In this thesis, the positioning accuracy of the techniques in Taiwan¡¦s environment can be estimated by using the existing positioning algorithms. The satellite interferer location techniques for geostationary satellites can produce an error ellipse by measuring time difference of arrival (TDOA) and frequency difference of arrival (FDOA) between two signals which pass through the different uplink and downlink path of two satellites. In order to reduce the positioning error of the TDOA/FDOA technique, we proposed a method that using a helicopter to achieve the multibeam antenna (MBA) positioning. Using angle measurement, the positioning is carried out by fitting the measured power ratio of the interference signals received by the multibeam antenna to the gain ratio of the beams as a function of the incoming angle. This hybrid positioning technique was shown to reduce the positioning error and search area of the error ellipse.

No description available.

<p>Ultra wideband (UWB) communication systems refers to systems whose bandwidth is many times greater than the “narrowband” systems (refers to a signal which occupies only small amount of space on the radio spectrum). UWB can be used for indoor, communications for high data rates, or very low data rates for substantial link distances because of the extremely large bandwidth, immune to multi-path fading, penetrations through concrete block or obstacles. UWB can also used for short distance ranging whose applications include asset location in a warehouse, position location for wireless sensor networks, and collision avoidance.</p><p>In order to verify analytical and simulation results with real-world measurements, the need for experimental UWB systems arises. The Institute of Communications Engineering [IANT] has developed a low-cost experimental UWB positioning system to test UWB based positioning concepts. The mobile devices use the avalanche effect of transistors for simple generation of bi-phase pulses and are TDMA multi-user capable. The receiver is implemented in software and employs coherent cross-correlation with peak detection to localize the mobile unit via Time-Difference-Of-Arrival (TDOA) algorithms. Since the power of a proposed UWB system’s signal spread over a very wide bandwidth, the frequencies allocated to multiple existing narrowband systems may interfere with UWB spectrum. The goal of the filters discussed in this project is to cancel or suppress the interference while not distort the desired signal. To investigate the interference, we develop a algorithm to calculate the interference tones. In this thesis, we assume the interference to be narrowband interference (NBI) modeled as sinusoidal tones with unknown amplitude, frequency and phase. If we known the interference tones then it may be removed using a simple notched filter. Herein, we chose an adaptive filter so that it can adjust the interference tone automatically and cancel. In this thesis I tested adaptive filter technique to cancel interference cancellation (ie) LMS algorithm and Adaptive Noise Cancellation (ANC) technique. In this thesis performance of the both filters are compared.</p>

The use of spread spectrum signals has increased dramatically in military applications. Finding methods for detecting and positioning of these signals have become interesting research areas for signal intelligence purposes. One method is to measure the time difference of arrival (TDOA) that occurs when two receivers are synchronous and spatially separated. Based on the TDOA-technique an audio-demonstrator has been developed and implemented. This report describes the theory for how sound received in microphones can be used to extract information about the transmitter’s position from the measured time difference. The technique has been implemented and tested in a non-silencing room where sound from a loudspeaker has been recorded into MATLAB through the use of microphones. By correlating the received signals, an estimation of the time difference can be made. A hyperbolic function represents all possible transmitter positions for the given time difference. With three of more receivers a single position can be estimated. With an accuracy within a couple of hundreds of a degree, a direction can be estimated with simulated signals for a given SNR (usually 25dB) or a position within a few centimetres when the transmitter is a couple of meters away. Tests with real audio signals show less satisfying results. The position can at best be estimated with an accuracy of 5% of the distance to the receiver when the microphones are spread out 0.7m apart. The performance of the audio-demonstrator can be improved by using better methods for finding the points of intersection between hyperbolas and by weighting the estimated time differences.

Ultra wideband (UWB) communication systems refers to systems whose bandwidth is many times greater than the “narrowband” systems (refers to a signal which occupies only small amount of space on the radio spectrum). UWB can be used for indoor, communications for high data rates, or very low data rates for substantial link distances because of the extremely large bandwidth, immune to multi-path fading, penetrations through concrete block or obstacles. UWB can also used for short distance ranging whose applications include asset location in a warehouse, position location for wireless sensor networks, and collision avoidance. In order to verify analytical and simulation results with real-world measurements, the need for experimental UWB systems arises. The Institute of Communications Engineering [IANT] has developed a low-cost experimental UWB positioning system to test UWB based positioning concepts. The mobile devices use the avalanche effect of transistors for simple generation of bi-phase pulses and are TDMA multi-user capable. The receiver is implemented in software and employs coherent cross-correlation with peak detection to localize the mobile unit via Time-Difference-Of-Arrival (TDOA) algorithms. Since the power of a proposed UWB system’s signal spread over a very wide bandwidth, the frequencies allocated to multiple existing narrowband systems may interfere with UWB spectrum. The goal of the filters discussed in this project is to cancel or suppress the interference while not distort the desired signal. To investigate the interference, we develop a algorithm to calculate the interference tones. In this thesis, we assume the interference to be narrowband interference (NBI) modeled as sinusoidal tones with unknown amplitude, frequency and phase. If we known the interference tones then it may be removed using a simple notched filter. Herein, we chose an adaptive filter so that it can adjust the interference tone automatically and cancel. In this thesis I tested adaptive filter technique to cancel interference cancellation (ie) LMS algorithm and Adaptive Noise Cancellation (ANC) technique. In this thesis performance of the both filters are compared.

For target location and tracking in wireless communication systems, mobile target positioning and tracking play an important role. Since multi-sensor system can be used as an efficient solution to target positioning process, more accurate target location estimation and tracking results can be obtained. However, both the deployment of designed multi-sensor and location algorithm may affect the overall performance of position location. In this thesis, based on the time difference of arrival (TDOA), two closed-form least-square location methods, spherical-interpolation (SI) method and spherical-intersection (SX) method are used to estimate the target location. The two location methods are different from the usual process of iterative and nonlinear minimization. The locations of the target and the designed multiple sensors may yield geometric effects on location performance. The constraints and performance of the two location methods will first be introduced. To achieve real-time target tracking, the Kalman filtering structures are used to combine the SI and SX methods. Because these two positioning and tracking systems have different and complementary performance inside and outside the multi-sensor array, we consider using data fusion to improve location estimation results by using interacting multiple model (IMM) based estimator, in which internal filters running in parallel are designed as the SX-KF1 and the SI-KF2. However, due to the time-varying characteristics of measurement noises, we propose an adjusting scheme for measurement noise variance assignment in the Kalman filters to obtain improved location estimation results. Simulation results are obtained by running Matlab program. In three-dimensional multi-sensor array scenarios, the results of moving target location estimation shows that the IMM-based estimators effectively improve the position performance.

Accurate indoor geolocation is an important and novel emerging technology for commercial, public safety, and military applications. Since most wireless communication systems used for indoor position location may suffer from dense multipath situation, which leads to a severe degradation of position accuracy. The improved TDOA/AOA(Time Difference of Arrival/ Angle of Arrival) position location for indoor ultra-wide band (UWB) systems in the thesis improves the position accuracy of indoor location by using fine resolution of UWB signals. In the line of sight situation, by means of increasing angle of arrival (AOA) information to time difference of arrival (TDOA) based location to achieve the goal of accurate indoor geolocation and provides non-line of sight (NLOS) error mitigation for time measurement and AOA selection to suppress the impact to position accuracy in NLOS environment. Finally, the extended Kalman filter is used to perform position tracking of the target. In the simulations, the NLOS error in time measurement is produced according to the characteristics of indoor UWB channel. Several assumptions of NLOS errors are made in angular measurement. It is observed that proposed method efficiently mitigates the position error in NLOS environment, and detect if the NLOS exists between base station and mobile station immediately.

<p>The use of spread spectrum signals has increased dramatically in military applications. Finding methods for detecting and positioning of these signals have become interesting research areas for signal intelligence purposes. One method is to measure the time difference of arrival (TDOA) that occurs when two receivers are synchronous and spatially separated. Based on the TDOA-technique an audio-demonstrator has been developed and implemented. This report describes the theory for how sound received in microphones can be used to extract information about the transmitter’s position from the measured time difference. The technique has been implemented and tested in a non-silencing room where sound from a loudspeaker has been recorded into MATLAB through the use of microphones. By correlating the received signals, an estimation of the time difference can be made. A hyperbolic function represents all possible transmitter positions for the given time difference. With three of more receivers a single position can be estimated. With an accuracy within a couple of hundreds of a degree, a direction can be estimated with simulated signals for a given SNR (usually 25dB) or a position within a few centimetres when the transmitter is a couple of meters away. Tests with real audio signals show less satisfying results. The position can at best be estimated with an accuracy of 5% of the distance to the receiver when the microphones are spread out 0.7m apart. The performance of the audio-demonstrator can be improved by using better methods for finding the points of intersection between hyperbolas and by weighting the estimated time differences.</p>

Position information is important for various applications, including location-aware communications, autonomous driving, industrial internet of things (IoT). Geometry based techniques such as time-of-arrival (TOA), time-difference-of-arrival (TDOA), and angle-of-arrival (AOA) are widely used and can be formed as optimization prob lems. In order to solve these optimization problems efficiently, stochastic optimization methods are discussed in this work in solving target positioning problems and tackling key issues in location-based applications. Firstly, the direction of arrival (DOA) estimation problem is studied in this work. Grid search is useful in the algorithms such as maximum likelihood estimator (MLE), MUltiple SIgnal Classification (MUSIC), etc. However, the computational cost is the main drawback. To speed up the search procedure, we implement random ferns to extract the features from the beampatterns of different DOAs and use these features to identify potential angle candidates. Then, we propose an ultrasonic air-writing system based on DOA estimation. In this application, stochastic optimization methods are implemented to solve gesture classification problems. This work shows that stochastic optimization methods are effective tools to address and benchmark practical positioning-related problems. Next, we discuss how to select antennas properly to reduce the expectation of DOA estimation error in a switch-based multiple-input-multiple-output (MIMO) system. Cram`er Rao lower bound (CRLB) expresses a lower bound on the variance of an unbiased estimator, but it does not work well for low SNR scenarios. We use DOA threshold-region approximation as an indicator and propose a greedy algorithm and a neural network-based algorithm. Finally, we propose a joint time difference of arrival (TDOA) and phase difference of arrival (PDOA) localization method. It is shown that the phase difference, which is also widely used in DOA estimation, can improve the performance of the well established TDOA technique. Although the joint TDOA/PDOA cost function has a lot of local minima, accurate estimates can be obtained effectively by choosing an appropriate initial estimation and using particle swarm optimization (PSO).

This thesis deals with the use of spatial awareness methods within technologies designed for creation of short-range wireless sensor networks. The thesis analyzes several techniques that can be used to estimate position of objects within the sensor network. For a practical solution, a method based on measuring the time differences of the sent messages was chosen. A circuit implementation of a network node based on the DW1000 chip, which works on ultra-wideband transmission technology, was implemented. A sensor network with the appropriate user application for its operation and display of localization results was also implemented.