-weather conditions and at any time of the day. Apart from this, we also need a system which is highly accurate in terms of measuring the parameters like distance and velocity of the objects in its field of view. Keeping these factors in mind we have proposed a robust model to fuse camera and radar data, which is an economical choice with a proven performance. This model is implemented using Robot Operating System (ROS) environment, which is an Open source middleware for Autonomous Driving Application.

4 Jenis Radar Yang Sering Digunakan Untuk Navigasi Radar adalah salah satu jenis peralatan navigasi yang digunakan di darat, laut dan udara yang sering difungsikan untuk melacak gelombang elektromagnetik dari sensor dan kembali ke sensor. Radar sering digunakan di bidang transportasi dan militer. Penggunaan Radar di bidang Transportasi yaitu berfungsi untuk melacak keberadaan alat transportasi yang dicari misalnya mencari keberadaan benda yang ada di laut, darat dan udara. Selain itu rada juga sering digunakan untuk keperluan militer misalnya berfungsi untuk mencari keberadaan tank-tank musuh atau lokasi keberadaan musuh di medan pertempuran. Berikut ini jenis-jenis radar yang sering digunakan untuk navigasi : 1. Jenis Radar berdasarkan bentuk gelombangnya (Waveform)

Penemuan radar (radio detection and ranging)pada tahun 1953 oleh Robert Watson-Watt juga menerapkan sistem kerja gelombang ultrasonik. Seperti sonar, alat inipun menjadi inspirasi digunakannya ultrasonik dalam bidang obstetri ginekologi kelak. Hanya pemanfaatannya saat itu lebih banyak digunakan untuk kepentingan pelacakan kapal musuh di udara.Perkembangan pemakaian ultrasonik di bidang obstetri ginekologi berikutnya jugatak lepas dari peranan penemuan Sonar merupakan sistem yang menggunakangelombang suara bawah air yang dipancarkan dan dipantulkan untuk mendeteksi danmenetapkan lokasi obyek di bawah laut atau untuk mengukur jarak bawah laut.Sejauh ini sonar telah luas digunakan untuk mendeteksi kapal selam danmendeteksi kedalaman, penangkapan ikan komersial, keselamatan penyelaman, dankomunikasidi laut.

Natural Language Processing (NLP) is a popular branch with how machines comprehend and interpret human language. A computer can only comprehend information in the form of numbers, not words. As a result, it's critical to research what preprocessing and featur techniques are required to implement on a human language so that when it's transformed to machine form, the computer can understand it. Text classification plays a vital role in NLP jobs, with applications in web search, document cate structure are naturally difficult to convert to a machine given special attention since they serve as a precurs Any errors in the early preprocessing approaches are passed on to the NLP pipeline's later stages. In addition, the order in which techniques like tokenization, StopWords elimination, and lemm considered. Information retrieval systems are particularly concerned with how efficiently textual input is cleaned and filtered to remove noisy material that does not add to efficiency and, moreover, leads to incorrect resul survey work emphasizes the importance of effective text preprocessing approaches, as well as information retrieval using Natural Language Processing feature extraction techniques.

Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.

Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.

By using pulse compression, radar can simultaneously achieve the energy of a long pulse and the resolution of a short pulse. The immunity of pulse compression radar against jamming can be increased by using waveform agility and diversity.
The most important types of pulse compression waveforms are frequency modulated, phase-coded, and orthogonal waveforms. In this paper, we will study and generate these waveforms in Matlab, and explain the main properties of each waveform and compare between them from the point of Doppler tolerance and time-sidelobe level using ambiguity function. Finally, we briefly introduce how radar waveforms can be generated using SDR

Digital Signal Processing (DSP) systems involve a wide spectrum of DSP algorithms and their realizations are often accelerated by use of novel VLSI design techniques. Now-a-days various DSP systems are implemented on a variety of programmable signal processors or on application specific VLSI chips. This paper presents the design of Adaptive Finite Impulse Response (FIR) filter for moving target detection in various clutter conditions in Radar Receiver. The design uses pipelined COordinate Rotation DIgital Computer (CORDIC) unit and pipelined multiplier to get high system throughput and reduced latency in each of the pipelined stage. Saving area on silicon substrate is essential to the design of any pipelined CORDIC. The area reduction in proposed design can be achieved through optimization in the number of micro rotations. For better adaptation and performance of Adaptive Filters and to minimize quantization error, the numbers of iterations are also optimized.

When radar systems were first implemented, engineers were solving complex mathematics and building prototypes to evaluate the performance of the systems. The design process took long time to complete. Nowadays, radar systems are becoming more complex and hence, evaluation of designs is now more complex. A development tool for demonstration of design is therefore required to evaluate and test the design of radar system. This tool can also be in the education of relevant engineering topics such as beamforming, direction-ofarrival (DOA) estimation and Doppler filtering. In addition, studies of a typical radar system can also be made possible.

Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.

In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM have been compared. This comparison was conducted to seek a robust method that would produce good classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG) signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder with SVM has been proposed. The EEG dataset used in this research was created by the University of Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature engineering. However, our prosed method of autoencoder in combination with SVM produced a similar accuracy of 65% without using any feature engineering technique. This research shows that this system of classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally control a robotic device or an exoskeleton.

This doctoral thesis was written at the Technologies for Cultural Heritage Laboratory (TCH Lab) which is part of the Electronic Department of the University of Florence. It is a multidisciplinary laboratory in the Information Technology area that is dealing with developing and testing of innovative techniques for conservation and monitoring of Cultural and Environmental Heritage.
This thesis deals with advanced data processing in Interferometric Synthetic Aperture Radar for unstable slope monitoring. Mainly the attention of the author is turned to the data processing algorithms for imaging the meaningful content of the specific radar observations. The particular acquisition system used in each type of observation was developed at the TCH Lab and was based on a Continuous Wave Stepped Frequency radar architecture.
Now GB-SAR interferometry is generally recognized as a powerful tool for detecting the displacements of large structures such as dams or buildings, but also for the terrain monitoring, exactly as the space-born SAR interferometry. But, in respect to space- born systems, for monitoring localized landslide phenomena (of the order of 1 km x 1 km area), GB-SAR seems to be more suitable as it can be specifically set up for a particular scenario geometry and in according to the dynamic characteristics of the landslide.
While conventional interferometric synthetic aperture radar is a very effective technique for measuring surface deformation, almost any interferogram includes large areas where the signals decorrelate and no measurements are possible. Consequently, most SAR studies focuses on areas that are dry and sparsely vegetated. A relatively new analysis technique (PS method) overcomes the decorrelation problem by identifying resolution elements whose echo is dominated by a single scatterer in a series of interferograms.
After an introduction on radar and SAR systems, in this Thesis we focused on the application of GB-SAR to monitor an open pit quarry using the PS method, and on the influence of the atmospheric disturbances, in particular boundary layer turbulence, on ground based radar measurements.
As far as the turbulence disturbances concerns, in this thesis an experimental survey was planned in order to deeply understand how radar signal, and in particular his statistic, can change in presence of such phenomena. The results obtained by using these procedures on real data acquired in a experimental facility are discussed too. The agreement between theoretical and real data confirms the validity of the used statistic, confirming the “Universal distribution” as a powerful tool to understand differend kind of complex phenomena.
Chapter 1 deals with Synthetic aperture techniques for imaging and interferometric applications, while Chapter 2 describes a measurement campaign in an open pit quarry near Florence, and his results are presented and discussed. Chapter 3 presents two experiments devoted to the study of the influence of atmospherical turbulence on radar signals.

In this paper we propose an approach for testing time-domain properties of analog and mixed-signal circuits. The approach is based on an adaptation of a recently developed test generation technique for hybrid systems and a new concept of coverage for such systems. The approach is illustrated by its application to some benchmark circuits.

Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.

Pulsed noise jamming is a common anti-radar jamming technique. It creates a noise pulse when radar signal is received, thus concealing any aircraft flying behind it with a block of noise. Modern Linear Frequency Modulated Pulse Compression (LFM-PC) radar, which is characterized by its high processing gain, is considered as one of the challenges to jammer systems. In this paper, the performance of such radar is evaluated analytically, which has not been exploited in any other literature before, under the effect of pulsed noise jamming. Mathematical models of the LFM-PC matched filter response in clear environment as well as pulsed noise jamming are derived. Receiver Operating Characteristic (ROC) is derived and used as a performance measurer. The Derived analytical results agreed with simulation results.

This thesis presents a study of different radar ranging techniques, synthetic aperture radio (SAR) imaging techniques and its application in Through Wall Imaging Radar. Ultra wide band (UWB) Stepped-Frequency Continuous Wave radar, in the range of 0.5 GHz to 3.0 GHz, is used as the ranging technique. Imaging of targets is done using back projection algorithm.
A novel simulator was developed to compensate for the lack of hardware. Simulator uses GPU for massive parallel processing. OpenGL is used for utilizing GPU hardware, it has wide availability and does not put limitation on hardware like CUDA or OpenCL.
Filtered Back Projection was used to reconstruct a 2D image from the range data acquired. Back Projection Algorithm is done on the CPU for ease. Algorithm is implemented in C++ with SIMD using AVX for high speed. OpenCV library is used for displaying the image and storing it in appropriate format.

In this work we investigate the different sensing schemes for detection of four targets as observed through a vector Poisson and Gaussian channels when the sensing time resource is limited and the source signals can be observed through a variety of sum combinations during that fixed time. For this purpose we can maximize the mutual information or the detection probability with respect to the time allocated to different sum combinations, for a given total fixed time. It is observed that for both Poisson and Gaussian channels; mutual information and Bayes risk with 0 − 1 cost are not necessarily consistent with each other. Concavity of mutual information between input and output, for certain sensing schemes, in Poisson channel and Gaussian channel is shown to be concave w.r.t given times as linear time constraint is imposed. No optimal sensing scheme for any of the two channels is investigated in this work.

Forest fire is one of those natural disasters that have been causing huge destruction in terms of loss of vegetation, animals and hence affects the economy. Image segmentation techniques have been applied on satellite images of forest fire to extract fire object and some data mining techniques have been used for predicting the spread of forest fire. This paper proposes a novel approach to isolation of fire region using time-sequenced images, classifying fire images from non-fire images, predicting its movement and estimating the area burnt. Once the images are enhanced, the fire region is segmented out. Feature extraction provides the necessary inputs for classification of images as fire and non-fire images. Linear regression is used to predict the movement of forest fire to facilitate better evacuation strategy. Burnt area is calculated from the difference image. This work is helpful in drafting evacuation strategies quickly by predicting the movement of forest fire and facilitates the kick-off of rehabilitation activities by identifying and assessing the burnt area.