The purpose of this study is to undertake the analysis of underwater detection and tracking using the Doppler phase-shift effects to enhance the detection capability. The fundamental principle is owing to the fact that the M-sequence may result in a better distinction to the echo returning from a moving target than the traditional LFM signal, in that the matched filter using M-sequence may need to estimate and compensate the doppler shift due to the moving target. The experiments were carried out in two harbors: True Love Pier of Kaohsiung Harbor (TLPKH) and Woods Hole Hrabor (WHH). The TLPKH is an inner harbor, with sediment being mud, while the WHH is an open types, suitable for target detection. The results from WHH experiment has shown that when the results from M-sequence and traditional LFM signal were compared, the M-sequence yields much better capability both in detection and estimation of the speed of the moving target along the beam axis. However, the signals from TLPKH were too weak for analysis, therefore, the data from TLPKH were used to analyze the environmental noise, transmission loss, which were combined with estimated values for sonar parameters to conduct the sonar performance analysis in an harborenvironment.

abstract: Ultrasound imaging is one of the major medical imaging modalities. It is cheap, non-invasive and has low power consumption. Doppler processing is an important part of many ultrasound imaging systems. It is used to provide blood velocity information and is built on top of B-mode systems. We investigate the performance of two velocity estimation schemes used in Doppler processing systems, namely, directional velocity estimation (DVE) and conventional velocity estimation (CVE). We find that DVE provides better estimation performance and is the only functioning method when the beam to flow angle is large. Unfortunately, DVE is computationally expensive and also requires divisions and square root operations that are hard to implement. We propose two approximation techniques to replace these computations. The simulation results on cyst images show that the proposed approximations do not affect the estimation performance. We also study backend processing which includes envelope detection, log compression and scan conversion. Three different envelope detection methods are compared. Among them, FIR based Hilbert Transform is considered the best choice when phase information is not needed, while quadrature demodulation is a better choice if phase information is necessary. Bilinear and Gaussian interpolation are considered for scan conversion. Through simulations of a cyst image, we show that bilinear interpolation provides comparable contrast-to-noise ratio (CNR) performance with Gaussian interpolation and has lower computational complexity. Thus, bilinear interpolation is chosen for our system. / Dissertation/Thesis / M.S. Electrical Engineering 2013

Besides structural imaging, OCT can be used to estimate axial velocities of the sample resolved in depth by Dopplerprocessing. In Fourier domain OCT (FD-OCT), this is accomplished by measuring the phase difference (i.e. phase shift) between timely separated A-scans at the same depth. In most cases, these data are disturbed by noise caused by intrinsic noise of the OCT system, specified by the SNR, and decorrelation noise caused by the transversal movement of the optical beam relative to the sample. Since the first use of Doppler methods in OCT, many methods to reduce the phase shift noise by averaging have been presented. While all these methods use a fixed set of consecutive A-scans, the best method, exhibiting no bias and having the smallest standard deviation, was questionable. Recently, Doppler processing methods depending on the mentioned noise sources and delivering the most likely phase shift and thereby axial velocity became available. The relation of these methods to previously known methods like the Kasai estimator, maximum likelihood estimator (MLE) and joint spectral and time domain OCT (jSTdOCT) will be discussed.

In this thesis, an Experimental Radar System is designed and constructed for use in experimental radar studies such as clutter measurement and target detection, both in the laboratory and outdoor. COTS laboratory equipments are utilized as hardware elements of the radar and MATLAB is used as signal processing and user interface software tool. Vector signal generator (as transmitter), spectrum analyzer with vector signal analysis (as receiver), a high power amplifier, a low noise amplifier, horn antennas and a computer are the hardware units of the system. Various transmit signals are generated and pulse Doppler processing is performed at the receiver side. The system is controlled through the user interface which runs on a PC.

The performance of radar detection and imaging systems strongly depends on the characteristics of radar clutter. In order to improve the radar signal processing algorithms, successful analysis and modeling of radar clutter are required. For a successful model of radar clutter, both the spectral and statistical characteristics of the clutter should be revealed. Within the scope of this study, an experimental radar data acquisition system is established to analyze radar clutter. The hardware and the data processing system are first verified using generic signals and then a set of measurements is taken in the open terrain. In this thesis, the limitations and problems encountered during the establishment of the system are explained in detail. The spectral and statistical analyses performed on the recorded data are examined. The temporal and spatial behavior of the measured clutter data are explored. The hypothetical models proposed so far in the literature are tested on the experimental data and the fitting of models to the experimental data is confirmed using various goodness-of-fit tests. Finally, the results of the analyses are interpreted in the light of the radar system parameters and the characteristics of the illuminated terrain.

Due to recent improvements, robots are more applicable in factories and various production lines where smoke, fog, dust, and steam are inevitable. Despite their advantages, robots introduce new safety requirements when combined with humans. Radars can play a crucial role in this context by providing safe zones where robots are operating in the absence of humans. The goal of this Master’s thesis is to investigate different clutter suppression methods for single radar sensor reflection data via digital signal processing. This was done in collaboration with ABB Jokab AB, Sweden. The calculations and implementation of the digital signal processing algorithms are made with Octave. A critical problem is false detection that could possibly cause irreparable damage. Therefore, a safety system with an extremely low false alarm rate is desired to reduce costs and damages. In this project, we have studied four different digital low pass filters: moving average, multiple-pass moving average, Butterworth, and window-based filters. The results are compared, and it is ascertained that all the results are logically compatible, broadly comparable, and usable in this context.

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. / 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.