Remote Vibration Estimation Using Displaced Phase Center Antenna SAR in a Strong Clutter Environment

Synthetic aperture radar (SAR) is a ubiquitous remote sensing platform that is used for numerous applications. In its most common con\ufb01guration, SAR produces a high resolution, two-dimensional image of a scene of interest. An underlying assumption when creating this high resolution image is that all targets in the ground scene are stationary throughout the duration of the image collection. If a target is not static, but instead vibrating, it introduces a modulation on the returned radar signal termed the micro-Doppler e\ufb00ect. The ability to estimate the targets vibration frequency and vibration amplitude by exploiting the micro-Doppler e\ufb00ect, all while in a high clutter environment can provide strategic information for target identi\ufb01cation and target condition/status. This thesis discusses one method that processes the non-stationary signal of interest generated by the vibrating target in displaced phase center antenna (DPCA)-SAR in high clutter. The method is based on the extended Kalman \ufb01lter (EKF) \ufb01rst proposed by Dr. Wang in his PhD dissertation titled Time-frequency Methods for Vibration Estimation Using Synthetic Aperture Radar [24]. Previously, EKF method could accurately estimate the target\u27s vibration frequency for single component sinusoidal vibrations. In addition, the target\u27s vibration amplitude and position could be tracked throughout the duration of the aperture for single component sinusoidal vibrations. This thesis presents a modi\ufb01cation to the EKF method, which improves the EKF method\u27s overall performance. This modi\ufb01cation improves the tracking capability of single component vibrations and provides reliable position tracking for several other di\ufb00erent types of vibration dynamics. In addition, the EKF method is more reliable at higher noise levels. More speci\ufb01cally, for a single component vibration, the mean square error (MSE) of the original method is .2279, while the MSE of the method presented in this paper is .1503. Therefore, the method presented in this paper improves the position estimate of the vibrating target by 34% when SNR = 15 dB. For the multicomponent vibrations, the mean square error of the estimated target position is reduced b 76% when SNR = 15 dB. The original EKF method and the modi\ufb01ed EKF method as well as simulations for various target vibration dynamics are provided in this thesis.\u2

Remote Vibration Estimation Using Displaced-Phase-Center Antenna SAR for Strong Clutter Environments

It has been previously demonstrated that it is possible to perform remote vibrometry using synthetic aperture radar (SAR) in conjunction with the discrete fractional Fourier transform (DFrFT). Specifically, the DFrFT estimates the chirp parameters (related to the instantaneous acceleration of a vibrating object) of a slow-time signal associated with the SAR image. However, ground clutter surrounding a vibrating object introduces uncertainties in the estimate of the chirp parameter retrieved via the DFrFT method. To overcome this shortcoming, various techniques based on subspace decomposition of the SAR slow-time signal have been developed. Nonetheless, the effectiveness of these techniques is limited to values of signal-to-clutter ratio ≥5 dB. In this paper, a new vibrometry technique based on displaced-phase-center antenna (DPCA) SAR is proposed. The main characteristic of a DPCA-SAR is that the clutter signal can be canceled, ideally, while retaining information on the instantaneous position and velocity of a target. In this paper, a novel method based on the extended Kalman filter (EKF) is introduced for performing vibrometry using the slow-time signal of a DPCA-SAR. The DPCA-SAR signal model for a vibrating target, the mathematical characterization of the EKF technique, and vibration estimation results for various types of vibration dynamics are presented

On Improved Accuracy Chirp Parameter Estimation using the DFRFT with Application to SAR-based Vibrometry

The Discrete Fractional Fourier Transform (DFRFT) has in recent years, become a useful tool for multicomponent chirp signal analysis. Chirp signals are transformed into spectral peaks in the chirp rate versus center frequency representation, whose coordinates are related to the underlying chirp parameters via a computed empirical peak to parameter mapping incorporated into the Santhanam-Peacock algorithm. In this thesis, we attempt to quantify the accuracy of the DFRFT approach by first studying the discretization error sources that arise from the transitioning of the continuous FRFT to DFRFT. Then, we refine prior work by Ishwor Bhatta to develop analytical expressions for the chirp rate and center frequency parameters instead of the empirical mapping approach. We further study the extensions of this refined DFRFT approach using zero padding, spectral peak interpolation, and chirp-z-transform based zooming. The performance of the refined estimators is compared versus the Cramer-Rao lower bound and shown to asymptotically approach the bound. This refined DFRFT approach is then applied to Synthetic Aperture Radar Vibrometry data from several vibrating targets and the estimated acceleration information and vibration frequencies are shown to be very close to the corresponding ground-truth accelerometer measurements

Contributions in inverse synthetic aperture radar imaging

Ph.DDOCTOR OF PHILOSOPH

Interferometric synthetic aperture sonar system supported by satellite

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

Radar target micro-doppler signature classification

This thesis reports on research into the field of Micro-Doppler Signature (μ-DS) based radar Automatic Target Recognition (ATR) with additional contributions to general radar ATR methodology. The μ-DS based part of the research contributes to three distinct areas: time domain classification; frequency domain classification; and multiperspective μ-DS classification that includes the development of a theory for the multistatic μ-DS. The contribution to general radar ATR is the proposal of a methodology to allow better evaluation of potential approaches and to allow comparison between different studies. The proposed methodology is based around a “black box” model of a radar ATR system that, critically, includes a threshold to detect inputs that are previously unknown to the system. From this model a set of five evaluation metrics are defined. The metrics increase the understanding of the classifier’s performance from the common probability of correct classification, that reports how often the classifier correctly identifies an input, to understanding how reliable it is, how capable it is of generalizing from the reference data, and how effective its unknown input detection is. Additionally, the significance of performance prediction is discussed and a preliminary method to estimate how well a classifier should perform is developed. The proposed methodology is then used to evaluate the μ-DS based radar ATR approaches considered. The time domain classification investigation is based around using Dynamic Time Warping (DTW) to identify radar targets based on their μ-DS. DTW is a speech processing technique that classifies data series by comparing them with a pre-classified reference dataset. This is comparable to the common k-Nearest Neighbour (k-NN) algorithm, so k-NN is used as a benchmark against which to evaluate DTW’s performance. The DTW approach is observed to work well. It achieved high probability of correct classification and reliability as well as being able to detect inputs of unknown class. However, the classifier’s ability to generalize from the reference data is less impressive and it performed only slightly better than a random selection from the possible output classes. Difficulties in classifying the μ-DS in the time domain are identified from the k-NN results prompting a change to the frequency domain. Processing the μ-DS in the frequency domain permitted the development of an advanced feature extraction routine to maximize the separation of the target classes and therefore reduce the effort required to classify them. The frequency domain also permitted the use of the performance prediction method developed as part of the radar ATR methodology and the introduction of a na¨ıve Bayesian approach to classification. The results for the DTW and k-NN classifiers in the frequency domain were comparable to the time domain, an unexpected result since it was anticipated that the μ-DS would be easier to classify in the frequency domain. However, the naıve Bayesian classifier produced excellent results that matched with the predicted performance suggesting it could not be bettered. With a successful classifier, that would be suitable for real-world use, developed attention turned to the possibilities offered by the multistatic μ-DS. Multiperspective radar ATR uses data collected from different target aspects simultaneously to improve classification rates. It has been demonstrated successful for some of the alternatives to μ-DS based ATR and it was therefore speculated that it might improve the performance of μ-DS ATR solutions. The multiple perspectives required for the classifier were gathered using a multistatic radar developed at University College London (UCL). The production of a dataset, and its subsequent analysis, resulted in the first reported findings in the novel field of the multistatic μ-DS theory. Unfortunately, the nature of the radar used resulted in limited micro-Doppler being observed in the collected data and this reduced its value for classification testing. An attempt to use DTW to perform multiperspective μ-DS ATR was made but the results were inconclusive. However, consideration of the improvements offered by multiperspective processing in alternative forms of ATR mean it is still expected that μ-DS based ATR would benefit from this processing

Technique-Based Exploitation Of Low Grazing Angle SAR Imagery Of Ship Wakes

The pursuit of the understanding of the effect a ship has on water is a field of study that is several hundreds of years old, accelerated during the years of the industrial revolution where the efficiency of a ship’s engine and hull determined the utility of the burgeoning globally important sea lines of communication. The dawn of radar sensing and electronic computation have expanding this field of study still further where new ground is still being broken. This thesis looks to address a niche area of synthetic aperture radar imagery of ship wakes, specifically the imaging geometry utilising a low grazing angle, where significant non-linear effects are often dominant in the environment. The nuances of the synthetic aperture radar processing techniques compounded with the low grazing angle geometry to produce unusual artefacts within the imagery. It is the understanding of these artefacts that is central to this thesis. A sub-aperture synthetic aperture radar technique is applied to real data alongside coarse modelling of a ship and its wake before finally developing a full hydrodynamic model for a ship’s wake from first principles. The model is validated through comparison with previously developed work. The analysis shows that the resultant artefacts are a culmination of individual synthetic aperture radar anomalies and the reaction of the radar energy to the ambient sea surface and spike events

Advanced signal processing methods for plane-wave color Doppler ultrasound imaging

Conventional medical ultrasound imaging uses focused beams to scan the imaging scene line-by-line, but recently however, plane-wave imaging, in which plane-waves are used to illuminate the entire imaging scene, has been gaining popularity due its ability to achieve high frame rates, thus allowing the capture of fast dynamic events and producing continuous Doppler data. In most implementations, multiple low-resolution images from different plane wave tilt angles are coherently averaged (compounded) to form a single high-resolution image, albeit with the undesirable side effect of reducing the frame rate, and attenuating signals with high Doppler shifts. This thesis introduces a spread-spectrum color Doppler imaging method that produces high-resolution images without the use of frame compounding, thereby eliminating the tradeoff between beam quality, frame rate and the unaliased Doppler frequency limit. The method uses a Doppler ensemble formed of a long random sequence of transmit tilt angles that randomize the phase of out-of-cell (clutter) echoes, thereby spreading the clutter power in the Doppler spectrum without compounding, while keeping the spectrum of in-cell echoes intact. The spread-spectrum method adequately suppresses out-of-cell blood echoes to achieve high spatial resolution, but spread-spectrum suppression is not adequate for wall clutter which may be 60 dB above blood echoes. We thus implemented a clutter filter that re-arranges the ensemble samples such that they follow a linear tilt angle order, thereby compacting the clutter spectrum and spreading that of the blood Doppler signal, and allowing clutter suppression with frequency domain filters. We later improved this filter with a redesign of the random sweep plan such that each tilt angle is repeated multiple times, allowing, after ensemble re-arrangement, the use of comb filters for improved clutter suppression. Experiments performed using a carotid artery phantom with constant flow demonstrate that the spread-spectrum method more accurately measures the parabolic flow profile of the vessel and outperforms conventional plane-wave Doppler in both contrast resolution and estimation of high flow velocities. To improve velocity estimation in pulsatile flow, we developed a method that uses the chirped Fourier transform to reduce stationarity broadening during the high acceleration phase of pulsatile flow waveforms. Experimental results showed lower standard deviations compared to conventional intensity-weighted-moving-average methods. The methods in this thesis are expected to be valuable for Doppler applications that require measurement of high velocities at high frame rates, with high spatial resolution

Terahertz Micro-Doppler Radar for Detection and Characterization of Multicopters

abstract: The micromotions (e.g. vibration, rotation, etc.,) of a target induce time-varying frequency modulations on the reflected signal, called the micro-Doppler modulations. Micro-Doppler modulations are target specific and may contain information needed to detect and characterize the target. Thus, unlike conventional Doppler radars, Fourier transform cannot be used for the analysis of these time dependent frequency modulations. While Doppler radars can detect the presence of a target and deduce if it is approaching or receding from the radar location, they cannot identify the target. Meaning, for a Doppler radar, a small commercial aircraft and a fighter plane when gliding at the same velocity exhibit similar radar signature. However, using a micro-Doppler radar, the time dependent frequency variations caused by the vibrational and rotational micromotions of the two aircrafts can be captured and analyzed to discern between them. Similarly, micro-Doppler signature can be used to distinguish a multicopter from a bird, a quadcopter from a hexacopter or a octacopter, a bus from a car or a truck and even one person from another. In all these scenarios, joint time-frequency transforms must be employed for the analysis of micro-Doppler variations, in order to extract the targets’ features. Due to ample bandwidth, THz radiation provides richer radar signals than the microwave systems. Thus, a Terahertz (THz) micro-Doppler radar is developed in this work for the detection and characterization of the micro-Doppler signatures of quadcopters. The radar is implemented as a continuous-wave (CW) radar in monostatic configuration and operates at a low-THz frequency of 270 GHz. A linear time-frequency transform, the short-time Fourier transform (STFT) is used for the analysis the micro-Doppler signature. The designed radar has been built and measurements are carried out using a quadcopter to detect the micro-Doppler modulations caused by the rotation of its propellers. The spectrograms are obtained for a quadcopter hovering in front of the radar and analysis methods are developed for characterizing the frequency variations caused by the rotational and vibrational micromotions of the quadcopter. The proposed method can be effective for distinguishing the quadcopters from other flying targets like birds which lack the rotational micromotions.Dissertation/ThesisMasters Thesis Electrical Engineering 201

Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design