­^¤å´£­n¡G Two different topics associated with their respective applications are proposed in this thesis. The first topic is focused on the implementation of a 4-Kb 500MHz 4-T CMOS SRAM using low-Vthn bitline drivers and high-Vthp latches. The storage of data is realized by a pair of cross-coupled PMOS transistors, while the wordline is controlled by a pair of NMOS transistors. The advantages of dual threshold voltage transistors can be used to reduce the access time and maintain data retention at the same time. The second topic is the implementation of cascade address transition detector (ATD) design with high noise immunity. We employ a feedback loop to prevent interference of noise and false alarm signal to stabilize the generated CS (Chip Select) signal. Besides, we use one delay buffer to dynamically adjust the CS strobe.

Most of the operating vessel traffic management systems experience problems, such as track loss and track swap, which may cause confusion to the traffic regulators and lead to potential hazards in the harbour operation. The reason is mainly due to the limited adaptive capabilities of the algorithms used in the detection process. The decision on whether a target is present is usually based on the magnitude of the returning echoes. Such a method has a low efficiency in discriminating between the target and clutter, especially when the signal to noise ratio is low. The performance of radar target detection depends on the features, which can be used to discriminate between clutter and targets. To have a significant improvement in the detection of weak targets, more obvious discriminating features must be identified and extracted. This research investigates conventional Constant False Alarm Rate (CFAR) algorithms and introduces the approach of applying ar1ificial intelligence methods to the target detection problems. Previous research has been unde11aken to improve the detection capability of the radar system in the heavy clutter environment and many new CFAR algorithms, which are based on amplitude information only, have been developed. This research studies these algorithms and proposes that it is feasible to design and develop an advanced target detection system that is capable of discriminating targets from clutters by learning the .different features extracted from radar returns. The approach adopted for this further work into target detection was the use of neural networks. Results presented show that such a network is able to learn particular features of specific radar return signals, e.g. rain clutter, sea clutter, target, and to decide if a target is present in a finite window of data. The work includes a study of the characteristics of radar signals and identification of the features that can be used in the process of effective detection. The use of a general purpose marine radar has allowed the collection of live signals from the Plymouth harbour for analysis, training and validation. The approach of using data from the real environment has enabled the developed detection system to be exposed to real clutter conditions that cannot be obtained when using simulated data. The performance of the neural network detection system is evaluated with further recorded data and the results obtained are compared with the conventional CFAR algorithms. It is shown that the neural system can learn the features of specific radar signals and provide a superior performance in detecting targets from clutters. Areas for further research and development arc presented; these include the use of a sophisticated recording system, high speed processors and the potential for target classification.

International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California / GPS signal fixed dwell and variable dwell time sequential search algorithms are compared with probability of false alarm and detection and searching rate. An adaptive search algorithm is proposed according to different work modes and interference or jam circumstance, which has effectively improved signal acquiring speed and reliability. Mathematical simulation shows its correction and feasible.

International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / It is need to design acquisition and tracking for code loop and carrier loop to detect the high dynamic Global Position System (GPS) signal. Acquiring signal quickly and shortening acquisition time in the cold case are key technology of a high dynamic GPS receiver. Moreover, fast acquisition of C/A code is the base of code tracking and carrier acquisition and tracking. This paper describes elements and implementation of a new parallel-sequential search Algorithm to acquire C/A code of the high dynamic GPS signal. And combined with a 12-channel correlator named GP2021 produced by GEC Co., the arithmetic implementation to acquire C/A code of the high dynamic GPS signal used sequential search based on DSP technology is also given.

No description available.

The Federal Aviation Administration (FAA) wishes to minimize the overall operational costs of their aviation security detection systems. These systems consist of a collection of security devices. The objective of this research is to develop an algorithm to design the optimal system of devices. The Secure Air Flight Effectiveness (SAFE) Model accomplishes this objective by using the probability of detection and the probability of giving a false alarm for each individual device. A Generalized Hill Climbing (GHC) algorithm was implemented to identify the system with the minimum operational cost. Suggestions for future research directions are also included. / Master of Science

International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California / An Improved AMI (Alternate Mark Inverse) Code used in telemetry system is proposed, its implementation and properties analysis are reported, including error performance analysis, power spectrum analysis, the relationship between acqusition probability of the first frame marker and error threshold and length of frame marker, etc. This type of code has the approximately identical power spectrum performance as the AMI Code. In addition, there have no long continuous zeroes in the data stream, which will cause phase-locked loop to fail. Using the Improved AMI Code, the equal probability of 0 and 1 is changed, which will increase acqusition probability of the first frame marker. Detailed description about how to create the Improved AMI Code is also discussed in this paper.

Maritime surveillance radars are critical in commerce, transportation, navigation, and defense. However, the sea environment is perhaps the most challenging of natural radar backdrops because maritime radars must contend with electromagnetic backscatter from the sea surface, or sea clutter. Sea clutter poses unique challenges in very low grazing angle geometries, where typical statistical assumptions regarding sea clutter backscatter do not hold. As a result, traditional constant false alarm rate (CFAR) detection schemes may yield a large number of false alarms while objects of interest may be challenging to detect. Solutions posed in the literature to date have been either computationally impractical or lacked robustness. This dissertation explores whether fully polarimetric radar offers a means of enhancing detection performance in low grazing angle sea clutter. To this end, MIT Lincoln Laboratory funded an experimental data collection using a fully polarimetric X-band radar assembled largely from commercial off-the-shelf components. The Point de Chene Dataset, collected on the Atlantic coast of Massachusetts’ Cape Ann in October 2015, comprises multiple sea states, bandwidths, and various objects of opportunity. The dataset also comprises three different polarimetric transmit schemes. In addition to discussing the radar, the dataset, and associated post-processing, this dissertation presents a derivation showing that an established multiple input, multiple output radar technique provides a novel means of simultaneous polarimetric scattering matrix measurement. A novel scheme for polarimetric radar calibration using a single active calibration target is also presented. Subsequent research leveraged this dataset to develop Polarimetric Co-location Layering (PCL), a practical algorithm for mitigation of low grazing angle sea clutter, which is the most significant contribution of this dissertation. PCL routinely achieves a significant reduction in the standard CFAR false alarm rate while maintaining detections on objects of interest. Moreover, PCL is elegant: It exploits fundamental characteristics of both sea clutter and object returns to determine which CFAR detections are due to sea clutter. We demonstrate that PCL is robust across a range of bandwidths, pulse repetition frequencies, and object types. Finally, we show that PCL integrates in parallel into the standard radar signal processing chain without incurring a computational time penalty.

With current advances in sensors and information technology, online measurements of process variables become increasingly accessible for process control and monitoring. Such measurements may take the shape of curves rather than scalar values. The term Multichannel Functional Data (MFD) is used to represent the observations of multiple process variables in the shape of curves. Generally MFD contains rich information about processes. The challenge of process control in MFD is that Statistical Process Control (SPC) is not directly applicable. Furthermore, there is no systematic approach to interpret the complex variation in MFD. In this research, our objective is to develop an approach to systematically analyze the complex variation in MFD for process change detection and process faulty condition discrimination. The main contributions of this thesis are: MFD decomposition, process change detection, and process faulty condition discrimination. We decomposed MFD into global and local components. The approach reveals global and local variations that are due to global signal shifts and local variations. Global variation was extracted using weighted spline smoothing technique, whereas, local variation was obtained by subtracting the global variation from original signals. Weights were obtained using the local moving average of the generalized residuals. The proposed approach helps in process change detection and process faulty condition discrimination based on further MFD analysis using Principal Curve Regression (PCuR) Test. For process change detection, global variation component was used in the PCuR test. In-control global data sets were used as training data to detect process change that is due to global and local variation. On the other hand, for faulty condition discrimination purpose, local variation component was used in the PCuR test. In-control local variation data sets were used as training data in the PCuR test; therefore, process faulty condition that is due to local variations remains in control, whereas, process faulty condition that is due to global shifts appears as random out of control points in the PCuR test. We applied our approach on real life forging data sets. A simulation study was also conducted to verify the approach and results are promising for wide applications.

Made available in DSpace on 2015-03-26T13:32:14Z (GMT). No. of bitstreams: 1 texto completo.pdf: 2818845 bytes, checksum: be3f419fcc4c9f0b3cb6050f150daf3c (MD5) Previous issue date: 2012-02-16 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / This study aimed to estimate the probabilities of false and true alarms caused by the Cumulative Sum control chart over the i rational subgroups, according to various combinations of size n of subgroup rational, standardized decision interval h* and the tolerance value k*. To study them, were simulated data from a random variable Y, under normal distribution with mean μ0 = 0 and standard deviation 1 s 0 = for a process under statistical control over 50 rational subgroups, for n between 1-16. To this end, 1000 simulations were performed by rational subgroup. Then four out of control processes have been set for the statistical average at all rational subgroup ( μ1 = μ0 +ds 0 ) in which d refers to the displacement of the average in numbers of standard deviations of the process. The probability of false alarm a decreases with the increase, increase and decrease of k*, h* and i respectively, while the probability of true alarm Pd has direct relation to n and i, and inverse relation to h* for the same pre-defined minimum difference between the means μ0 and μ1 considering the choice of k* as being half of that difference in number of standard deviations. Both probabilities of true and false alarms were obtained by the normal and lognormal 3P probability distributions adjusted to the random variable Z(i) + S (i −1)* H . In order to give a power greater than 0.90 and a equal or less than 0.05 or 0.01 were recommended to different combinations of k*, h*, i and n. / O presente trabalho teve por objetivo estimar as probabilidades dos alarmes falsos e verdadeiros provocados pelo gráfico de controle CUSUM tabular ao longo dos i subgrupos racionais, em função de diferentes combinações entre o tamanho n do subgrupo racional, o interval o de decisão padronizado h* e o valor de tolerância k*. Para estudá-los foram simulados dados de uma variável aleatória Y, sob distribuição normal com média μ0 = 0 e desvio-padrão 1 s 0 = para um processo sob controle estatístico para até 50 subgrupos racionais com até 16 repetições. Para tanto, foram realizadas 1000 simulações por subgrupo racional. Em seguida foram estabelecidos outros quatro processos fora de controle estatístico para a média em todos os subgrupos racionais ( μ1 = μ0 +ds 0 ), em que d se refere ao deslocamento da média em número de desvios-padrão do processo. A robabilidade do alarme falso (a ) diminui com os respectivos aumento, aumento e diminuição de k*, h* e i, enquanto a probabilidade do alarme verdadeiro (Pd) possui relação direta com n e i, e inversa com h* para uma mesma diferença mínima pré-definida entre as médias μ1 e μ0 e considerando-se a escolha de k* como sendo a metade desta em número de desvios-padrão. Ambas probabilidades dos alarmes falso e verdadeiro foram obtidas por meio das distribuições de probabilidade normal e lognormal 3P ajustadas à variável aleatória Z(i) + S (i −1) * H . Para conferir um Pd igual ou superior a 0,90 e a igual ou inferior a 0,05 ou 0,01 recomendou-se diferentes combinações de k*, h*, i e n.