ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / Spatial multiplexing (SM) systems have received significant attention because the architecture offers high spectral efficiency. However, relatively little research exists on optimization of SM systems in the presence of jamming. In a spatially uncoded SM system, such as V-BLAST, the channel state information is assumed to be unavailable a priori at both transmitter and receiver. Here, Kalman filtering is used to estimate the Rayleigh fading channel at the receiver. The spatial correlation of the jammer plus noise is also estimated, and spatial whitening to reject the jammers is employed in both the Kalman channel estimator and detector. To avoid the exponential complexity of maximum-likelihood (ML) detection, the QRD-M algorithm is employed. In contrast to sphere decoding, QRD-M has fixed decoding complexity of order O(M), and is thus attractive for hardware implementation. The performance of the joint Kalman filter channel estimator, spatial whitener and QRD-M detector is verfied by simulations.

ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / An acoustic modem employing direct-sequence spread-spectrum (DSSS) signaling is considered with LDPC coding. The underwater acoustic channel is tracked using a Kalman filter which requires accurate data decisions. To improve KF performance and reduce the overall error rate, joint iterative LDPC decoding and channel estimation is proposed based on a factor graph and sum-product algorithm approximation. In this scheme, the decoder posterior log likelihood ratios (LLRs) provide data decisions for the KF. Decoder extrinsic LLRs are similarly incorporated into the detector LLRs to yield improved priors for decoding. Error rate simulations of the overall modem are provided for a shallow-water channel model with Ricean/Rayleigh fading.

A typical petro-chemical or oil-refining plant is known to operate with hundreds if not thousands of control loops. All critical loops are primarily required to operate at their respective optimal levels in order for the plant to run efficiently. With such a large number of vital loops, it is difficult for engineers to monitor and maintain these loops with the intention that they are operating under optimum conditions at all times. Parts of processes are interactive, more so nowadays with increasing integration, requiring the use of a more advanced protocol of control systems. The most widely applied advanced process control system is the Model Predictive Controller (MPC). The success of these controllers is noted in the large number of applications worldwide. These controllers rely on a process model in order to predict future plant responses. Naturally, the performance of model-based controllers is intimately linked to the quality of the process models. Industrial project experience has shown that the most difficult and time-consuming work in an MPC project is modeling and identification. With time, the performance of these controllers degrades due to changes in feed, working regime as well as plant configuration. One of the causes of controller degradation is this degradation of process models. If a discrepancy between the controller’s plant model and the plant itself exists, controller performance may be adversely affected. It is important to detect these changes and re-identify the plant model to maintain control performance over time. In order to avoid the time-consuming process of complete model identification, a model validation tool is developed which provides a model quality indication based on real-time plant data. The focus has been on developing a method that is simple to implement but still robust. The techniques and algorithms presented are developed as far as possible to resemble an on-line software environment and are capable of running parallel to the process in real time. These techniques are based on parametric (regression) and nonparametric (correlation) analyses which complement each other in identifying problems -iiwithin on-line models. These methods pinpoint the precise location of a mismatch. This implies that only a few inputs have to be perturbed in the re-identification process and only the degraded portion of the model is to be updated. This work is carried out for the benefit of SASOL, exclusively focused on the Secunda plant which has a large number of model predictive controllers that are required to be maintained for optimal economic benefit. The efficacy of the methodology developed is illustrated in several simulation studies with the key intention to mirror occurrences present in industrial processes. The methods were also tested on an industrial application. The key results and shortfalls of the methodology are documented. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2010.

The desire for precise polymer property control, minimum wastage through grade transitions, and early instrument fault detection, has led to a significant effort in the modelling and control of ethylene polymerisation world-wide. Control is difficult due to complex inter-relationships between variables and long response times from gas to solid phase. The approach in this study involves modelling using the kinetic equations. This forms the basis of a scheme for real-time kinetic parameter identification and Kalman filtering of the reactor gas composition. The scheme was constructed off-line and tested on several industrial polymer grades using historical plant data. The scheme was also converted into a form for use on the linear low-density polyethylene plant, Poly 2, at POLlFIN Limited. There proved to be no difficulty in the identification step, but the Kalman filter requires more tuning for reliable fault detection. The software has been commissioned on-line and results from the POLlFIN plant match the off-line model exactly. / Thesis (M.Sc.Eng.)-University of Natal, Durban, 2000.

CIVINS / The US Navy has identified a need for an autonomous, persistent, forward deployed system to Detect, Classify, and Locate submarines. In this context, we investigate a novel method for multiple sensor platforms acting cooperatively to locate an uncooperative target. Conventional tracking methods based on techniques such as Kalman filtering or particle filters have been used with great success for tracking targets from a single manned platform; the application of these methods can be difficult for a cooperative tracking scenario with multiple unmanned platforms that have considerable navigation error. This motivates investigation of an alternative, set-based tracking algorithm, first proposed by Detweiler et al. for sensor network localization, to the cooperative tracking problem. The Detweiler algorithm is appealing for its conceptual simplicity and minimal assumptions about the target motion. The key idea of this approach is to compute the temporal evolution of potential target positions in terms of bounded regions that grow between measurements as the target moves and shrink when measurements do occur based on an assumed worst-case bound for uncertainty. In this thesis, we adapt the Detweiler algorithm to the scenario of cooperative tracking for persistent undersea surveillance, and explore its limitations when applied to this domain. The algorithm has been fully implemented and tested both in simulation and with postprocessing of autonomous surface craft (ASC) data from the PLUSNet Monterey Bay 2006 experiment. The results indicate that the method provides disappointing performance when applied to this domain, especially in situations where communication links between the autonomous tracking platforms are poor. We conclude that the method is more appropriate for a large N tracking scenario, with a large number of small, expendable tracking nodes, instead of our intended scenario with a smaller number of more sophisticated mobile trackers. / CIVINS / US Navy (USN) author.

Approved for public release; distribution is unlimited / Design requirements for a small satellite (NPSAT-1) Attitude Determination and Control Subsystem (ADCS) is a three-axis stabilized spacecraft which requires a control attitude of +/- 1.0 degrees and knowledge attitude of +/- 0.1 degree. Several design aspects are considered in development of attitude control systems for a small satellite, such as: spacecraft dynamics, space environment, disturbance torques, orbit type, and spacecraft complexity. The ideal spacecraft's attitude sensor is a rate gyroscope, which provides rate information to the attitude control system. In the case of NPSAT-1, due to budget constraints alternative sensors will be utilized, such as: a three-axis magnetometer, earth sensors, and a Global Positioning System (GPS). A small satellite designed to have a three-axis stabilized, biased momentum system, must have a robust control system and requires a momentum wheel to provide stiffness to maintain attitude, and magnetic torque rods on each axis. The current design of NPSAT-1 uses all of these sensors to provide rate information for damping and stability to the control system that requires a complicated attitude control design. The purpose of this attitude control design simulation is to investigate and propose a control law utilizing a single pitch momentum wheel and three magnetic torque rods. A further proposal is to utilize a constant speed momentum wheel to avoid momentum damping and over speed, replace the pitch control with magnetic torquers, and develop a Kalman filter estimator to provide all the required angular rates. / Lieutenant Commander, United States Navy

Luo Yilun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 87-91). / Abstracts in English and Chinese. / Chapter 1. --- Introduction --- p.1 / Chapter 1.1. --- Organization --- p.3 / Chapter 2. --- Architecture of MAG-μIMU --- p.5 / Chapter 2.1. --- Hardware for Attitude Filter --- p.5 / Chapter 2.2. --- Handwriting Recording for a Digital Writing Instrument --- p.7 / Chapter 3. --- Inertial Tracking for Handwriting --- p.9 / Chapter 3.1. --- Spatial Descriptions and Transformations --- p.9 / Chapter 3.1.1. --- Vector Description and Position of a Frame --- p.9 / Chapter 3.1.2. --- Coordinate Transformation and Orientation of a Frame --- p.10 / Chapter 3.1.3. --- Kinematics for Digital Writing Instruments --- p.12 / Chapter 3.1.4. --- Vector Rotation --- p.16 / Chapter 3.2. --- Euler Angles for Rotation in Space --- p.17 / Chapter 3.3. --- Euler Angles Attitude Kinematics --- p.19 / Chapter 3.4. --- Singular Problem --- p.19 / Chapter 4. --- Attitude in Quaternion --- p.22 / Chapter 4.1. --- Quaternion Operations --- p.22 / Chapter 4.1.1. --- Quaternion Conjugate --- p.23 / Chapter 4.1.2. --- Quaternion Norm --- p.24 / Chapter 4.1.3. --- Quaternion Inverse --- p.24 / Chapter 4.2. --- Orientation Description in Quaternion --- p.24 / Chapter 4.3. --- Attitude Kinematics in Quaternion --- p.25 / Chapter 5. --- Kalman Filter --- p.27 / Chapter 5.1. --- Time Update --- p.28 / Chapter 5.2. --- Measurement Update --- p.29 / Chapter 5.2.1. --- Maximum a Posterior Probability --- p.29 / Chapter 5.2.2. --- Batch Least-Square Estimation --- p.31 / Chapter 5.2.3. --- Measurement Update in Kalman Filter --- p.34 / Chapter 5.3. --- Kalman Filter Summary --- p.36 / Chapter 6. --- Extended Kalman Filter --- p.38 / Chapter 7. --- Attitude Extended Kalman Filter --- p.41 / Chapter 7.1. --- Time Update Model --- p.41 / Chapter 7.1.1. --- Attitude Strapdown Theory for a Quaternion --- p.41 / Chapter 7.1.2. --- Error Model for Time Update --- p.42 / Chapter 7.2. --- Measurement Update Model --- p.43 / Chapter 7.2.1. --- Error Model for the Measurement Update --- p.45 / Chapter 7.3. --- Summary --- p.46 / Chapter 8. --- Experiment Results --- p.47 / Chapter 8.1. --- Experiment for Attitude EKF based on MAG-μIMU --- p.47 / Chapter 8.1.1. --- Simulation Test --- p.48 / Chapter 8.1.2. --- Experiment Test --- p.49 / Chapter 8.2. --- Writing Application based on Attitude EKF Compensation --- p.52 / Chapter 8.2.1. --- Stroke Segment Kalman Filter --- p.54 / Chapter 8.2.2. --- Zero Velocity Compensation --- p.58 / Chapter 8.2.3. --- Complementary Attitude EKF for Writing Experiment --- p.60 / Chapter 9. --- Future Work --- p.73 / Chapter 9.1. --- Unscented Kalman Filter --- p.73 / Chapter 9.1.1. --- Least-square Estimator Structure --- p.73 / Chapter 9.1.2. --- Unscented Transform --- p.74 / Chapter 9.1.3. --- Unscented Kalman Filter --- p.76 / Chapter 9.2. --- Experiment Result --- p.81 / Chapter 10. --- Conclusion --- p.85 / Chapter 10.1. --- Attitude Extended Kalman Filter --- p.85 / Chapter 10.2. --- Complementary Attitude EKF --- p.85 / Chapter 10.3. --- Unscented Kalman Filter --- p.86 / Chapter 10.4. --- Future Work --- p.86 / Bibliography --- p.87 / Appendix A --- p.92

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by Lawrence Charles Vallot. / M.S.

The Global Positioning System (GPS) has become popular research and application interests in surveying and many other areas. Nowadays, the accuracy of the Differential GPS can easily reach the order of a few meters. Yet, there are still many ways to exploit the GPS system signal carrier to improve the accuracy to less than meter level. In this thesis, a new approach to improve the accuracy to less than meter level is presented while the observer is in the dynamic situation. In order to reach the sub-meter accuracy, we measure on the carrier phase difference (The L1 carrier frequency is 1575.42 Mhz, 1=19 em) between a reference point A and a primary point B. This actually means we work on the accuracy of centimeter. In this proposed method of the precision survey, first the Differential GPS is used to fix the position in the accuracy of meter level, and then by measuring the signal carrier relative difference we can work on the accuracy in the accuracy level of the wavelength (19 cm). The measuring on the relative carrier phase will introduce the problem of initial modulo 2π phase (integer wavelength) ambiguity. To solve the initial integer ambiguity, A Multiple Model Estimation Algorithm (MMEA) which was developed by D.T. Magill in 1965 is applied. The MMEA is composed of a bank of parallel Kalman filters, all operating on the input measurement sequence simultaneously. Each filter in the bank of filters is modeled around a different hypothesis. The number of the required parallel filters is the number of hypothesis of integer ambiguity which is determined by the error range of the differential phase measurement. And the error range of the differential phase measurement is related to the accuracy of the Differential GPS. The precision positioning by MMEA method has some advantage compares with other methods now being used . . It does not require continuous observation of the satellites initially. . Kalman filter is recursive technique. So it has the potential of on-line . . Kalman filter is widely used in navigation and approved to be very efficient and versatile. Computer simulation results are given for a hypothetical GPS system. They demonstrate that the MMEA can effectively solve the integer wavelength ambiguity problem in dynamic situation. The simulation results presented are especially encouraging with regard to the flexibility and efficiency in precision survey. A further improvement of precision surveying by GPS is also discussed in the last Chapter. By using Markov Model and Verterbi Algorithm, a more flexible and reliable precision surveying method could be available.

This thesis investigates the detection and classification of small boats using a passive sonar system. Noise radiated from a small boats consists of broadband noise and harmonically related tones that correspond to parameters in the boats engine and propeller. A novel signal processing method for detection and discrimination of noise radiated from small boats has been developed. There are two main components to the algorithm. The first component detects the presence of small boats by the harmonic tonals radiated from the boat propeller and engine. The second component was designed to extract the a signature from passive sonar data. The Harmonic Extraction and Analysis Tool (HEAT) was designed to estimate the fundamental frequency of the harmonic tones, track the fundamental frequency using a Kalman filter, and automatically extract the amplitudes of the harmonic tonals to generate a harmonic signature for the boat. The algorithm is shown to accurately extract theses signatures, and results show that the signatures are unique enough that the same boat passing by the hydrophone multiple times can be recognized.