Micromotion Feature Extraction of Space Target Based on Track-Before-Detect

The micromotion feature of space target provides an effective approach for target recognition. The existing micromotion feature extraction is implemented after target detection and tracking; thus the radar resources need to be allocated for target detection, tracking, and feature extraction, successively. If the feature extraction can be implemented by utilizing the target detecting and tracking pulses, the radar efficiency can be improved. In this paper, by establishing a feedback loop between micromotion feature extraction and track-before-detect (TBD) of target, a novel feature extraction method for space target is proposed. The TBD technology is utilized to obtain the range-slow-time curves of target scatterers. Then, micromotion feature parameters are estimated from the acquired curve information. In return, the state transition set of TBD is updated adaptively according to these extracted feature parameters. As a result, the micromotion feature parameters of space target can be extracted concurrently with implementing the target detecting and tracking. Simulation results show the effectiveness of the proposed method

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

Review of radar classification and RCS characterisation techniques for small UAVs or drones

This review explores radar-based techniques currently utilised in the literature to monitor small unmanned aerial vehicle (UAV) or drones; several challenges have arisen due to their rapid emergence and commercialisation within the mass market. The potential security threats posed by these systems are collectively presented and the legal issues surrounding their successful integration are briefly outlined. Key difficulties involved in the identification and hence tracking of these `radar elusive' systems are discussed, along with how research efforts relating to drone detection, classification and radar cross section (RCS) characterisation are being directed in order to address this emerging challenge. Such methods are thoroughly analysed and critiqued; finally, an overall picture of the field in its current state is painted, alongside scope for future work over a broad spectrum

Research on Target Detection Algorithm of Radar and Visible Image Fusion Based on Wavelet Transform

The target detection rate of unmanned surface vehicle is low because of waves, fog, background clutter and other environmental factors on the interference. Therefore, the paper studies the target detection algorithm of radar and visible image fusion based on wavelet transform. The visible image is preprocessed to ensure the detection effect. The multi-scale fractal model is used to extract the target features, and the difference between the fractal features of the target and the background is used to detect the target. The radar image is denoised by a combination of median filtering and wavelet transform. The processed visible light and radar image are fused with wavelet transform strategy. The coefficients of the low frequency sub-band are processed by the average fusion strategy. The coefficients of the high frequency sub-band are processed using a strategy with a higher absolute value. The standard deviation, the spatial frequency and the contrast resolution of the image fusion result are compared. The simulation results show that the processed image is better than the unprocessed image after the fusion

Loading an Equidistant Ion Chain in a Ring Shaped Surface Trap and Anomalous Heating Studies with a High Optical Access Trap

Microfabricated segmented surface ion traps are one viable avenue to scalable quantum information processing. At Sandia National Laboratories we design, fabricate, and characterize such traps. Our unique fabrication capabilities allow us to design traps that facilitate tasks beyond quantum information processing. The design and performance of a trap with a target capability of storing hundreds of equally spaced ions on a ring is described. Such a device could aid experimental studies of phenom- ena as diverse as Hawking radiation, quantum phase transitions, and the Aharonov - Bohm effect. The fabricated device is demonstrated to hold a 3c 400 ion circular crystal, with 9 μm average spacing between ions. The task is accomplished by first characterizing undesired electric fields in the trapping volume and then designing and applying an electric field that substantially reduces the undesired fields. In addition, experimental efforts are described to reduce the motional heating rates in a surface trap by low energy in situ argon plasma treatment that reduces the amount of surface contaminants. The experiment explores the premise that carbonaceous compounds present on the surface contribute to the anomalous heating of secular motion modes in surface traps. This is a research area of fundamental interest to the ion trapping community, as heating adversely affects coherence and thus gate fidelity. The de- vice used provides high optical laser access, substantially reducing scatter from the surface, and thus charging that may lead to excess micromotion. Heating rates for different axial mode frequencies are compared before and after plasma treatment. The presence of a carbon source near the plasma prevents making a conclusion on the observed absence of change in heating rates

Computer-aided diagnosis of complications of total hip replacement X-ray images

Hip replacement surgery has experienced a dramatic evolution in recent years supported by the latest developments in many areas of technology and surgical procedures. Unfortunately complications that follow hip replacement surgery remains the most challenging dilemma faced both by the patients and medical experts. The thesis presents a novel approach to segment the prosthesis of a THR surgical process by using an Active Contour Model (ACM) that is initiated via an automatically detected seed point within the enarthrosis region of the prosthesis. The circular area is detected via the use of a Fast, Randomized Circle Detection Algorithm. Experimental results are provided to compare the performance of the proposed ACM based approach to popular thresholding based approaches. Further an approach to automatically detect the Obturator Foramen using an ACM approach is also presented. Based on analysis of how medical experts carry out the detection of loosening and subsidence of a prosthesis and the presence of infections around the prosthesis area, this thesis presents novel computational analysis concepts to identify the key feature points of the prosthesis that are required to detect all of the above three types of complications. Initially key points along the prosthesis boundary are determined by measuring the curvature on the surface of the prosthesis. By traversing the edge pixels, starting from one end of the boundary of a detected prosthesis, the curvature values are determined and effectively used to determine key points of the prosthesis surface and their relative positioning. After the key-points are detected, pixel value gradients across the boundary of the prosthesis are determined along the boundary of the prosthesis to determine the presence of subsidence, loosening and infections. Experimental results and analysis are presented to show that the presence of subsidence is determined by the identification of dark pixels around the convex bend closest to the stem area of the prosthesis and away from it. The presence of loosening is determined by the additional presence of dark regions just outside the two straight line edges of the stem area of the prosthesis. The presence of infections is represented by the determination of dark areas around the tip of the stem of the prosthesis. All three complications are thus determined by a single process where the detailed analysis defer. The experimental results presented show the effectiveness of all proposed approaches which are also compared and validated against the ground truth recorded manually with expert user input

Characterisation and control of trapped-ion qubit

Trapped ions are one of the promising platforms that realise a quantum bit, or qubit, in quantum computation. The fundamental quantum operations, such as single- and two-qubit gates, have been demonstrated. However, the fidelity of a quantum gate is easily compromised by inadequate qubit initialisation or incorrect settings of experimental parameters. This thesis aims to address those issues, allowing for the complete coherent control of the trapped ion qubit. This thesis describes the construction and testing of a new ion trap apparatus for optimal control of a trapped ion qubit, which ideally makes the quantum gates more robust against experimental parameters. This thesis extends the two-level Ramsey interferometry to higher order in a trapped ion. Creation and certification of the motional superposition require excellent control of the trapped ion qubit. We prepare a motional superposition state with undesired AC Stark shift due to the off-resonant carrier compensated by our compensation scheme. We successfully certify the superposition consists of three motional Fock states, $(\ket{0}+\ket{1}+\ket{2})/\sqrt{3}$, using a robust certifier derived from statistical moments of the interference pattern. The thesis presents the results of a Bayesian estimator that estimates the Rabi frequency and detuning frequency by processing the measurement records via Bayes' theorem. We compare the estimate from the Bayesian estimator and the standard fitting method, in which Rabi frequency and detuning are estimated by fitting the Rabi oscillation and the frequency spectrum of the ion, and found the Bayesian estimator can estimate those unknown parameters as accurately as the standard fitting method, but only requires less than one-hundredth of measurements necessary for the fitting method. We also experimentally demonstrate measurement-based cooling, which is an alternative way to cool the ion to its ground state. Contrary to resolved sideband cooling, which is routinely used for the ground state cooling in our experiment, this cooling method probabilistically prepares the ion in its motional ground state. We perform a state-dependent mapping operation that maps the ion's atomic state to either $\ket{g}$ or $\ket{e}$ conditioned on its motional states: the ion's atomic state is mapped to $\ket{e}$ if its motional state is $\ket{0}$; otherwise the ion's atomic state is mapped to $\ket{g}$. The following projective measurement of the atomic state of the ion enables the discrimination between the motional ground state and the motional excited states. Therefore we can prepare the ion in the motional ground state by selecting the instances where the ion is measured to be in $\ket{e}$, which heralds the motional ground state. In the near future, the group will begin a project to implement and evaluate recent proposals for making quantum gates robust against a mis-set of frequency using a polychromatic light field.Open Acces